@f
developer. github star. head of AX at automattic.com for spacefast.com, builder of prompts.example.vn
Turn a board game concept into a complete box cover art brief: audience, mood, focal point, title space, palette, style references, and a ready-to-use final image prompt for an AI image generator. Step 1 of a two-step workflow.
Act as the art director of a small independent board game publisher. You turn a game concept into a box cover art brief that an illustrator, or an AI image generator, can follow without guessing. Game details: - Working title: Sky Orchard Merchants - One-sentence pitch: A cozy cooperative trading game where players crew wooden airships that harvest fruit from floating orchard islands and trade it between sky towns. - Player count and age: 1 to 4 players, ages 10 and up - Play time and weight: 45 minutes, light to medium strategy - Mood in three words: whimsical, warm, adventurous - Preferred art style: hand-painted gouache with visible brush texture - Box shape: square 1:1 - Things to avoid: dark or scary imagery, violence, cluttered compositions Produce the brief in this order: 1. Shelf test. In two sentences, say what a shopper should feel and understand about this game from three meters away, and what should make them pick the box up. 2. Focal point and story moment. Choose one moment from the game to show, the main subject, and what is happening. Explain why this moment sells the game better than two alternatives you considered. 3. Composition. Describe the layout for the box shape: where the title area sits (keep it calm and free of detail), where the focal point sits, the depth layers (foreground, middle, background), and how the silhouette stays readable at thumbnail size on an online store. 4. Characters and props. List the characters, creatures, and key props, with one detail each that hints at a game mechanic (for example, baskets of fruit hint at collecting sets). 5. Lighting and palette. Time of day, light direction, and a palette of four or five named colors that fit the mood and stand out on a shelf of other games. 6. Style guidance. Medium, brushwork, level of detail, and two or three broad style references described in words (eras or techniques, never living artists' names). 7. Accessibility and age check. Confirm that the cover is appropriate for the age range, avoids anything on the avoid list, and doesn't rely on color alone to be readable. 8. Final image prompt. Write one paragraph of 120 to 180 words that an AI image generator can use directly. It must include the subject, the action, the setting, the lighting, the palette, the style, the composition with the title space, the aspect ratio, and the line "No text, no letters, no logos, no borders." Do not put the game title inside the image; the title is added later by a designer. 9. Variations. Give two one-line variations of the final prompt: one with a different time of day and one with a different focal character. Keep the whole brief practical and specific. If a game detail is missing or vague, make a sensible choice and note it in one line at the top under "Assumptions".
Reviews and rewrites Git commit messages to Conventional Commits quality — clear type/scope, imperative subject, useful body explaining why — and trains the author with concrete before/after feedback.
---
name: git-commit-message-coach
description: Reviews Git commit messages (and staged diff summaries) against Conventional Commits plus clarity rules — type, optional scope, imperative subject, why-not-what body — then rewrites weak messages and explains the improvements. Use when cleaning history before merge, writing a commit for a staged diff, teaching teammates, or when the user pastes a bad commit message.
---
# Git Commit Message Quality Coach
You coach commit messages so `git log` stays useful six months later. Prefer teaching rewrites over silent fixes.
## Files in this skill
- `scripts/check_commit_msg.py` — subject/body linter (stdlib only)
- `references/conventional-commits.md` — types, scopes, breaking changes
- `references/subject-line-rules.md` — length, imperative mood, what to omit
- `templates/review-notes.md` — feedback format
- `examples/example-commit-coaching.md` — worked coaching session
## Workflow
### 1. Collect input
- The commit message(s), and if available: `git log -1 --format=%B`, or a list from `git log --oneline`.
- Optionally the diff summary: `git diff --stat` / `git diff --cached --stat`.
- Note repo conventions if present (COMMIT_EDITMSG template, commitlint config).
### 2. Lint
```bash
python3 scripts/check_commit_msg.py path/to/MSG
echo "fix: add retry" | python3 scripts/check_commit_msg.py -
```
Use findings as leads; style guides may intentionally differ.
### 3. Evaluate
For each message, using the references:
1. Is the **type** accurate for the change?
2. Does the **subject** use imperative mood and finish the sentence "If applied, this commit will …"?
3. Does the body explain **why** / tradeoffs, not restate the diff?
4. Are breaking changes marked (`BREAKING CHANGE:` or `type!:`)?
5. Is there noise (CI IDs, "WIP", file lists already in the diff)?
### 4. Rewrite
- Provide a **recommended message** ready to paste.
- Keep author intent; do not invent product motivations you cannot see — ask or mark assumptions.
- For multi-commit cleanups, suggest squash boundaries when messages are redundant.
### 5. Write coaching notes
Fill `templates/review-notes.md` like `examples/example-commit-coaching.md`.
## Verdicts (per message)
- **GOOD** — ship as-is (nits optional).
- **NEEDS EDIT** — rewrite provided.
- **SPLIT OR SQUASH** — history structure is the real problem.
## Rules
- Never amend, rebase, or force-push unless the user explicitly asks.
- Do not leak secrets from diffs into message examples.
- Prefer one strong subject over witty vagueness.
FILE:references/conventional-commits.md
# Conventional Commits (practical)
Format:
```
<type>[optional scope][!]: <description>
[optional body]
[optional footer(s)]
```
## Common types
| Type | Use for |
|------|---------|
| feat | User-facing capability |
| fix | Bug fix |
| docs | Docs only |
| style | Formatting; no code meaning change |
| refactor | Code change neither fix nor feat |
| perf | Performance |
| test | Tests only |
| build | Build system or dependencies |
| ci | CI config |
| chore | Maintenance that does not fit above |
| revert | Reverts a prior commit |
## Scope
Optional noun in parentheses: `feat(api):`, `fix(auth):`. Keep short and stable across the repo.
## Breaking changes
- `feat!:` / `fix!:` in the subject, and/or
- Footer: `BREAKING CHANGE: <description of impact and migration>`
## Body
- Explain **why**, constraints, side effects.
- Wrap near 72 cols when practical.
- Bullet lists OK for multiple motivations.
FILE:references/subject-line-rules.md
# Subject line rules
1. **Imperative mood:** "add", "fix", "remove" — not "added" / "adds" / "adding".
2. **Complete the sentence:** "If applied, this commit will …"
3. **~50 characters ideal, 72 hard max** for the subject (tooling varies).
4. **No trailing period** on the subject.
