linsy 28b78dd7bf
feat: add inherit-legacy-style — prevent AI code style drift in legac… (#2098)
* feat: add inherit-legacy-style — prevent AI code style drift in legacy projects

- 4-dimension meta-architecture scan (File Anatomy, State & Control Flow, Infrastructure, Error Handling)
- Scale-adaptive (small=full read, large=smart sampling)
- Signal-threshold noise reduction with one-at-a-time grilling protocol
- Generates .ai-style-rules.md with persistent CLAUDE.md hook
- Language- and framework-agnostic

* fix: add AskUserQuestion to allowed-tools, add When to Use/How It Works/Examples sections per bot review

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Co-authored-by: wulinzai <linsywu@gmail.com>
2026-06-07 13:26:40 +08:00

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name, description, origin, allowed-tools
name description origin allowed-tools
inherit-legacy-style Legacy-project style inheritance skill. Use when the user types /inherit-legacy-style, or when onboarding an AI coding agent onto a hand-written legacy project and you need to prevent "style drift" (the model imposing its pretrained mainstream idioms onto the project). Language- and framework-agnostic — it aligns meta-architecture only, not syntax. Once run, it becomes a behavioral constraint on all subsequent coding tasks. Do NOT use for pure research or one-off questions unrelated to code-style alignment. community Read, Glob, Grep, Bash, Edit, Write, AskUserQuestion

Inherit Legacy Style

Prevents AI code style drift in legacy projects by scanning the codebase for implicit conventions across 4 meta-architecture dimensions, resolving conflicts with the user one at a time, and crystallizing the consensus into an enforceable .ai-style-rules.md. Fully language- and framework-agnostic.

When to Activate

  • User types /inherit-legacy-style
  • User mentions onboarding AI onto a hand-written legacy project
  • User is worried about AI-generated code "drifting" from existing project conventions
  • User wants to extract and codify their project's implicit coding rules

When to Use

Use this skill when you need to preserve legacy project style and prevent AI-generated style drift. See When to Activate above for trigger conditions.

Prerequisites

  • Git (recommended; non-Git projects fall back to file timestamps for incremental mode)
  • Read/Write access to the project root (generates .ai-style-rules.md and optionally CLAUDE.md)

Workflow

Step 0 — Auto-Detect Mode

Silently check for .ai-style-rules.md at the project root:

File exists? Mode
No Branch A — First-time Full-Scan
Yes Branch B — Incremental Sniff

Announce the mode in one line and proceed — never ask the user to pick.

Branch A — First-time Full-Scan

1. Measure scale, pick a scanning tier

git ls-files | grep -cE '\.(js|ts|jsx|tsx|vue|py|go|rs|java|kt|rb|php|cs|swift|c|cpp|h)$'
Tier Source files Strategy
Small ≲ 50 Full close-read every source
Medium 50500 Infra layer = full read; business layer = sample 23 per dimension
Large ≳ 500 Strict sampling + budget cap; --stat summary first, then targeted reads

2. Scan along 4 dimensions

  1. File Anatomy — in-file declaration order (imports → types → main logic → helpers → export)
  2. State & Control Flow — naming conventions for async state, pagination, flags
  3. Infrastructure — where cross-cutting utils live (interceptors, formatters, middleware)
  4. Error Handling — try/catch vs global interceptor vs Result return; null-check habits

3. Apply signal-threshold noise reduction

Before interrupting the user, evaluate signal strength:

  • Weak signal → auto-suppress: minority <5% AND count <10 → majority wins, minority goes to DONTs
  • Strong signal → grill: near-even split, or semantic fork on a core dimension
  • Small-project exception: sources ≲50, "3 vs 2" is NOT a majority → grill it

4. Resolve conflicts one at a time (Grilling Protocol)

For each strong-signal conflict, present exactly ONE question with 4 options:

📄 Evidence: pathA uses style X, pathB uses style Y ⚠️ Risk: mixing both fractures the project style Choose: 1 follow X 2 follow Y 3 this is evolution, update rules 4 I have a new rule

Suspend until the user answers, then proceed to the next conflict. Never stack questions.

