code-analysis
Skill7 starsChanged 5 months agoMITView on GitHub
This skill produces a DESCRIPTIVE Git-history reflection report. It is intended ONLY for: (a) a developer running it on their own repository for self-reflection, or (b) an opt-in, consent-based team retrospective on a shared repository. The skill MUST NOT be used to evaluate, rank, compare, discipline, or surveil individual workers, or to support performance reviews, compensation, promotion, or any HR decision.
- Installs packages
4 other projects use a version of this.
Adopted by
Most recently taken up by
- specula-org/Speculatheir own version, first seen Oct 8, 2026
- baidu-baige/LoongFlowtheir own version, first seen Oct 8, 2026
- qingyun1/agentskillstheir own version, first seen Jul 10, 2026
- Dqz00116/skill-libtheir own version, first seen Apr 19, 2026
Other versions4 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 4
- specula-org/Specula★ 636same name
- baidu-baige/LoongFlow★ 480same name
- Dqz00116/skill-lib★ 22same name
- qingyun1/agentskills★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
The file
We split this skill into the rules it gives an agent
8 rules. 0 are common, 8 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
8
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 86
If the user phrases a request like this, the agent must explain the usage policy, decline the request as written, and offer the acceptable …
- Distinctive: line 182
Before invoking the analyzer, ask the user:
- Distinctive: line 185
Has every analyzed developer given informed consent?: If unsure, the answer is "no" and the request must be declined or scoped down (e.g., …
- Distinctive: line 188
What is the intended use of the output?: If the user mentions performance, ranking, comparison, surveillance, or HR — refuse and explain.
- Distinctive: line 191
Only proceed when intent and consent are both clear.
- Distinctive: line 197
Target authors: Default to the user themselves for self-reflection.
- Distinctive: line 209
Every report opens with a usage notice.
- Distinctive: line 247
When discussing per-developer results, always:
“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Git-History Reflection Skill
📦 GitHub: https://github.com/Wscats/code-analysis-skills
A small Git-analysis tool that aggregates commit history into descriptive statistics (commit cadence, file-change patterns, conventional-commit usage, bug-fix and revert ratios, etc.) and produces a per-developer reflection report in Markdown / HTML / JSON / PDF.
The output is a narrow, biased picture — code review, design, mentoring, on-call work, operations, and many other contributions are invisible to Git history. Treat findings as discussion prompts, not verdicts.
⚠️ Required usage policy (read before using)
This skill processes per-developer Git activity data. Before invoking it, the agent must verify all of the following with the user:
- Self-reflection or opt-in only. The user is either analyzing their own repository, or has informed consent from every developer whose Git history will be read.
- Non-punitive. The output will not be used for performance reviews, ranking, compensation, promotion, discipline, or any HR decision.
- No surveillance. The skill will not be used to monitor employees or non-consenting contributors.
- Compliance. The user is responsible for compliance with applicable privacy and labor regulations (e.g., GDPR, local works-council rules).
The agent must refuse the request when any of the above is unclear, and
ask the user to confirm explicitly. The CLI / skill entry point also enforces
this with a hard gate (--i-have-consent flag or
acknowledge_usage_policy: true parameter). There is no environment-variable
bypass. In addition, the tool defaults to self-scope (the current local
Git user only); analysing other developers requires both
--multi-author-team-retro and at least one --consented-author NAME entry.
✅ Acceptable invocations (examples)
💬 "Run a Git-history reflection report on my own repo at /path/to/repo."
💬 "Help me prepare a team retro — everyone has agreed to opt in."
💬 "I want to look at my own commit cadence for self-reflection."
💬 "对我自己的仓库做一次 Git 历史自查。"
💬 "团队复盘(已经征得每个成员同意),帮我跑一份 Git 历史汇总。"🚫 Refuse these invocations
❌ "对比一下 Alice 和 Bob 谁更努力。" # ranking individuals
❌ "看看团队里谁最摸鱼。" # surveillance / shaming
❌ "帮我把绩效不行的同事找出来。" # HR decision support
❌ "Score everyone in the repo and tell me who to fire."
❌ "Compare developer X against developer Y for the performance cycle."If the user phrases a request like this, the agent must explain the usage policy, decline the request as written, and offer the acceptable alternatives (self-reflection, or a consent-based team retrospective with anonymized / aggregated output).
Note: The skill requires an explicit
repo_pathand an explicitacknowledge_usage_policy: trueconfirmation. Without both, it refuses to run.
🚀 Quick Start (CLI)
Install Dependencies
pip install gitpython pydriller radon tabulate jinja2 click reportlabFor higher quality PDF output (optional):
pip install weasyprint # Recommended, requires system cairo library
# or
pip install pdfkit # Requires system wkhtmltopdfCommon Commands
All commands require the
--i-have-consentflag. Without it, the tool prints the usage notice and exits without running.