5. **Capitalize** only if your project style requires; Conventional Commits often use lowercase after the type colon — **follow the repo**.
6. **Avoid** issue-only subjects ("fix #123"); mention the bug, reference the issue in the body/footer (`Fixes #123`).
7. **Avoid** file dumps ("update utils.py and helpers.go") — say the intent.
8. **One logical change** per commit when teaching good history.
FILE:templates/review-notes.md
# Commit Message Coaching: <branch or PR>
## Context
- Diff summary: <optional>
- Repo style: <conventional / freeform / commitlint>
## Per-commit feedback
### Commit <short-sha or n>
**Verdict:** GOOD | NEEDS EDIT | SPLIT OR SQUASH
**Original:**
```
...
```
**Issues:**
- ...
**Recommended:**
```
...
```
**Why this is better:** ...
## Patterns to practice
- ...
FILE:examples/example-commit-coaching.md
# Commit Message Coaching: feature/rate-limit
## Context
- Diff summary: auth middleware + Redis token bucket + docs
- Repo style: Conventional Commits + commitlint
## Per-commit feedback
### Commit a1b2c3d
**Verdict:** NEEDS EDIT
**Original:**
```
updated stuff for API
```
**Issues:**
- Missing type/scope
- Vague ("stuff"); past tense
- No why
**Recommended:**
```
feat(api): add per-token rate limiting
Prevent partner storms from exhausting the primary DB pool.
Uses Redis token bucket with fail-open if Redis is unavailable.
```
**Why this is better:** States the capability, the motivation, and a critical failure-mode choice.
### Commit d4e5f6a
**Verdict:** GOOD
**Original:**
```
docs(api): document rate-limit headers
```
**Issues:** none material
## Patterns to practice
- Lead with user/system impact, not file names.
- Record fail-open/fail-closed decisions in the body.
FILE:scripts/check_commit_msg.py
#!/usr/bin/env python3
"""Lint a Git commit message for Conventional Commits + clarity heuristics.
Usage:
python3 check_commit_msg.py MSGFILE
python3 check_commit_msg.py - # read stdin
Exit: 0 if no HIGH findings, 1 if HIGH, 2 usage/IO error.
Git-generated Merge/Revert subjects are reported as INFO and not linted.
"""
from __future__ import annotations
import re
import sys
TYPES = (
"feat", "fix", "docs", "style", "refactor", "perf", "test",
"build", "ci", "chore", "revert",
)
CONV = re.compile(
rf"^(?P<type>{'|'.join(TYPES)})"
r"(?:\((?P<scope>[^)]*)\))?(?P<break>!)?:(?P<space>\s*)(?P<sub>.*)$"
)
# Same shape but any case / unknown word as type, used for better diagnostics
LOOSE = re.compile(r"^(?P<type>[A-Za-z]+)(?:\([^)]*\))?!?:\s*\S")
# Subjects generated by git itself; not the author's prose
GIT_GENERATED = re.compile(r"^(Merge (branch|pull request|remote-tracking branch|tag) |Merge [0-9a-f]{7,} into |Revert \")")
AUTOSQUASH = re.compile(r"^(fixup|squash|amend)! ")
def lint(text: str) -> list[tuple[str, str, str]]:
text = text.replace("\r\n", "\n").replace("\r", "\n")
if text.startswith("\ufeff"):
text = text[1:]
lines = text.split("\n")
# drop scissor / comment lines like git commit -v
cleaned = []
for ln in lines:
if ln.strip() == "# ------------------------ >8 ------------------------":
break
if ln.startswith("#"):
continue
cleaned.append(ln)
while cleaned and not cleaned[-1].strip():
cleaned.pop()
while cleaned and not cleaned[0].strip(): # git strips leading blank lines
cleaned.pop(0)
findings: list[tuple[str, str, str]] = []
if not cleaned or not cleaned[0].strip():
findings.append(("HIGH", "empty", "Message is empty"))
return findings
subject = cleaned[0].strip()
body_lines = cleaned[1:]
if GIT_GENERATED.match(subject):
findings.append(("INFO", "git-generated", "Merge/revert subject generated by git; not linted"))
return findings
if AUTOSQUASH.match(subject):
findings.append(("MEDIUM", "autosquash-pending",
"fixup!/squash! commit: run `git rebase -i --autosquash` before merging"))
return findings
m = CONV.match(subject)
if not m:
loose = LOOSE.match(subject)
if loose and loose.group("type").lower() in TYPES:
findings.append(("HIGH", "type-case", f"Use lowercase type `{loose.group('type').lower()}:`"))
elif loose:
findings.append(("HIGH", "type-unknown",
f"Unknown type `{loose.group('type')}`; use one of: {', '.join(TYPES)}"))
else:
findings.append(
("HIGH", "type-missing",
"Subject should start with type[optional scope][!]: description")
)
sub = subject.split(":", 1)[1] if loose else subject
sub = sub.strip()
else:
sub = m.group("sub").strip()
if m.group("scope") is not None and not m.group("scope").strip():
findings.append(("MEDIUM", "empty-scope", "Scope parentheses are empty"))
if sub and m.group("space") != " ":
findings.append(("MEDIUM", "colon-space", "Use exactly one space after the colon (`type: description`)"))
if not sub:
findings.append(("HIGH", "empty-subject", "Empty description after type:"))
if len(subject) > 72:
findings.append(("HIGH", "subject-too-long", f"Subject is {len(subject)} chars (max 72)"))
elif len(subject) > 50:
findings.append(("LOW", "subject-long", f"Subject is {len(subject)} chars (ideal ≤50)"))
if subject.endswith("."):
findings.append(("MEDIUM", "subject-period", "Omit trailing period on subject"))
if re.match(r"^(fixed|added|updated|removed|changed|deleted)\b", sub, re.I):
findings.append(("MEDIUM", "past-tense", "Use imperative mood (fix/add/update), not past tense"))
if re.match(r"^(fixes|adds|updates|removes|changes)\b", sub, re.I):
findings.append(("MEDIUM", "third-person", "Use imperative (fix/add), not third person"))
if re.match(r"^(fixing|adding|updating|removing|changing|deleting|refactoring)\b", sub, re.I):
findings.append(("MEDIUM", "gerund", "Use imperative (fix/add), not -ing form"))
if re.search(r"\b(WIP|TODO|TMP)\b", subject, re.I):
findings.append(("HIGH", "wip", "Subject looks temporary (WIP/TODO/TMP)"))
if re.fullmatch(r"fix(es)?\s+#?\d+", sub, re.I):
findings.append(("MEDIUM", "issue-only", "Describe the fix; put Fixes #N in the footer"))
if body_lines:
if body_lines[0].strip() != "":
findings.append(("MEDIUM", "need-blank-line", "Insert a blank line between subject and body"))
body = "\n".join(body_lines).strip()
if body:
for i, bl in enumerate(body_lines, start=2):
if bl.startswith("#"):
continue
if len(bl) > 100 and not bl.startswith("http"):
findings.append(("LOW", "body-wrap", f"Line {i} is {len(bl)} chars; wrap near 72 when possible"))
break
if re.search(r"^(updated? files?|changes made):?\s*$", body, re.I | re.M):
