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[Git] Use when generating developer KPI, performance, contribution value, story point, man-day, or code-quality reports from local git commit history.
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インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/duc01226/EasyPlatform --skill git-developer-performanceコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
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SKILL.md を表示中
[Architecture] Use when designing solution architecture across backend, frontend, deployment, monitoring, testing, and code quality.
[Utilities] Use when you need to answer technical and architectural questions.
[Content] Use when you need to brainstorm as a PO/BA — structured ideation for problem-solving, new product creation, or feature enhancement.
SOC 職業分類に基づく
| name | git-developer-performance |
| version | 1.0.0 |
| description | [Git] Use when generating developer KPI, performance, contribution value, story point, man-day, or code-quality reports from local git commit history. |
Goal: Plan and generate a developer KPI-style quality-work report from local git history only. Workflow:
$plan, and create tasks per contributor.scripts/git-developer-performance.cjs to create commit inventory and work packets.quality-work-summary.md and evidence-proof.md outside .claude.
Key Rules:git history. Do not query external services.DOMAIN\first.lastpart matching a full name; use --identity-map for exceptions.man_days_traditional (no AI) and man_days_ai (AI coding assistant with project context)..claude before finalizing, so context loss cannot erase evidence..claude; default root is reports/developer-performance/.Use when the user asks for developer KPI/performance, productivity, contribution value, story-point estimates, man-day estimates, quality impact, or quality-work reporting from git commits.
Before analysis, set or declare this goal:
Plan and generate a developer performance quality-work report from local git history, then execute the plan and produce the report. Then trigger
$planor create equivalent plan artifacts. This skill is not a commit-list export. It requires reading direct commits and merge/admin commits per contributor, then synthesizing value. Use ultrathink/deep analysis for final synthesis when contributor count or churn is high.
node .claude/skills/git-developer-performance/scripts/git-developer-performance.cjs [options]
Options: --branch <ref> defaults to develop then main; --days <n> defaults to 60; --since <date> overrides days; --until <date> defaults now; --out <dir> defaults to reports/developer-performance; --identity-map <csv> accepts identity,email,displayName,id; --json prints machine-readable result.
Examples:
node .claude/skills/git-developer-performance/scripts/git-developer-performance.cjs
node .claude/skills/git-developer-performance/scripts/git-developer-performance.cjs --branch release/1.4 --days 30
node .claude/skills/git-developer-performance/scripts/git-developer-performance.cjs --since 2026-01-01 --until 2026-03-31 --out reports/dev-performance-q1
Creates a timestamped run folder containing:
summary.md - team evidence report, authored signal sort, warnings, and integration/admin activity.analysis-plan.md - AI execution plan with one task per contributor.work-packets/*.md - per-contributor commit/change packets for qualitative analysis.quality-work-summary.md and evidence-proof.md - AI-written value synthesis and proof appendix.analysis/ - target folder for AI-written per-contributor synthesis.contributors.csv, commits.csv, developers/*.md, data/*.json - source evidence and deterministic aggregates.references/analysis-workflow.md before final synthesis.analysis-plan.md.work-packets/*.md.git show --stat --find-renames <hash> and targeted patches for high-impact commits.Before delivering a generated report:
node --test .claude/skills/git-developer-performance/tests/*.test.cjs..claude.AI Mistake Prevention — Failure modes to avoid on every task:
Re-read files after context changes. Context compaction, resume, or long-running work can make memory stale; verify current files before acting. Verify generated content against source evidence. AI hallucinates APIs, names, claims, and document facts. Check the relevant source before documenting or referencing. Check downstream references before deleting or renaming. Removing an artifact can stale docs, generated mirrors, configs, and callers; map references first. Trace the full impact chain after edits. Changing a definition can miss derived outputs and consumers. Follow the affected chain before declaring done. Verify ALL affected outputs, not just the first. One green check is not all green checks; validate every output surface the change can affect. Assume existing values are intentional — ask WHY before changing. Before changing a constant, limit, flag, wording, or pattern, read nearby context and history. Surface ambiguity before acting — don't pick silently. Multiple valid interpretations require an explicit question or stated assumption with risk. Keep shared guidance role-relevant. Universal guidance must help every receiving skill or agent; code-specific obligations belong only in code-specific protocols.
Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.
IMPORTANT MUST ATTENTION Goal: Plan and generate a developer KPI-style quality-work report from local git history only.
Protocols in force (concise digest of the SYNC/shared blocks this skill carries):
MUST ATTENTION apply critical + sequential thinking — every claim needs appropriate traced evidence (file:line for repo/code claims; source URL or artifact section for research, product, content, and docs claims); confidence >80% to act, <60% DO NOT recommend. Anti-hallucination: never present guess as fact, admit uncertainty freely, cross-reference independently, stay skeptical of own confidence.
IMPORTANT MUST ATTENTION use local git history only.
IMPORTANT MUST ATTENTION trigger planning before qualitative analysis; this is a large task.
IMPORTANT MUST ATTENTION default to develop, fallback to main, and use last 60 days when the user does not specify.
IMPORTANT MUST ATTENTION do not present authored or integration signals as complete measures of human performance.
IMPORTANT MUST ATTENTION shared feature-branch implementation credit follows direct commit authors, not merge authors; never let raw churn or zero-change merge/admin commits inflate implementation SP or man-day estimates.
IMPORTANT MUST ATTENTION never publish a single ambiguous MD number; show no-AI and AI-assisted MD separately.
MUST ATTENTION apply AI mistake prevention — verify generated content against evidence, trace downstream references before deleting or renaming, verify all affected outputs, re-read files after context loss, and surface ambiguity before acting.