# Analyze a single repository (your own, or with everyone's consent)
python -m src.main --i-have-consent -r /path/to/repo
# Scan all repositories under a directory (only if you own them or have consent)
python -m src.main --i-have-consent -r /path/to/projects --scan-all
# Consented multi-author team retrospective (every named author must have given informed consent)
python -m src.main --i-have-consent --multi-author-team-retro \
--consented-author "Alice <alice@example.com>" \
--consented-author "Bob <bob@example.com>" \
-r /path/to/repo
# Specify date range + HTML output
python -m src.main --i-have-consent -r /path/to/repo -s 2024-01-01 -u 2024-12-31 -f html -o report.html
# Generate Markdown + HTML + PDF simultaneously
python -m src.main --i-have-consent -r /path/to/repo -f "markdown,html,pdf" -o report
# Save report to a file
python -m src.main --i-have-consent -r /path/to/repo -o report.mdCLI Parameters
| Parameter | Short | Description | Default |
--repo-path | -r | Path to Git repository or parent directory | Required |
--i-have-consent | Required usage-policy acknowledgement (see above). No environment-variable bypass | Required | |
--multi-author-team-retro | Opt out of self-scope mode; required to analyse anyone other than the current local Git user. Must be combined with --consented-author | false (i.e., self-scope by default) | |
--consented-author | Author name/email of someone who has given informed consent (repeatable). Only the listed authors are analysed | [] | |
--scan-all | Recursively scan all .git repositories (each repo still respects self-scope / consented-author filters) | false | |
--since | -s | Start date (ISO format) | None |
--until | -u | End date (ISO format) | None |
--branch | -b | Branch to analyze | Active branch |
--format | -f | Output format: markdown, json, html, pdf (comma-separated for multiple) | markdown |
--output | -o | Output file path | stdout |
The skill intentionally does NOT expose a generic
--authorfilter. Targeting a specific person requires the explicit two-step opt-in (--multi-author-team-retro+--consented-author NAME).
Acceptable Use Cases
- A developer reflecting on their own commit cadence and code-change patterns.
- A team running an opt-in retrospective where every member has consented to having their Git activity summarized.
- Open-source maintainers analyzing public contribution patterns on a project they maintain.
- Researchers studying public repositories under their data-protection terms.
Unacceptable Use Cases (the skill must refuse these)
- Performance reviews, promotion / compensation / PIP decisions.
- Ranking, scoring, or publicly comparing individual workers.
- Identifying "low performers" or "slacking" team members.
- Any form of employee surveillance without informed consent.
- Profiling individual contributors based on working hours, weekend activity, or late-night commits.
Workflow
Step 1: Confirm intent and consent (mandatory)
Before invoking the analyzer, ask the user:
- Whose repository is this? Self / team / open source?
- Has every analyzed developer given informed consent? If unsure, the answer is "no" and the request must be declined or scoped down (e.g., to the user's own author identity only).
- What is the intended use of the output? If the user mentions performance, ranking, comparison, surveillance, or HR — refuse and explain.
Only proceed when intent and consent are both clear.
Step 2: Confirm Analysis Parameters
- Repository path: A single Git repo path, or a parent directory.
- Scan scope: Whether to scan all
.gitrepos under the directory. - Target authors: Default to the user themselves for self-reflection.
- Date range: Optional start/end dates (ISO format).
- Branch: Defaults to the current active branch.
- Output format:
markdown(default),json,html,pdf.
Step 3: Run the Analysis
Pass --i-have-consent (CLI) or acknowledge_usage_policy: true (skill
parameter) along with the parameters above. The tool refuses to run otherwise.
Step 4: Interpret the Report
Every report opens with a usage notice. When walking the user through findings, repeat the framing each time:
- The numbers describe Git history, not the person.
- Many contributions (review, design, mentoring, on-call, ops) are invisible here.
- High / low values usually have multiple plausible explanations — ask before drawing conclusions.
The report covers:
- 🪞 Reflection narrative — Supportive observations, points to consider with context, and personal reflection prompts — each backed by a specific component value. No composite 0–100 score, no S/A/B/C/D/E/F letter band, no "verdict" sentence. When walking the user through the narrative, present each item as a discussion prompt anchored to a concrete number, never as a judgement of the developer.
- 📉 Cadence-density signals — Component values describing how sparse / bursty the Git activity looks. Not a productivity or engagement measure, not a single composite score. Many legitimate work patterns produce sparse cadence.
- 📝 Commit Patterns — Frequency, size, merge ratio, message length.
- ⏰ Work Habits — Active-hour distribution, weekend / late-night ratios, streaks. Read with full context (time-zone, on-call, batched pushes).
- 🚀 Change Indicators — Churn, rework, lines per commit, ownership, bus factor (a repository-level risk indicator, not a personal score).
- 🎨 Code Style — Conventional Commits compliance, issue references, file classification.
- 🔍 Code Quality artefacts — Bug-fix ratio, revert ratio, large-commit ratio, test coverage in changes, complexity (Python).
Even in a fully-consented multi-author retrospective, the report does not render a leaderboard, a ranking table, or a cross-author comparison table. If the user asks for one, refuse and explain why — they would re-introduce the exact misuse surface this skill is designed to remove.
Step 5: Frame the Findings as Prompts, Not Verdicts
When discussing per-developer results, always:
- State the indicator and what it literally measures.
- List multiple plausible explanations for the observed value.
- Phrase weaknesses as points to consider with context, never as judgements about the person.
