Track and update action item status from natural language updates like 'Seanのメールには返信しておいた' or 'Lu対応予定'. Integrates with daily-comms-ops workflow. Use when managing action items across communication channels.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Evaluate project deliverables (code, docs, config) and calculate a 0-100 completeness score with weighted criteria and prioritized action items. Use when assessing project readiness, reviewing milestones, or identifying gaps before release.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
실행 점수 미검증
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
This skill systematically evaluates project deliverables across multiple dimensions (functional requirements, quality standards, test coverage, documentation, deployment readiness) and produces a weighted 0-100 completeness score. It identifies gaps, ranks missing items by priority, and provides actionable next steps to reach completion.
Determine the project type and load the appropriate evaluation template.
Supported project types:
skill -- Claude skill development (SKILL.md, scripts, tests, references)webapp -- Web application (frontend, backend, API, tests, docs)library -- Reusable library/package (code, tests, docs, packaging)document -- Documentation-only project (structure, completeness, quality)custom -- User-defined criteria from JSON file# List available templates
python3 scripts/score_project.py --list-templates
# Use a specific template
python3 scripts/score_project.py --template skill --project-path ./skills/my-skill
Scan the project directory to inventory existing files and categorize them by evaluation dimension:
python3 scripts/score_project.py \
--template skill \
--project-path ./skills/my-skill \
--verbose
For each evaluation dimension, check criteria against the project inventory:
references/scoring-methodology.md for detailed scoring rulesFor each unmet criterion:
Produce a comprehensive report in both JSON and Markdown formats.
python3 scripts/score_project.py \
--template skill \
--project-path ./skills/my-skill \
--output-dir ./reports \
--format both
{
"schema_version": "1.0",
"project_path": "./skills/my-skill",
"project_type": "skill",
"timestamp": "2026-03-16T08:00:00Z",
"overall_score": 85,
"dimensions": [
{
"name": "Functional Requirements",
"weight": 0.30,
"raw_score": 90,
"weighted_score": 27.0,
"criteria": [
{"name": "SKILL.md exists", "met": true, "severity": "critical"},
{"name": "Scripts directory exists", "met": true, "severity": "major"}
]
}
],
"gaps": [
{
"criterion": "At least 3 tests",
"dimension": "Test Coverage",
"severity": "major",
"effort": "medium",
"priority": 1,
"action": "Add unit tests covering core scoring logic"
}
],
"summary": {
"critical_gaps": 0,
"major_gaps": 1,
"minor_gaps": 2,
"ready_for_release": false
}
}
# Project Completeness Report
**Project**: ./skills/my-skill
**Type**: skill
**Date**: 2026-03-16
**Overall Score**: 85/100
## Score Breakdown
| Dimension | Weight | Score | Weighted |
|-----------|--------|-------|----------|
| Functional Requirements | 30% | 90 | 27.0 |
| Quality Standards | 20% | 80 | 16.0 |
| Test Coverage | 25% | 70 | 17.5 |
| Documentation | 15% | 95 | 14.3 |
| Deployment Readiness | 10% | 100 | 10.0 |
## Priority Actions
1. **[Major]** Add unit tests covering core scoring logic
2. **[Minor]** Add inline code comments
3. **[Minor]** Create CHANGELOG.md
## Readiness Assessment
- Critical Gaps: 0
- Major Gaps: 1
- Minor Gaps: 2
- **Ready for Release**: No (resolve major gaps first)
scripts/score_project.py -- Main scoring script with CLI interfacereferences/scoring-methodology.md -- Detailed scoring rules and dimension definitionsreferences/project-templates.md -- Evaluation templates for different project types아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Track and update action item status from natural language updates like 'Seanのメールには返信しておいた' or 'Lu対応予定'. Integrates with daily-comms-ops workflow. Use when managing action items across communication channels.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
AI活用提案の専門コンサルタントスキル。LLM・AIエージェントの活用事例知識を基に、業界別、部門別、シーン別に最適なAI導入提案を行います。システム化、業務改善、効率化を得意とし、具体的な活用事例、期待効果、導入ステップを含む実践的な提案を提供します。Use when proposing AI/LLM adoption strategies for specific industries, departments, or business scenarios.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Generate AI-powered BPO service proposals for Japanese companies in the US market. Use when creating outsourcing proposals with AI service menus, ROI estimation, implementation roadmaps, and bilingual (JA/EN) proposal documents for 在米日系企業向けAI実装.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
AI(LLM)が生成した日本語テキストの「AI臭」を検出・診断し、人間らしい文章にリライトするスキル。 Use when: 「AIっぽい文章を直して」「人間らしくリライトして」「AI臭を消して」「この文章をもっと自然にして」 「テキストのAI感を減らして」「機械っぽさを取りたい」 "make this sound more human", "remove AI tone", "humanize this text", "detect if this is AI-generated". 6つのAI特有パターン(視覚的マーカー、単調なリズム、マニュアル的構成、非コミット姿勢、抽象語の濫用、 定型メタファー)を正規表現ベースで検出し、0-100のAI臭スコアを算出。3つの人間化技法 (バランスを崩す・客観を崩す・論理を崩す)でリライトを実行する。 Note: 検出スクリプトは日本語テキスト専用。英語テキストの場合はClaude自身がreferences/を参照して分析・リライトする。
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Generate audit-ready internal control design documents from As-Is business process inventories. Produces control IDs, assertion mappings, procedures, SoD analysis, KPIs, materiality thresholds, and implementation roadmaps. Use when building internal controls for new audit engagements, SOX/J-SOX compliance, or process improvement initiatives.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Review audit-related documents (control design documents, bottleneck analyses, requirements definitions, etc.) for quality, scoring them 0-100 with a severity-rated findings list. Use when reviewing audit documents, checking control design quality, or verifying cross-document consistency. Supports documents governed by US GAAP, IFRS, or J-GAAP.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.