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/goodgit 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/good)<a href="https://agentmods.dev/commands/mrgoonie/human-mcp/good"><img src="https://agentmods.dev/badge/commands/mrgoonie/human-mcp/good.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 5.1 | $0.00009 | $0.00175 |
| Opus 5 | $0.00005 | $0.00088 |
| Sonnet 5 | $0.00002 | $0.00035 |
| Haiku 4.5 | $0.00001 | $0.00017 |
Grade A, and why
good scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Write good creative & smart copy for this user request: <user_request>$ARGUMENTS</user_request>
Workflow
- If the user provides a screenshots or videos, use
eyes_analyzetool from Human MCP to describe as detailed as possible the issue, make sure copywriter can fully understand the issue easily based on the description. - Use multiple
researcheragents in parallel to search for relevant information & multiplescouteragents to scout the current codebase or given codebase (if any) to understand the project, then report back toplanneragent. - Use
planneragent to plan the copy, make sure it can satisfy the user request. - Use
copywriteragent to write the copy based on the plan, then report back to main agent.
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.
- 5d ago First seen · 13 lines · 9 tokens per session scan A f60d25e921a1
good is a command published in the GitHub repository mrgoonie/human-mcp (294 stars, last pushed 5mo ago), licensed MIT. It adds 9 tokens to every session and 175 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.
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