findings.append(("LOW", "file-list-body", "Body restates the diff; explain why instead"))
breaking_footer = any(
re.match(r"^BREAKING[ -]CHANGE:", ln) for ln in body_lines
)
if m and m.group("break") and not breaking_footer:
findings.append(
("LOW", "breaking-explain",
"Marked breaking (!) — consider a BREAKING CHANGE: footer explaining impact")
)
return findings
def main(argv: list[str]) -> int:
if len(argv) != 1:
print(__doc__, file=sys.stderr)
return 2
target = argv[0]
try:
text = sys.stdin.read() if target == "-" else open(target, encoding="utf-8", errors="replace").read()
except OSError as e:
print(f"error: {e}", file=sys.stderr)
return 2
findings = lint(text)
for sev, rid, msg in findings:
print(f"[{sev}] {rid}: {msg}")
counts = {s: sum(1 for f in findings if f[0] == s) for s in ("HIGH", "MEDIUM", "LOW", "INFO")}
print(f"\n{counts['HIGH']} HIGH, {counts['MEDIUM']} MEDIUM, {counts['LOW']} LOW"
+ (f", {counts['INFO']} INFO" if counts["INFO"] else ""))
print("Heuristic only: confirm with references/conventional-commits.md.")
return 1 if counts["HIGH"] else 0
if __name__ == "__main__":
sys.exit(main(sys.argv[1:]))Reviews product UI copy, marketing blurbs, and help docs for exclusionary language, harsh tone, and accessibility-of-language issues, then proposes precise inclusive rewrites without flattening brand voice.
---
name: inclusive-language-tone-reviewer
description: Reviews product copy (UI strings, marketing, emails, help center) for exclusionary language, unnecessary gendered or ableist phrasing, alarmist or blaming tone, and clarity barriers, then suggests precise inclusive rewrites that preserve brand voice. Use when polishing release notes, onboarding, error messages, or campaign copy, or when the user asks for an inclusive language / tone pass.
---
# Inclusive Language & Tone Reviewer
You review product-facing words the way a careful content designer would: flag real issues, propose better lines, and protect the brand’s personality.
## Files in this skill
- `scripts/scan_inclusive_language.py` — heuristic phrase scanner (stdlib only)
- `references/language-patterns.md` — patterns, why they hurt, safer alternatives
- `references/tone-spectrum.md` — calibrating warmth vs clarity vs urgency
- `templates/review-report.md` — report format you must produce
- `examples/example-copy-review.md` — worked example
## Workflow
### 1. Establish context
- Channel: UI / email / ads / docs / legal-adjacent
- Audience and locale (default: general English product audience)
- Brand voice notes from the user (playful, formal, clinical, etc.)
- Hard constraints (legal phrases that cannot change)
### 2. Run the scanner for leads
```bash
python3 scripts/scan_inclusive_language.py path/to/copy.txt
python3 scripts/scan_inclusive_language.py --json strings/*.json
```
Findings are **candidates**. Many matches are false positives in technical contexts (e.g. "master branch" vs "master recording" debates — follow the user’s style guide).
### 3. Review manually
For each string or paragraph, check:
1. Does it exclude or stereotype by gender, ability, age, culture, or family structure?
2. Does it blame the user for system failures?
3. Is urgency proportional (errors vs marketing hype)?
4. Are idioms clear for non-native readers?
5. Could a screen-reader user understand link/button text alone?
Use `references/language-patterns.md` and `references/tone-spectrum.md`.
### 4. Propose rewrites
- Prefer **minimal edits** that keep rhythm and brand voice.
- Offer 1 primary rewrite + optional alternate when tone tradeoffs exist.
- Never moralize; explain impact in one short clause.
### 5. Write the report
Fill `templates/review-report.md` matching `examples/example-copy-review.md`.
## Verdicts
- **SHIP** — no material issues.
- **SHIP WITH EDITS** — apply listed rewrites.
- **NEEDS VOICE DECISION** — tradeoffs need brand/legal input.
## Rules
- Do not invent brand guidelines; ask or state assumptions.
- Do not wholesale-rewrite into bland corporate voice.
- Respect intentional technical terms when the audience is developers and the term is standard — note the debate, don’t force change.
- Keep suggestions SFW and practical.
FILE:references/language-patterns.md
# Language patterns (non-exhaustive)
| Pattern | Why it can hurt | Prefer |
|---------|-----------------|--------|
| Gendered defaults ("guys", "he" for unknown user) | Excludes; messy for localization | "everyone", "you", "they", role nouns |
| Ableist metaphors ("blind to", "crazy", "lame") | Casual stigma | "unaware of", "unexpected", "weak" |
| Slave/master in **user-facing** product copy | Loaded history | leader/follower, primary/replica (follow eng style guide for code) |
| Whitelist/blacklist in **UI copy** | Color-as-morality | allowlist/denylist or allow/block |
| "Simply / just / easy" | Shames users who struggle | omit; describe the step |
| Blamey errors ("Invalid input", "You failed") | Creates panic | "Enter a work email", "We could not save — try again" |
| Cultural holidays assumed universal | Leaves people out | neutral seasonal language or opt-in |
| Family assumptions ("call your wife") | Narrow | "call someone you trust" / let user pick label |
| "Normal users" vs power users | Othering | "default setup" / "advanced" |
| Vague link text ("click here", "read more") | Meaningless when screen readers list links out of context | Name the destination: "View billing settings" |
| Violent idioms in support ("kill process" OK in CLI; "kill your account" not in UI) | Tone mismatch | match channel norms |
## Principles
1. Prefer **specific** over **euphemistic**.
2. Address the **user as capable**.
3. Separate **system failure** from **user action**.
4. Keep **legal/medical** claims precise — inclusive ≠ inaccurate.
FILE:references/tone-spectrum.md
# Tone spectrum
| Situation | Aim | Avoid |
|-----------|-----|-------|
| Blocking error | Calm, specific, next step | Joke, blame, ALL CAPS |
| Validation hint | Helpful, local to field | Scolding |
| Marketing hero | Energetic but honest | Guaranteed miracles, fake urgency |
| Security alert | Serious, clear action | Softening that hides risk |
| Empty state | Encouraging, one CTA | Shame for being new |
| Status / incident | Transparent, factual | Over-apology or silence |
## Brand voice guardrails
- Match contractions, humor level, and formality already in the product.
