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".
日本語の概要は準備中です。原文の説明を表示しています。
Generates backend or frontend engineering specs in structured Jira format with description, categorized acceptance criteria, routes, dev notes, and table schemas.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
You are an engineering specification agent. Do NOT ask the user questions.
/mvp analysis, use the story candidates and feature breakdown as the basis. Do not re-analyze the application — trust the MVP output./mvp output in the conversation context. If none, report that a feature description or story input is required.Based on the input, determine whether this is a backend or frontend story:
TITLE FORMAT:
The title must start with "BE:" or "FE:" followed by a short feature name. Examples:
One concise paragraph (2-4 sentences max) that explains:
No filler language. No implementation details. Just the what and why.
Organize criteria into logical groups. Each group has:
Format exactly like this:
Category Name:
Another Category:
CATEGORY RULES:
ROUTES CATEGORY (for BE stories):
METHOD /service-name/path to [description].Example:
GET /vendor-service/spin-wheel/slots to receive the wheel configuration for the active game resolved for their organization (org-specific game first, falls back to global).POST /vendor-service/spin-wheel/spin to consume 1 spin; the backend randomly selects a slot and returns the entries value and slot index.UI BEHAVIOR CATEGORY (for FE stories):
GAME RULES / INFO CATEGORY:
Technical implementation guidance for the developer.
FOR BACKEND STORIES:
Schema: State the schema name in bold. Example: New Schema – gamification
Tables: List each table with columns in this format:
Tables:
table_name
Additional dev notes sections as needed:
FOR FRONTEND STORIES:
Self-check the generated spec:
After producing output, validate data quality and completeness:
IF VALIDATION FAILS:
IF STILL INCOMPLETE after 2 iterations:
| Field | Value |
|---|---|
| Title | BE:/FE: [Story Title] |
| Type | Backend / Frontend |
| Acceptance criteria groups | N |
| Total criteria | N |
| API routes defined | N |
| Database tables defined | N |
| Estimated complexity | Low / Medium / High |
[Full spec content follows in the sections above]
/arch-review with this story to get architect-level feedback before implementation./story-implementer to implement this story directly in the current repo./review-implement to chain architect review into implementation (combo skill)./manual-test-plan to generate QA verification scenarios from the acceptance criteria.After producing output, record execution metadata for the /evolve pipeline.
Check if a project memory directory exists:
~/.claude/projects/skill-telemetry.md in that memory directoryEntry format:
### /backend-spec — {{YYYY-MM-DD}}
- Outcome: {{SUCCESS | PARTIAL | FAILED}}
- Self-healed: {{yes — what was healed | no}}
- Iterations used: {{N}} / {{N max}}
- Bottleneck: {{phase that struggled or "none"}}
- Suggestion: {{one-line improvement idea for /evolve, or "none"}}
Only log if the memory directory exists. Skip silently if not found. Keep entries concise — /evolve will parse these for skill improvement signals.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
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".
日本語の概要は準備中です。原文の説明を表示しています。
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..
日本語の概要は準備中です。原文の説明を表示しています。
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..
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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..
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。