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 commands/mrgoonie/human-mcp/cigit clone --depth 1 https://github.com/mrgoonie/human-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/mrgoonie/human-mcp/ci)<a href="https://agentmods.dev/commands/mrgoonie/human-mcp/ci"><img src="https://agentmods.dev/badge/commands/mrgoonie/human-mcp/ci.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00007 | $0.00125 |
| Opus 5 | $0.00003 | $0.00063 |
| Sonnet 5 | $0.00001 | $0.00025 |
| Haiku 4.5 | $0.00001 | $0.00013 |
Grade A, and why
ci 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 4d 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.
What it actually says
Github Actions URL
$ARGUMENTS
Workflow
- Use the
planer-researcherto read the github actions logs, analyze and find the root causes of the issues, then provide a detailed plan for implementing the fixes. - Use proper developer agents to implement the plan.
- Use
testeragent to run the tests, make sure it works, then report back to main agent. - If there are issues or failed tests, ask main agent to fix all of them and repeat the process until all tests pass.
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.
- 4d ago First seen · 12 lines · 7 tokens per session scan A e906072a3279
ci is a command published in the GitHub repository mrgoonie/human-mcp (295 stars, last pushed 5mo ago), licensed MIT. It adds 7 tokens to every session and 125 once invoked, about $0.0000 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.
Other commands, from other repositories
report
Generate a project analytics report covering code quality, velocity, and health metrics.
explain
Explain a code file, function, or concept in clear, structured language.
design-api
Design a RESTful or GraphQL API based on the project's domain model and requirements.
write-adr
Create a new Architecture Decision Record documenting a technical decision.
create-activity
Generate a Jetpack Compose screen with proper architecture.
generate-api-ref
Generate API reference documentation from source code and route definitions.