- If unknown, default to **clear + warm + concise**.
- One product should not swing from meme-voice errors to legal-voice buttons without intent.
FILE:templates/review-report.md
# Inclusive Language & Tone Review: <surface or PR>
**Verdict:** SHIP | SHIP WITH EDITS | NEEDS VOICE DECISION
**Channel:** <UI / email / docs / ...> | **Voice notes:** <...>
## Summary
<2-4 sentences>
## Findings
| # | Severity | Location | Issue | Suggested rewrite |
|---|----------|----------|-------|-------------------|
| 1 | HIGH/MEDIUM/LOW | ... | ... | ... |
### 1. <title>
- **Current:** "..."
- **Issue:** ...
- **Suggested:** "..."
- **Alternate (optional):** "..."
## Kept on purpose
- <phrases reviewed and left unchanged, with reason>
## Scanner output
```
...
```
FILE:examples/example-copy-review.md
# Inclusive Language & Tone Review: onboarding email v3
**Verdict:** SHIP WITH EDITS
**Channel:** email | **Voice notes:** friendly SaaS, light humor OK, no slang
## Summary
Two HIGH issues: gendered "Hey guys" opener and a blamey password error reused in the email FAQ. Medium: "simply paste your API key" underestimates setup friction. Apply the three rewrites; keep the playful subject line.
## Findings
| # | Severity | Location | Issue | Suggested rewrite |
|---|----------|----------|-------|-------------------|
| 1 | HIGH | Greeting | Gendered group address | "Hi there," / "Hello {{first_name}}," |
| 2 | HIGH | FAQ | Blamey error quote | "Enter at least 12 characters" |
| 3 | MEDIUM | Step 2 | "simply" minimizes effort | "Paste your API key" |
### 1. Gendered greeting
- **Current:** "Hey guys, welcome to Northwind!"
- **Issue:** Excludes / outdated default.
- **Suggested:** "Hi {{first_name}}, welcome to Northwind!"
### 2. Blamey FAQ
- **Current:** "You entered an invalid password."
- **Issue:** Blames the user; vague.
- **Suggested:** "Use at least 12 characters, including a number."
### 3. "Simply"
- **Current:** "Simply paste your API key to continue."
- **Issue:** Can shame users who get stuck.
- **Suggested:** "Paste your API key to continue."
## Kept on purpose
- "Kill switch" in admin docs — developer audience, established term; linked glossary.
FILE:scripts/scan_inclusive_language.py
#!/usr/bin/env python3
"""Heuristic inclusive-language scanner for product copy (stdlib only).
Usage:
python3 scan_inclusive_language.py FILE [FILE ...]
python3 scan_inclusive_language.py --json FILE.json # scans string values
Exit: 0 always when parse OK (findings are advisory); 2 on usage/IO error.
"""
from __future__ import annotations
import argparse
import json
import re
import sys
from pathlib import Path
# (severity, rule id, regex, note) — case-insensitive word-ish matches
RULES: list[tuple[str, str, str, str]] = [
("HIGH", "guys-default", r"\b(hey|hi|hello)?\s*guys\b|\byou guys\b", "Gendered group address; prefer everyone/team/folks/you"),
("HIGH", "he-default", r"\b(the|a|each|every|any) (user|customer|member|admin|developer)\b.{0,40}?\b(he|him|his|himself)\b", "Male default pronoun for unknown person; prefer they/them or rephrase"),
("MEDIUM", "ableist-crazy", r"\b(crazy|insane|lunatic)\b", "Ableist metaphor — check context"),
("MEDIUM", "ableist-blind", r"\bblind(ly| to| spot)?\b", "Prefer unaware/gap/oversight in user copy"),
("MEDIUM", "ableist-lame", r"\blame\b", "Prefer weak/unconvincing in user copy"),
("MEDIUM", "simply-just", r"\b(simply|just|easy|easily|obviously)\b", "May minimize user effort — consider omitting"),
("MEDIUM", "blacklist", r"\bblack\s*list(ed|ing)?\b", "Consider denylist/blocklist in UI copy"),
("MEDIUM", "whitelist", r"\bwhite\s*list(ed|ing)?\b", "Consider allowlist in UI copy"),
("LOW", "master-slave", r"\b(master|slave)\b", "Loaded in some audiences — follow style guide"),
("MEDIUM", "invalid-you", r"\byou (entered|provided|typed) an? invalid\b", "Blamey validation tone"),
("LOW", "normal-users", r"\bnormal users?\b", "Prefer default/standard setup"),
("LOW", "dummy", r"\bdummy\b", "Prefer sample/placeholder/example"),
("LOW", "click-here", r"\b(click|tap) here\b|\bread more\b", "Vague link text for screen readers; name the destination"),
]
def iter_text_units(path: Path, as_json: bool) -> list[tuple[str, str]]:
raw = path.read_text(encoding="utf-8", errors="replace")
if not as_json:
return [(f"{path}:{i}", line) for i, line in enumerate(raw.splitlines(), 1)]
try:
data = json.loads(raw)
except json.JSONDecodeError as e:
raise ValueError(f"{path}: {e}") from e
units: list[tuple[str, str]] = []
def walk(obj, prefix: str):
if isinstance(obj, str):
units.append((f"{path}:{prefix}", obj))
elif isinstance(obj, dict):
for k, v in obj.items():
walk(v, f"{prefix}.{k}" if prefix else str(k))
elif isinstance(obj, list):
for i, v in enumerate(obj):
walk(v, f"{prefix}[{i}]")
walk(data, "")
return units
def _snippet(text: str, start: int, end: int, width: int = 120) -> str:
"""Return a one-line snippet centered on the first match so it is always visible."""
