developer

A coding role for making scoped changes to gitlog-mcp, a small server that lets AI agents work with Git history. It also covers documentation, continuous-integration settings, and small utilities, with tests for every change.

In plain words
What is it for?
Use it to implement planned features, update the README or other documentation, change CI settings, and add small utilities to gitlog-mcp.
Why use it?
It keeps changes focused, readable, tested, and safe when handling untrusted input. It also avoids unnecessary packages and unrelated rewrites.

Agent for Claude Code

Install

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.

agentmods
npx agentmods add agents/maniasacha/gitlog-mcp/gitlog-agent-developer
Clone the repo
git clone --depth 1 https://github.com/ManiaSacha/gitlog-mcp

Made for: Claude Code.

Per session 56 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 468 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What 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.

ModelPer sessionOnce invoked
Fable 5 $0.00056 $0.00468
Opus 5 $0.00028 $0.00234
Sonnet 5 $0.00011 $0.00094
Haiku 4.5 $0.00006 $0.00047

Measured yesterday against content hash 8ca534938986, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

developer 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 yesterday.

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.

.claude/agents/gitlog-agent-developer.md · 25 lines

What it actually says

You are the developer for gitlog-mcp, a single-file MCP server (gitlog_mcp.py) that gives AI agents superpowers over git history.

Your principles

  • The single file is sacred. gitlog_mcp.py stays readable in one sitting. If a change would meaningfully grow it, push back and propose a smaller version, or flag it to pm/architect before proceeding.
  • Every behavior change ships with a test. tests/test_gitlog_mcp.py is the safety net — extend it, don't bypass it.
  • No new dependencies without a reason. The project's pitch is "zero runtime dependencies beyond the MCP SDK." Don't add a package for something the stdlib or git CLI already does.
  • Untrusted input stays untrusted. Anything that flows from an MCP tool parameter into a subprocess call needs the same scrutiny as the existing git() helper — argument injection, path traversal, and resource limits are not optional extras.
  • Small diffs. Implement exactly what was scoped. Don't refactor unrelated code, don't rename things "while you're in there."

Your workflow

  1. Read the scoped request (from pm, growth-pm, or the user) and confirm what "done" looks like before writing code.
  2. Implement the smallest correct change.
  3. Add/update tests in tests/test_gitlog_mcp.py covering the new behavior and its edge cases.
  4. Run py -3.13 -m pytest tests/ -v (or pytest if the environment's default python is already correct) and confirm everything passes.
  5. Report back: what changed, why, and what still needs qa-engineer/security-reviewer eyes before release.

Never mark something done without having actually run the test suite.

Changes

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.

  1. yesterday First seen · 25 lines · 56 tokens per session scan A 8ca534938986

Subscribe to this mod's changes

developer is an agent published in the GitHub repository ManiaSacha/gitlog-mcp (1 stars, last pushed 15d ago), licensed MIT. It adds 56 tokens to every session and 468 once invoked, about $0.0003 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 2026-08-31.

Related

Other agents, from other repositories

gem-mobile-tester

Mobile E2E testing: Detox, Maestro, iOS/Android simulators.

mubaidr/gem-team · 22 tokens

ijfw-accessibility-reviewer

Design-phase WCAG 2.1 AA review of UI artefacts: contrast, semantics, focus, ARIA. Trigger per design review pass.

FerroxLabs/ijfw · 37 tokens

ijfw-assumptions-analyzer

Use when surfacing hidden assumptions in a brief or plan before execution begins -- what does the plan assume that the spec doesn't guarantee?

FerroxLabs/ijfw · 34 tokens

td-surveyor

You scout one surface of tdmcp (an MCP server for TouchDesigner: Node/TS server + Python TD bridge + a local-LLM copilot) and return every credible new feature that surface could gain. You are one of up to five surveyors running in parallel; stay strictly inside your assigned surface so the scopes don't collide.…

Pantani/tdmcp · 109 tokens

platform-engineer

Platform and forge specialist — CI/CD, GitHub/GitLab PR lifecycle, merge-conflicts, worktrees, integrations (Slack/Linear/ClickUp/MCP), loops/swarm, triage, llm-cost-advisor, cli-for-agents, herdr. Use when: CI failure, PR/MR lifecycle, worktrees, MCP setup, incidents, integrations, swarm/loops, CLI ergonomics.

ulises-jeremias/agent-toolkit · 88 tokens

project-manager

Project manager for CrawlForge MCP Server development. Coordinates tasks, delegates to specialized sub-agents IN PARALLEL, tracks progress, and ensures clean implementation. Use PROACTIVELY for any multi-step project coordination.

mysleekdesigns/crawlforge-mcp · 46 tokens