5. Generate .ai-style-rules.md with three mandatory sections:

  • [Golden Files] — real exemplar paths annotated with what they demonstrate
  • [Naming & State-Control Rules] — concrete, checkable conventions
  • [DONTs] — anti-patterns that must not propagate

6. Install the persistent hook

Ask the user for enforcement strength (use AskUserQuestion):

Option Mechanism
1 Soft hook (recommended) Write @.ai-style-rules.md reference into project CLAUDE.md
2 Hard hook Soft hook + `PreToolUse[Write
3 No hook Keep the rules file; user references manually

Branch B — Incremental Sniff

  1. Read existing .ai-style-rules.md; if it has a commit fingerprint, git diff <last_hash> HEAD --stat to pinpoint delta
  2. Read recent Git changes (git log -3 --stat → inspect suspect files on demand)
  3. For oversized diffs (>hundreds of files): --stat summary only + sample the largest changes
  4. Compare new code against recorded rules → conflicts go through Grilling Protocol
  5. Append evolution log at the end of .ai-style-rules.md (never overwrite old rules)

Per-Turn Enforcement

When .ai-style-rules.md is in context (loaded via CLAUDE.md), every code-writing task must open with a compliance declaration in the reasoning chain, naming the exemplar being followed and the DONTs being avoided.

How It Works

This skill auto-detects whether it's a first-time or incremental run via .ai-style-rules.md presence:

  • First-time (Branch A) — Measures project scale, scans codebase across 4 meta-architecture dimensions (File Anatomy, State & Control Flow, Infrastructure, Error Handling), applies signal-threshold noise reduction to suppress weak conflicts, resolves strong-signal conflicts one-at-a-time with the user, generates .ai-style-rules.md with Golden Files / Naming Rules / DONTs, and offers optional enforcement hooks.
  • Incremental (Branch B) — Reads existing rules, checks recent Git diffs for new or conflicting patterns, runs the same one-at-a-time grilling protocol for any conflicts found, and appends evolution logs without overwriting existing rules.
  • Per-Turn Enforcement — When hooked via CLAUDE.md, every code-writing task opens with a compliance declaration naming the exemplar followed and the DONTs avoided.

Output Specification

  • .ai-style-rules.md at project root (with commit fingerprint + scale tier in header)
  • Optionally CLAUDE.md with @.ai-style-rules.md reference
  • Evolution logs appended as ### [YYYY-MM-DD] Style Evolution Log entries

Anti-Patterns

  • Do NOT skip the scale measurement step — sampling a 30-file project "starves" it; full-scanning a 5,000-file repo blows up
  • Do NOT stack multiple conflict questions at once — grilling is strictly one-at-a-time
  • Do NOT overwrite old rules in incremental mode — always append evolution logs
  • Do NOT default to "hard hook" without asking — enforcement strength is the user's call
  • Do NOT judge syntax or tech-stack quality — this skill aligns meta-architecture only
  • Do NOT copy bugs from exemplar files — reuse structure, flag defects

Best Practices

  • Announce the detected mode (first-time vs incremental) and scale tier in one line before scanning
  • For large projects, read --stat summaries first, then targeted Read on suspect files
  • Let the signal threshold handle noise — a 843-vs-8 naming split should auto-resolve without user interruption
  • When in doubt about signal strength, lean toward asking
  • The CLAUDE.md soft hook (@.ai-style-rules.md) is usually sufficient; hard hook only if the user wants mechanical enforcement
  • init — initialize a new CLAUDE.md with codebase documentation
  • code-review — review diffs for correctness and style issues
  • simplify — review code for reuse and simplification opportunities

Examples

  1. First-time onboarding

    • User: "Help me onboard AI to this older codebase without changing its style."
    • Action: Run Branch A full-scan → measure scale → scan 4 dimensions → grill conflicts → generate .ai-style-rules.md → offer hook strength (soft/hard/none).
  2. Incremental update after team changes

    • User: "We added a new module; keep existing style rules intact."
    • Action: Run Branch B incremental sniff → compare Git deltas to recorded rules → grill any new conflicts → append evolution log without overwriting.
  3. Enforcing DONTs via CLAUDE.md

    • User: "Make sure all new code stays consistent with the project's rules."
    • Action: Soft hook installed → .ai-style-rules.md auto-loaded every session → every code-writing task opens with compliance declaration, reusing exemplar patterns and avoiding DONTs.