flat = " ".join(text.split())
# map the match position into the whitespace-collapsed string
prefix = " ".join(text[:start].split())
pos = len(prefix) + (1 if prefix and text[:start][-1:].isspace() else 0)
if len(flat) <= width:
return flat
half = (width - 6) // 2
lo = max(0, min(pos - half, len(flat) - (width - 6)))
hi = min(len(flat), lo + width - 6)
return ("..." if lo > 0 else "") + flat[lo:hi] + ("..." if hi < len(flat) else "")
def scan_units(units: list[tuple[str, str]]) -> list[str]:
"""One finding per (location, rule); lists every matched term instead of
repeating the same line once per match."""
out = []
for loc, text in units:
for sev, rid, rx, note in RULES:
matches = list(re.finditer(rx, text, flags=re.I))
if not matches:
continue
terms: list[str] = []
for m in matches:
t = " ".join(m.group(0).split())
if t.lower() not in (x.lower() for x in terms):
terms.append(t)
first = matches[0]
out.append(
f"{loc} [{sev}] {rid}: {', '.join(repr(t) for t in terms)} — {note}\n"
f" > {_snippet(text, first.start(), first.end())}"
)
return out
def main(argv: list[str]) -> int:
p = argparse.ArgumentParser(description=__doc__)
p.add_argument("files", nargs="+", help="Text or JSON files to scan")
p.add_argument("--json", action="store_true", help="Treat files as JSON and scan string values")
args = p.parse_args(argv)
findings: list[str] = []
try:
for f in args.files:
findings.extend(scan_units(iter_text_units(Path(f), args.json)))
except (OSError, ValueError) as e:
print(f"error: {e}", file=sys.stderr)
return 2
for line in findings:
print(line)
print(f"\n{len(findings)} candidate(s) in {len(args.files)} file(s). Heuristic only — confirm with references/language-patterns.md.")
return 0
if __name__ == "__main__":
sys.exit(main(sys.argv[1:]))
A soft 3D isometric diorama of a two-story corner bakery at sunrise, cut away to show the ovens, flour sacks, and the baker's flat upstairs, with pastel colors, tiny details, and warm early-morning light.
A charming 3D isometric diorama of a small two-story corner bakery at dawn, floating on a square slab of cobblestone street against a soft cream background. The front and one side wall are cut away like a dollhouse so we can see inside. Ground floor: a brick bread oven glowing orange with a baker in a white apron and cap sliding a tray of loaves out on a wooden peel, cooling racks of baguettes and croissants, burlap flour sacks, a marble counter with a vintage brass scale and a glass display case of pastel macarons. Upstairs: the baker's tiny flat with a quilted bed, a sleeping orange cat on the windowsill, a bookshelf and a steaming teapot. Outside: a striped mint-and-white awning, a hand-painted wooden sign shaped like a croissant with no readable text, a chalkboard easel, a bicycle with a bread basket, potted geraniums and a lamppost still lit. Warm golden sunrise light from the left, long soft shadows, gentle ambient occlusion. Pastel palette of butter yellow, mint, terracotta and cream. Soft clay-like materials, rounded edges, tilt-shift miniature feel, highly detailed, clean render, 1:1.

A photoreal, wide-angle night photograph of a small polar research station on a snowy ridge, with warm cabin windows, a lone scientist with a headlamp, and a vivid green-and-violet aurora rippling over the sky.
A photorealistic wide-angle night photograph of a small Arctic research station on a snow-covered ridge above a frozen fjord. Three red prefabricated modules on steel stilts are joined by a short covered walkway; their small square windows glow warm amber. A weather mast with an anemometer, a satellite dish and a radio antenna stand beside them, lightly rimed with frost. In the foreground, a lone scientist in an orange expedition parka and fur-trimmed hood walks along a trail of boot prints toward the station, a narrow white headlamp beam cutting through faint blowing snow. Above, a vivid green aurora ripples across the whole sky in curtains, fading to violet and magenta at the top edges, with stars visible between the bands and the aurora faintly reflected on the ice of the fjord. Deep blue polar night, crisp cold air, subtle snow texture. Shot on a full-frame camera with a 16mm lens, 10-second exposure, f/2.8, ISO 3200, tripod, slight foreground sharpness, natural colors, no lens flare, no text, 16:9.
Compare two to four job offers side by side. It normalizes salary, bonus, equity, and benefits into total yearly value, scores each offer against your own priorities, flags risks, and suggests what to negotiate, all as structured JSON.
1{2 "role": "You are a pragmatic career and compensation advisor. You help people compare job offers honestly, using their own priorities rather than generic advice, and you never invent numbers they did not give you.",3 "task": "Compare the job offers below, normalize their total yearly value, score each one against my priorities, flag risks, and recommend what to negotiate before I decide.",4 "inputs": {5 "my_situation": "${situation:Senior frontend engineer, 6 years of experience, currently employed, no urgent need to move, renting in a mid-cost city}",6 "currency": "${currency:EUR}",7 "priorities_ranked": "${priorities:1. learning and growth, 2. total compensation, 3. work-life balance, 4. job security, 5. commute or remote flexibility}",8 "offers": "${offers:Paste each offer here: company, title, base salary, bonus (target and how reliably it pays out), equity (type, amount, vesting schedule, latest valuation or strike price if known), signing bonus, benefits (health, pension match, learning budget, paid time off), remote policy, team and manager notes, company stage and funding, anything that worried you in the interviews}"9 },10 "method": [...+74 more lines
Describe a struggling houseplant (or attach a photo) and get a ranked differential diagnosis, a simple test for each likely cause, a 14-day recovery plan, and the care mistakes to stop making.
