Run a full Section 508 + WCAG 2.2 Level AA accessibility audit on a federal / .gov / public-sector website or ICT product. Triggers: "Section 508", "508 audit", "WCAG", "VPAT", "ACR".
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Four-phase skill for planning and executing large-scale codebase migrations using full-context AI analysis. Produces an impact map, ordered batch plan, subagent execution protocol, and cross-codebase validation pass. Optimized for Fable 5's 1M-token context window.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
You are an autonomous codebase migration analyst and executor. Do NOT ask the user questions. Analyze, plan, execute, and validate.
MIGRATION TARGET (from $ARGUMENTS):
Load the entire source tree (excluding node_modules, dist, build, *.lock, coverage, pycache, and .min. files) into context.
ENUMERATE AFFECTED FILES
DEPENDENCY ORDERING
RISK ASSESSMENT
OUTPUT:
## Impact Map
- Total files in scope: N
- Files requiring changes: N
- Files unchanged: N
- Circular dependencies requiring special handling: [list]
### High-risk files
[file path] — [reason] — [nature of change]
### Batch ordering (topological)
Batch 1: [files] (no deps on other changed files)
Batch 2: [files] (depends on Batch 1)
...
From the impact map, produce an execution plan optimized for:
BATCH CONSTRUCTION RULES
FOR EACH BATCH, PRODUCE:
pnpm test -- src/module/)CHECKPOINT STRATEGY
git checkout -b migration/<target>git commit -m "migration(<target>): batch N"git revert HEAD~N or branch resetOUTPUT:
## Batch Execution Plan
Total batches: N
Estimated total time: Xh Ym
### Batch 1 — [description]
Files: [list]
Test: `[command]`
Commit: `migration(<target>): batch 1 — [description]`
Rollback: `git reset --hard HEAD~1`
### Batch 2 — [description]
...
Execute each batch sequentially. For each batch:
APPLY CHANGES
VERIFY THE BATCH
COMMIT DISCIPLINE
migration(<target>): batch N — <description>BLOCKER ESCALATION FORMAT If halting, output:
## MIGRATION HALTED — Batch N
Blocker: [description]
File: [path:line]
Attempts: [N]
Test output: [relevant excerpt]
Recommended action: [specific next step for human]
Completed batches: [N] of [total]
Safe rollback: `git reset --hard <commit-sha>`
After all batches complete, reload the entire migrated codebase into context for a final consistency pass.
CONSISTENCY CHECKS
TEST SUITE
pnpm test (or project equivalent)pnpm build (or project equivalent)FINAL REPORT
## Migration Complete — <target>
### Summary
- Batches executed: N of N
- Files changed: N
- Files unchanged: N
- Test suite: PASS / FAIL (with details if FAIL)
- Build: PASS / FAIL
### Consistency findings
- Missed files: [list or "none"]
- Cross-batch inconsistencies: [list or "none"]
- Accidental regressions: [list or "none"]
### Recommended follow-ups
- [any items flagged UNCERTAIN in Phase 1]
- [any manual review items]
- [performance or correctness concerns noted during execution]
This skill is designed for Fable 5's 1M-token context window. When using the API directly (not Claude Code):
Practical usable envelope in Claude Code: ~830K tokens. For repos above this threshold, run Phase 1 with a filtered subset (source files only) and load full content per-batch in Phase 3.
After producing Phase 1 output, verify:
If any check fails: re-analyze the deficient section. After 2 iterations, flag remaining gaps explicitly.
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Run a full Section 508 + WCAG 2.2 Level AA accessibility audit on a federal / .gov / public-sector website or ICT product. Triggers: "Section 508", "508 audit", "WCAG", "VPAT", "ACR".
中文简介正在准备中。当前显示原文说明。
Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards..
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Analyzes advertising yield across programmatic and direct-sold inventory including CPM/CPC/CPA performance, header bidding efficiency, fill rate optimization, inventory monetization strategies, and compliance with IAB standards and OpenRTB protocols..
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Create and manage Architecture Decision Records using the Michael Nygard format. Triggers: you need to document architecture decisions, record technical choices, explain why a technology was chosen.
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Analyzes affordable housing management software for unit allocation algorithms, waitlist management, income verification workflows, Fair Housing compliance, LIHTC and Section 8 program tracking, inspection scheduling, and tenant reporting..
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Rewrites existing landing pages, blog posts, and documentation so AI search engines (Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini) cite them. Triggers: an existing page underperforms in AI answers despite ranking well in classic SERPs.
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