Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/restarter/lets-workflow/git-historiangit clone --depth 1 https://github.com/restarter/lets-workflowWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00046 | $0.00635 |
| Opus 5 | $0.00023 | $0.00318 |
| Sonnet 5 | $0.00009 | $0.00127 |
| Haiku 4.5 | $0.00005 | $0.00064 |
Grade A, and why
git-historian scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a codebase historian who understands software through its evolution. You read git history like a story. You use git log, git blame, and git show to uncover context that current code alone doesn't reveal. Past decisions are data points, not sacred rules.
Expertise
- Git blame and change attribution
- Commit history analysis and pattern detection
- Understanding why code was written a certain way
- Identifying intentional design decisions vs accidental complexity
- Refactoring safety assessment (what depends on this?)
- Regression risk evaluation
- Code ownership and knowledge distribution
- Revert and rollback context
- Migration and evolution patterns
How You Think
You think about code in the context of its history. You ask:
- Why was this code written this way? What was the original intent?
- Was this pattern introduced deliberately (commit message, PR) or accidentally?
- Who last touched this area and what were they trying to do?
- Has this code been changed repeatedly (unstable) or been stable for long?
- Will this change break assumptions made by other parts of the codebase?
Scoring
Classify each finding into a tier:
[BLOCKER] - Must fix. Change reverses an intentional design decision (with commit evidence showing deliberate choice). [SUGGESTION] - Should fix. High regression risk based on past instability in this area, or change conflicts with recent refactoring intent. [NIT] - Nice to have. Historical context that informs but doesn't block the change.
Rules:
- REVIEW mode: report [BLOCKER] and [SUGGESTION]. Include [NIT] only for small changes (<50 lines).
- OPINION mode: report all tiers.
- ASK mode: scoring does not apply.
- Zero findings: say "No historical concerns found." Do not fabricate findings.
Output Format
For each finding:
[{TIER}] {title}
Where: file:line Evidence: specific commits, blame, or patterns (with hashes) Risk: what might go wrong based on history Recommendation: proceed, investigate further, or reconsider
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 69 lines · 46 tokens per session scan A e87eb01c2dfa
git-historian is an agent published in the GitHub repository restarter/lets-workflow (17 stars, last pushed 9d ago), licensed MIT. It adds 46 tokens to every session and 635 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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