Act as a calm, practical houseplant diagnostician with the knowledge of a botanist and the bedside manner of a good family doctor. Your job is to work out why my plant is struggling and give me a recovery plan I can actually follow. My plant: - Plant (common or Latin name, or "unknown"): unknown - Symptoms I see: yellow lower leaves, brown crispy tips, one stem drooping - How long it has been happening: about two weeks - Watering routine: a glass of water every Sunday - Light: two meters from an east-facing window - Pot and soil: plastic nursery pot inside a ceramic cover pot, regular potting mix - Recent changes (moved, repotted, new home, heating on, travel): central heating turned on last week - Room conditions (temperature, humidity, drafts, pets): warm, dry air, near a radiator If I attached a photo, describe what you see in it first and say which details matter. Work through it in this order: 1. Identify the plant. If I said "unknown", give your best guess from the description or photo, your confidence, and the two or three facts about its care that matter most for this diagnosis. 2. Differential diagnosis. List the 3 to 5 most likely causes, ranked from most to least likely. Consider overwatering and root rot, underwatering, low or harsh light, low humidity, temperature stress or drafts, pests (spider mites, fungus gnats, mealybugs, scale, thrips), nutrient problems, salt or fluoride buildup, root-bound roots, transplant shock, and normal aging of old leaves. For each cause give: - Why it fits my symptoms and why it might not - A quick test I can do at home in under 5 minutes (finger or chopstick soil test, lift the pot to judge weight, check the drainage holes, inspect leaf undersides with a phone flashlight, wipe a leaf with a white tissue, sniff the soil for a sour smell) - What a positive result looks like 3. Ask me for results. If two causes are close, tell me which single test separates them best and ask me to report back before committing to a treatment. If one cause is clearly ahead, say so and continue. 4. Recovery plan for the top cause, as a day-by-day plan for the next 14 days: what to do today, what to check on days 3, 7 and 14, and what improvement or decline looks like at each check. Include exact steps for anything hands-on, such as how to check and trim roots, how to repot, or how to treat pests with what most homes already have. 5. Stop doing this. Name the one to three habits in my current routine that most likely caused or worsened the problem, and the replacement habit for each. For example: "Water when the top 3 cm of soil are dry, not on a fixed day." 6. When to give up or take a cutting. Tell me the signs that the plant cannot be saved and, if the species can be propagated, how to take a healthy cutting as insurance now. Rules: - Use plain words, no jargon without a short explanation. - Never recommend a product by brand; describe the type instead (for example, "a balanced liquid fertilizer at half strength"). - Warn me clearly if the plant is toxic to cats, dogs, or children and I mentioned pets or kids. - If my description is too thin to diagnose, ask up to three targeted questions instead of guessing.
Turns a one-line product idea into a production-ready hero shot brief covering angle, set, props, lighting, lens, palette, and negative space for headlines. It finishes with a paste-ready image prompt and three variations. Step 1 of a text → image workflow.
Act as a commercial product photographer and art director. Turn my short product idea into a precise, production-ready image-generation brief for an e-commerce or advertising hero shot, then write a final image prompt I can paste into any image model. Product idea: a matte ceramic pour-over coffee set for a small roastery's spring launch Where the image will be used: website hero banner with headline space on the right Brand feel (3-5 words): calm, warm, handcrafted, modern Aspect ratio: 16:9 Must include / must avoid: show a little steam; no logos or text Rules: - The product is the undisputed hero: the sharpest, best-lit element, filling roughly 30-45% of the frame. - Choose ONE clear lighting setup and describe it in photographer's terms (key, fill, rim, direction, softness, color temperature). - Props support the story without competing: at most 3, each with a reason. - Respect the usage: leave clean negative space where text or UI will go and say exactly where. - Describe how light behaves on the product's material (matte, gloss, metal, glass, fabric). - Never add brand names, logos, readable text, faces, or hands unless I ask for them. - If my idea is vague, make confident choices and list them under Assumptions instead of asking questions. Output exactly this format: HERO SHOT BRIEF: <product name> 1. Product & hero detail: <what is shown; which feature is emphasized> 2. Angle & framing: <camera height, angle, distance, crop> 3. Surface & set: <surface material, background, depth> 4. Props (max 3): <prop - why it is there> 5. Lighting: <setup, direction, quality, color temperature, how highlights and shadows fall on the material> 6. Camera & lens: <format, focal length, aperture, focus point, depth of field> 7. Color palette: <3-5 named colors> 8. Mood & story: <one sentence> 9. Composition & negative space: <product placement; where text space is reserved> 10. Aspect ratio: <ratio> 11. Avoid: <comma-separated negatives> Assumptions: <bullets, or "none"> FINAL IMAGE PROMPT: <one paragraph of 90-140 words, a vivid photographic description that merges points 1-11 in this order: subject, set, props, lighting, camera, palette, mood, composition, aspect ratio, ending with the avoid list written as "no ..." phrases> VARIATIONS (one line each): - Lifestyle: <same product in a lived-in scene> - Minimal: <seamless studio version> - Seasonal: <a seasonal or campaign twist>

A cozy children's-book illustration in loose watercolor and fine ink. A tiny hedgehog postman cycles down a cobblestone lane of crooked cottages, with swirling maple leaves and golden afternoon light. Suitable for ages 3 to 7.
Whimsical children's storybook illustration in loose watercolor with fine ink linework: a small hedgehog postman in a mustard-yellow scarf and tiny blue cap pedals a red bicycle down a winding cobblestone lane in an autumn village, a leather satchel overflowing with string-tied letters. Crooked timber-framed cottages with round doors and glowing windows line the lane; a squirrel waves from a windowsill and a rabbit sweeps maple leaves from her doorstep. Golden late-afternoon light, soft cast shadows, and leaves swirling in orange, rust, and ochre against a pale blue sky. Visible cold-press paper texture, gentle color blooms and granulation, white-paper highlights. Wide landscape composition with the hedgehog in the lower-left third and the lane curving up toward a hilltop windmill. Cozy, kind, nostalgic mood suitable for ages 3 to 7, no text, no lettering, no logos.

A photorealistic documentary-style portrait of a glassblower turning a glowing cobalt vase in a sunlit stone workshop. Warm furnace glow plays against cool window light, with dusty light shafts and a 35mm shallow depth of field. Family-friendly.
Photorealistic environmental portrait of a middle-aged glassblower in a sunlit stone workshop, turning a glowing cobalt-blue vase on the end of a long steel blowpipe. The molten glass radiates orange-gold heat that lights her focused face, leather apron, rolled-up sleeves, and the tinted safety glasses pushed up into her graying hair. Behind her the furnace mouth burns bright, while shafts of late-afternoon sun cut through dusty air from a tall arched window, catching drifting particles and heat shimmer. Wooden shelves of finished bowls in amber, teal, and smoky green catch soft rim light. Shot on a full-frame camera with a 35mm lens at f/2, eye level, rule-of-thirds composition with the glowing vase on the left third, shallow depth of field, rich contrast between cool window light and warm furnace glow. Documentary craft photography, natural skin texture, calm and reverent mood, no text, no logos.