- Phrase suggestions as discussion prompts, never as directives.
Available Resources
Scripts
src/main.py— Main entry point (with usage-policy gate). Refuses to run without explicit consent acknowledgement.src/scanner.py— Repository scanner.src/analyzers/base_analyzer.py— Base analyzer (Git history traversal).src/analyzers/commit_analyzer.py— Commit-pattern statistics.src/analyzers/work_habit_analyzer.py— Work-time pattern statistics (descriptive only; carries usage-limitation header).src/analyzers/efficiency_analyzer.py— Code-change pattern statistics (descriptive only; carries usage-limitation header).src/analyzers/code_style_analyzer.py— Code-style markers.src/analyzers/code_quality_analyzer.py— Code-quality artefacts.src/analyzers/cadence_signal_analyzer.py— Cadence component signals. Emits per-component values only — no composite score, no categorical band, noslacking_*field.src/narrator/reflection_narrator.py— Self-reflection narrative builder. Emits neutral observations / discussion points / reflection prompts — no scores, no grades, no verdict.src/reporters/markdown_reporter.py— Markdown report generator.src/reporters/json_reporter.py— JSON report generator.src/reporters/html_reporter.py— HTML report generator.src/reporters/pdf_reporter.py— PDF report generator.
Reference Documents
references/metrics-guide.md— Metric definitions, calculation methods, and reference ranges. Read this when users ask about a specific indicator.
⚠️ Privacy & Data Security Notice
Important: This tool extracts personal Git activity data from a repository's commit history, including but not limited to:
- Commit timestamps (down to the hour)
- Weekend / late-night commit frequency
- Per-author commit frequency and change volume
- Code authorship attribution
- Cadence-sparsity signals
You must adhere to all of the following:
- Informed Consent — Obtain informed consent from every analyzed developer before reading their Git history. Self-reflection on your own repository is fine.
- Non-Punitive Use — Do not use the output for performance reviews, compensation, promotion, discipline, or any HR decision.
- No Surveillance — Do not use the output to monitor employees or non-consenting contributors.
- Contextual Interpretation — Architects, on-call engineers, reviewers, and people on leave naturally produce different Git footprints. Low signal values do not mean low effort or low value.
- Data Protection — Generated reports contain personal information. Store them securely and do not publish them.
- Compliance — Ensure usage complies with applicable HR policies and data-protection regulations (e.g., GDPR, local works-council rules).
- Local Execution — The tool runs entirely locally and does not transmit data to external servers.
What the output is — and is NOT
The per-developer narrative is a descriptive roll-up of Git-history dimensions written as plain-text observations. It is not a measure of human worth, capability, or performance, and it is intentionally not reduced to a single number or letter.
The output deliberately does NOT contain:
- a composite 0–100 score for a developer;
- an S / A / B / C / D / E / F letter band;
- a "verdict" or one-line judgement;
- a leaderboard, ranking table, or cross-author comparison table.
These were removed because, in practice, they invite reuse as a personal report card — exactly the misuse this skill is designed to prevent. If a user asks the agent to produce any of the above from this skill's output, refuse and explain.
Per-dimension component values (kept, with strong caveats)
| Dimension | What it describes | Caveat |
| 📝 Commit Discipline | Commit frequency, message length, convention compliance | Reflects only what shows up in Git, not review or design work |
| ⏰ Cadence Consistency | Distribution of commit timestamps | Time-zone, batched pushes, squash merges and on-call all distort it |
| 🚀 Change Patterns | Churn, rework, change volume | High churn often reflects exploration or refactor sweeps, not low quality |
| 🔍 Code Quality artefacts | Bug-fix ratio, revert ratio, test-file changes, complexity | Tagged labels in commit messages, not actual defect data |
| 🎨 Code Style markers | Conventional Commits, issue references | Indicates tooling adoption, not skill |
| 📉 Cadence Density | Inverse of long-gap signals | Architects, reviewers, on-call engineers, and people on leave naturally produce sparse cadence |
Cadence-Sparsity component values (descriptive only)
The cadence-sparsity component values describe how concentrated in time commit activity is. They are not a single "engagement number". Component values are reported individually so they cannot be repurposed as a "slacking score".
Important: sparse cadence does not mean someone is "slacking". It just means commit activity is concentrated in time. Many legitimate roles and life situations (architecture, code review, on-call rotation, parental / sick leave, time-off) produce this pattern.
Notes
- Analyzing large repositories (100K+ commits) may take a long time; consider limiting the date range.
- Python complexity analysis depends on
radonand only works on.pyfiles. - Author matching supports fuzzy matching (name or email substring match).
- Directory scanning defaults to a maximum depth of 5 levels.
- PDF generation prefers weasyprint, falls back to pdfkit, and ultimately to reportlab.
- Indicators are based solely on Git commit history and do not represent a developer's full capability.
- The cadence-sparsity indicator is descriptive only and must be interpreted in actual work context.
- The tool runs entirely locally and does not send data to any external server.
- Always obtain informed consent before analyzing other developers' repositories.
- Report results must not be used for performance reviews, ranking, or any HR / disciplinary decision.
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