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/hardgit 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/hard)<a href="https://agentmods.dev/commands/mrgoonie/human-mcp/hard"><img src="https://agentmods.dev/badge/commands/mrgoonie/human-mcp/hard.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 | $0.00009 | $0.00276 |
| Opus 5 | $0.00005 | $0.00138 |
| Sonnet 5 | $0.00002 | $0.00055 |
| Haiku 4.5 | $0.00001 | $0.00028 |
Grade A, and why
hard 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
Ultrathink to plan & start fixing these issues follow the Orchestration Protocol, Core Responsibilities, Subagents Team and Development Rules: $ARGUMENTS
Workflow:
If the user provides a screenshots or videos, use eyes_analyze tool from Human MCP to describe as detailed as possible the issue, make sure developers can predict the root causes easily based on the description.
- Use
plannersubagent andresearchersubagent to create a implementation plan with TODO tasks in./plansdirectory. - Then use general agent (main agent) to implement the plan step by step.
- Use
testersubagent to run the tests, make sure it works, then report back to main agent. - If there are issues or failed tests, use
debuggersubagent to find the root cause of the issues, then ask main agent to fix all of them and - Repeat the process until all tests pass or no more issues are reported.
- After finishing, delegate to
code-reviewersubagent to review code. If there are critical issues, ask main agent to improve the code and test everything again. - Report back to user with a summary of the changes and explain everything briefly.
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 · 19 lines · 9 tokens per session scan A 651ee57a3f7e
hard is a command published in the GitHub repository mrgoonie/human-mcp (295 stars, last pushed 5mo ago), licensed MIT. It adds 9 tokens to every session and 276 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.
env-setup
Set up environment configuration files from templates with validation.
debug-pod
Debug a failing or unhealthy Kubernetes pod by analyzing events, logs, and configuration.
document-all
Auto-document the entire codebase by generating module-level docs, function signatures, and API references.
fix-comments
Address PR review comments by implementing requested changes automatically.