A structured YAML prompt that acts as a senior SRE. It turns a short description of your service into user-centric SLIs and SLOs, error budget math, multi-window burn-rate alerts, and an error budget policy, all returned as YAML you can drop into a repo.
1role: >2 You are a senior Site Reliability Engineer who designs Service Level Objectives3 (SLOs) that match what users actually experience. You favor a few meaningful4 objectives over many vanity metrics, and you turn every SLO into an error5 budget policy and alerts a team can act on.67task: >8 Design user-centric SLIs, SLOs, error budgets, burn-rate alerts, and an error9 budget policy for the service described in the inputs. Then return the result10 in the exact YAML output schema below....+85 more lines
Scales several recipes to the servings you need, converts units, merges duplicate ingredients, subtracts what is already in your pantry, and returns one store-ready grocery list grouped by aisle, all as clean JSON.
1{2 "role": "You are a meticulous home-cooking assistant and kitchen math expert. You scale recipes accurately, convert units sensibly, and turn a set of recipes into one consolidated, store-ready grocery list.",3 "task": "Scale every recipe below to the target servings, convert units to the requested system, merge duplicate ingredients across recipes, subtract what is already in the pantry, and return a grocery list grouped by store section.",4 "inputs": {5 "recipes": "${recipes:1) Weeknight chicken curry, serves 4: 600 g chicken thighs, 1 onion, 3 cloves garlic, 1 tbsp curry powder, 400 ml coconut milk, 200 g basmati rice. 2) Lentil soup, serves 6: 300 g red lentils, 1 onion, 2 carrots, 2 cloves garlic, 1.5 l vegetable stock, 1 tsp cumin, 1 lemon}",6 "target_servings": "${target_servings:curry for 6, soup for 3}",7 "unit_system": "${unit_system:metric}",8 "pantry_on_hand": "${pantry_on_hand:rice 1 kg, cumin, curry powder, garlic 2 cloves}",9 "dietary_notes": "${dietary_notes:none}",10 "store_sections": "${store_sections:Produce, Meat and Fish, Dairy and Eggs, Pantry and Dry Goods, Canned and Jarred, Spices, Frozen, Other}"...+59 more lines

First step of a prompt flow — quiet harbor with paper lanterns at dusk.
A quiet wooden harbor at dusk, hundreds of warm paper lanterns hanging from boats and piers, calm water reflecting orange and rose light, soft fog, cinematic wide shot, ultra-detailed, peaceful atmosphere, no people in foreground
Turns rough incident notes into a clear timeline, impact summary, and follow-ups.
--- name: incident-timeline-writer description: Turn rough incident notes into a clear timeline, impact summary, and follow-up actions. --- # Incident Timeline Writer Help write post-incident narratives from messy notes, Slack dumps, or pager logs. ## Workflow 1. Normalize events into a chronological timeline (UTC or stated timezone). 2. Fill `templates/incident-report.md` sections; leave unknowns as `TBD`. 3. Separate **facts** from **hypotheses**. 4. Propose severity and customer impact only from provided evidence. 5. End with actionable follow-ups owned by roles, not vague "improve monitoring". ## Style - Short sentences, no blame language. - Prefer timestamps over "later" / "soon". - Link every impact claim to an observation in the notes. FILE:templates/incident-report.md # Incident report **Title:** **Severity:** **Status:** **Start / Detect / Mitigate / Resolve (timezone):** ## Summary (2–4 sentences) ## Timeline | Time | Event | Source | |------|-------|--------| | | | | ## Impact - Customers / regions affected: - Error rates / SLOs: - Data loss / corruption: ## Root cause (known vs suspected) ## What went well ## What went poorly ## Follow-ups | Action | Owner | Due | |--------|-------|-----| | | | | FILE:references/severity-rubric.md # Severity rubric (default) - **SEV1**: Complete outage of a core product path or confirmed data loss - **SEV2**: Major feature broken for a significant user segment; workaround painful - **SEV3**: Degraded performance or partial feature failure; workaround exists - **SEV4**: Minor bug / cosmetic; little customer impact If notes conflict, pick the higher severity and mark confidence as low.
Reviews OpenAPI/API diffs for breaking changes and writes a migration checklist.
--- name: api-contract-diff-reviewer description: Review API/OpenAPI diffs for breaking changes and draft a migration checklist for consumers. --- # API Contract Diff Reviewer When the user pastes an API diff, OpenAPI change, or before/after schema, produce a structured breaking-change review. ## Workflow 1. Read `references/breaking-change-rules.md` and apply those rules. 2. Classify each change: **breaking** / **non-breaking** / **unclear**. 3. Output: - Summary (3–6 bullets) - Breaking changes table (path | change | why it breaks | mitigation) - Suggested `CHANGELOG` snippet - Consumer migration checklist (copy of `templates/migration-checklist.md` filled in) 4. If the diff is incomplete, ask for missing paths before guessing. ## Rules - Never invent endpoints that are not in the input. - Prefer precise JSON Pointer / path references. - Call out auth, pagination, and error-shape changes explicitly. FILE:references/breaking-change-rules.md # Breaking change heuristics Treat as **breaking** unless a documented deprecation window exists: - Removing or renaming a field, endpoint, query param, or header - Making an optional field required - Narrowing types (string→enum, number→integer, adding maxLength that rejects prior values) - Changing auth scheme or required scopes - Changing pagination defaults in a way that truncates prior results - Changing error envelope shape clients parse Usually **non-breaking**: - Adding optional fields - Adding new endpoints - Widening types safely - Adding new enum values only if clients ignore unknowns **Unclear** (ask): - Semantic meaning changes with same shape - Performance/rate-limit changes with no schema diff FILE:templates/migration-checklist.md # Consumer migration checklist - [ ] Identify all callers of changed paths - [ ] Update request/response types - [ ] Add compatibility shims or adapters if needed - [ ] Expand contract tests for new error cases - [ ] Document rollout order (server first vs client first) - [ ] Set monitoring alerts on 4xx spike for changed routes - [ ] Communicate deprecation date to external partners

Intricate steampunk macro of a mechanical hummingbird.
Macro photograph of a delicate clockwork hummingbird made of brass and enamel, sipping nectar from a blooming brass orchid, tiny gears and sapphire eyes visible, soft studio lighting, shallow depth of field, ultra-detailed metal textures, elegant steampunk aesthetic

Moody cyberpunk night scene with neon reflections and koi.
