Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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。
Detect project maturity stage (new/early/mid/mature) from file structure and route to appropriate onboarding workflow
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。
Detect the maturity stage of a software project by analyzing its file structure, configuration files, documentation, and test coverage. Route to the appropriate onboarding or initialization workflow based on the detected stage.
Skill({ skill: 'project-stage-detection' });
Invoke when:
| Stage | Description | Indicators |
|---|---|---|
new | Freshly initialized, no meaningful content | Only boilerplate files, no src/ |
early | Has core structure but missing key components | src/ exists, no tests or CI |
mid | Functional codebase, gaps in quality infrastructure | Tests exist, no CI/CD or sparse docs |
mature | Full-featured with CI/CD, tests, docs, linting | All quality gates present |
Command:
node .claude/skills/project-stage-detection/scripts/main.cjs --dir <project_root>
Expected output: JSON with stage, confidence, indicators, and recommendations.
Verify: Exit code 0 and valid JSON with a stage field.
The script checks for these indicators, scoring each:
| Indicator | Weight | Checked Path(s) |
|---|---|---|
| Source directory exists | HIGH | src/, lib/, app/ |
| Tests exist | HIGH | tests/, test/, spec/, __tests__/ |
| CI/CD pipeline configured | HIGH | .github/workflows/, .gitlab-ci.yml |
| Package.json / pyproject.toml | MED | package.json, pyproject.toml |
| README exists and non-trivial | MED | README.md (>500 bytes) |
| Linting configured | MED | .eslintrc*, .ruff.toml, pylintrc |
| Documentation directory | LOW | docs/, .claude/docs/ |
| Changelog present | LOW | CHANGELOG.md, CHANGELOG.rst |
| Dependencies locked | LOW | package-lock.json, pnpm-lock.yaml |
| Score Range | Stage |
|---|---|
| 0–2 | new |
| 3–5 | early |
| 6–7 | mid |
| 8–9 | mature |
Command to verify score:
node .claude/skills/project-stage-detection/scripts/main.cjs --dir . --json | node -e "const d=require('fs').readFileSync('/dev/stdin','utf8');const r=JSON.parse(d);console.log('Stage:',r.stage,'Score:',r.score,'Confidence:',r.confidence)"
Based on the detected stage:
| Stage | Recommended Action |
|---|---|
new | Invoke project-onboarding skill to bootstrap |
early | Invoke gap-detection to find missing infrastructure |
mid | Invoke gap-detection then proactive-audit |
mature | Invoke gap-detection as health check only |
Routing command:
// After detection
if (result.stage === 'new') {
Skill({ skill: 'project-onboarding' });
} else {
Skill({ skill: 'gap-detection' });
}
Output location: .claude/context/reports/backend/project-stage-report-YYYY-MM-DD.md
Report format:
# Project Stage Detection Report
**Date:** {{date}}
**Project:** {{project_root}}
**Detected Stage:** {{stage}}
**Confidence:** {{confidence}}%
## Evidence
{{indicators_table}}
## Recommendations
{{recommendations_list}}
See schemas/output.schema.json for the full structured output contract.
Input validated against schemas/input.schema.json before execution.
Output contract defined in schemas/output.schema.json.
planner — uses on task start to calibrate workflow complexityarchitect — uses for brownfield assessment before redesigndeveloper — uses to determine onboarding steps for new reposmaster-orchestrator — uses to route to correct initialization workflowBefore starting:
Read .claude/context/memory/learnings.md for any previously detected stage for this project. If the stage was recently detected (within 7 days), skip re-detection and use cached result.
After completing:
Append to .claude/context/memory/learnings.md:
## Project Stage Detection — {{date}}
- Project: {{project_root}}
- Stage: {{stage}} (confidence: {{confidence}}%)
- Key gaps: {{gap_summary}}
- Recommended next action: {{next_action}}
mature for a project with no tests — tests are a required mature indicator..claude/ subdirectories — scan the project root only.existsSync checks.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
Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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。
Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
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。
N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.
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。
Force adversarial code review stance that eliminates confirmation bias — reviewer must find issues or re-analyze
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。
Creates specialized AI agents on-demand when no existing agent matches a request. Use when the Router cannot find a suitable agent for a task. Enables self-evolution by generating persistent agents.
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。
LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations
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。