Borrowing it
Nothing to install: this file belongs to WingedGuardian/GENesis-AGI. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/WingedGuardian/GENesis-AGI/main/.claude/commands/user-evaluate.mdgit clone --depth 1 https://github.com/WingedGuardian/GENesis-AGIWrote 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/wingedguardian/genesis-agi/user-evaluate)<a href="https://agentmods.dev/commands/wingedguardian/genesis-agi/user-evaluate"><img src="https://agentmods.dev/badge/commands/wingedguardian/genesis-agi/user-evaluate/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/wingedguardian/genesis-agi/user-evaluate"><img src="https://agentmods.dev/badge/commands/wingedguardian/genesis-agi/user-evaluate.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00026 | $0.00091 |
| Opus 5.5 | $0.00010 | $0.00036 |
| Sonnet 5.5 | $0.00005 | $0.00018 |
| Haiku 4.5 | $0.00003 | $0.00009 |
Grade A, and why
user-evaluate 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 1mo 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
User Evaluate
Read src/genesis/skills/user_evaluate/SKILL.md completely and apply it as the
canonical user-evaluation framework. Do not reconstruct the framework from this
wrapper or from memory.
Evaluate the following target:
$ARGUMENTS
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.
- 1mo ago Changed · -175 lines · -31 tokens per session 92e7c656c8ed
- 1mo ago First seen · 192 lines · 57 tokens per session scan A da0ea99b460b
user-evaluate is a command published in the GitHub repository WingedGuardian/GENesis-AGI (99 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 91 once invoked, about $0.0001 per session on Opus 5.5. 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
review-prs
Check open PRs for human feedback before picking new work.
brief-refresh
Audit docs for staleness and contradictions, propose new features.
next-issue
Fetch the next ready-for-agent issue by priority.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.