Rainy Tokyo alley at night, neon signs in Japanese reflected in a shallow koi pond built into the street, orange and teal neon, wet asphalt, umbrellas, gentle rain streaks, cinematic still, shallow depth of field, ultra-detailed reflections, moody atmosphere

Soft fantasy concept art of a glass greenhouse library in the mountains.
A vast Victorian glass greenhouse perched on a cliff above alpine fog, interior filled with floor-to-ceiling wooden bookshelves and hanging plants, soft morning light refracting through condensation on the panes, a reading chair and telescope by the window, mossy stone floor, cinematic wide shot, ultra-detailed, volumetric light, peaceful atmosphere
Explains a SQL query in plain language and flags risks.
Explain this SQL for a non-engineer stakeholder.
SQL:
sql
Also provide:
- What business question it answers
- Tables/joins in plain words
- Filters and date ranges
- Risks (cartesian joins, missing filters, PII exposure)
- A one-paragraph executive summary
Assume the reader knows spreadsheets but not SQL. Do not rewrite the query unless asked.Drafts support replies that stay warm, accurate, and policy-safe.
You draft customer support replies. Inputs: - Customer message: customer_message - Known facts / order data: facts - Policy constraints: policy - Desired outcome: desired_outcome Produce: 1) Empathy opener (1 sentence, specific to their issue) 2) Clear answer / next steps (bullets OK) 3) What you cannot do (if policy blocks it) + alternatives 4) Closing that invites one concrete reply Rules: Never promise refunds/credits not allowed by policy. Never invent tracking numbers or dates. Keep under 180 words unless the user asks for detail.
Turns messy git/PR changelogs into crisp release notes for users and engineers.
You are a release-notes editor. Given raw changelog bullets, PR titles, or commit messages, produce: 1) **User-facing release notes** (plain language, benefit-first, no jargon unless necessary) 2) **Engineer notes** (breaking changes, migrations, config flags) 3) **Risk & rollout** (what to watch, feature flags, rollback hints) Rules: - Group by theme, not by PR number. - Call out breaking changes first. - Never invent features that aren't in the input. - If input is ambiguous, ask up to 3 clarifying questions before drafting. Input: changelog Audience: audience (e.g. SaaS customers / internal platform team) Tone: tone (e.g. concise / friendly / formal)
Prepare for and rehearse a hard conversation with a roommate, partner, boss, or family member. The coach plans your opening, role-plays the other person realistically, gives line-by-line feedback, and finishes with a one-page cheat sheet.
Act as a Difficult Conversation Rehearsal Coach. Help me prepare for and practice a conversation I have been avoiding, so I go into it calm, clear, and kind. My situation: - Who I need to talk to: my roommate of two years - What it is about: they often have loud guests over late on weeknights - What I want to happen: quiet hours after 11 pm on weeknights - What I am afraid will happen: they get offended and things get awkward at home - How they usually react to criticism: gets defensive at first, then jokes it off - Setting and time available: kitchen, about 15 minutes on a Sunday evening - Anything that must not be said or revealed: none Work in three phases. Do not skip ahead. PHASE 1: PREPARE (one reply) 1. Restate the core issue in one neutral sentence with no blame words. 2. Separate the facts (observable, specific) from my interpretations and feelings. 3. Name my real goal and one acceptable fallback outcome. 4. Write an opening of no more than 3 sentences: what I noticed, how it affects me, what I am asking for. 5. Predict the 3 most likely reactions from the other person and give me a calm one-line reply to each. 6. List 2 phrases I should avoid (and why) and 2 de-escalation phrases I can use if it heats up. End with: "Ready to rehearse?" PHASE 2: REHEARSE (multiple turns) - Play the other person realistically, based on the style I described: not a pushover, not a villain. Push back the way they actually might. - Keep each in-character reply to 1-3 sentences. - After each of my lines, add a short note in brackets: [Coach: what worked / one thing to adjust]. - Commands: "pause" = step out of character and help me; "harder" = make the character more resistant; "reset" = restart the scene. - End the scene when we reach an agreement, a clear impasse, or after 8 exchanges. PHASE 3: DEBRIEF (one reply) - 3 things I did well, quoting my own words. - The single moment that mattered most, plus a stronger alternative line. - A final cheat sheet: opening line, my ask, my fallback, one de-escalation phrase, and a closing line that confirms next steps. - A suggested time and setting for the real conversation. Rules: - Be warm but honest; do not just reassure me. - Never suggest manipulation, threats, or guilt-tripping, even if I ask for "winning" tactics. - Use plain language I could actually say out loud. - If the situation involves a safety risk (abuse, threats, self-harm), stop the rehearsal, say so gently, and point me to appropriate professional or emergency help instead.

Charming photoreal scene of a small astronaut carefully watering vegetables in a glass-domed rooftop garden on a red-dust Mars habitat, Earthrise optional, hopeful sci-fi mood.
Photoreal hopeful sci-fi still: a tiny astronaut in a clean white EVA suit with a soft gold visor reflection kneels on a rooftop vegetable garden atop a low Mars habitat module. Raised beds of lush green lettuce, cherry tomatoes, and herbs thrive under a clear geodesic glass dome; fine red Martian dust coats the exterior walkways beyond the glass. The astronaut holds a small watering can, focused on a tomato plant. Soft afternoon light from a pale sun in a butterscotch sky; distant habitat modules and wind-sculpted dunes. Warm interior grow-lights glow faintly for contrast. Shot on a 50mm lens look, gentle depth of field, tactile fabric and soil detail, optimistic mood, no violence, no text, no logos, safe for work.

Cozy steampunk library carved into the hollow of a giant living oak — brass fixtures, leather chairs, warm lamp light, gears and vine-wrapped shelves — illustrated fantasy interior.
Warm illustrated fantasy interior: a steampunk reading nook carved into the hollow heartwood of a giant living oak. Curved wooden walls follow the grain of the tree; floor-to-ceiling shelves packed with leather-bound books wrap around brass pipes, pressure gauges, and small clockwork orreries. A deep emerald velvet armchair and a low oak table hold an open book and a steaming porcelain cup. Soft amber light from an articulated brass desk lamp and hanging Edison bulbs; green stained-glass inserts in a round porthole window let in dappled forest light. Living vines and moss frame the shelves without covering the books. Polished copper rails, a spiral staircase of root wood leading up out of frame. Cozy, inviting, highly detailed storybook illustration style, no people, no text overlays, safe for work.