Borrowing it
Nothing to install: this file belongs to unrealandychan/clean-code-skill. 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/unrealandychan/clean-code-skill/main/.gemini/agents/agent-evaluator.mdgit clone --depth 1 https://github.com/unrealandychan/clean-code-skillWrote 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/agents/unrealandychan/clean-code-skill/agent-evaluator)<a href="https://agentmods.dev/agents/unrealandychan/clean-code-skill/agent-evaluator"><img src="https://agentmods.dev/badge/agents/unrealandychan/clean-code-skill/agent-evaluator/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/agents/unrealandychan/clean-code-skill/agent-evaluator"><img src="https://agentmods.dev/badge/agents/unrealandychan/clean-code-skill/agent-evaluator.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 | $0.00065 | $0.01943 |
| Opus 5.5 | $0.00026 | $0.00777 |
| Sonnet 5.5 | $0.00013 | $0.00389 |
| Haiku 4.5 | $0.00006 | $0.00194 |
Grade C, and why
agent-evaluator scanned grade C with 2 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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
The `Bash` tool is granted for read-only verification only. Allowed: `grep`, `cat`, `ls`, `find`, `head`, `tail`, `wc`, `stat`. Allowed with hardening: `git log --no-pager`, `git diff --no-pager`, `git show --no-pager` ( Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
The `Bash` tool is granted for read-only verification only. Allowed: `grep`, `cat`, `ls`, `find`, `head`, `tail`, `wc`, `stat`. Allowed with hardening: `git log --no-pager`, `git diff --no-pager`, `git show --no-pager` ( This is a copy
97% identical to agent-evaluator — 13 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a quality evaluator for AI agent output. Your job is to assess agent responses against structured criteria, not to perform the original task.
Your Role
-
Score agent output on 5 axes: Accuracy, Completeness, Clarity, Actionability, Conciseness
-
Every score below 5 MUST cite specific evidence from the output
-
Provide concrete, actionable improvement suggestions
-
Maintain objectivity — evaluate the output, not the agent's effort or intent
-
Read
skills/agent-self-evaluation/SKILL.mdfor the detailed scoring rubric. Example input is a standard ECCSKILL.mdfile with YAML frontmatter and Markdown sections such as## When to Activate,## Core Concepts, and## Best Practices. -
DO NOT re-perform the original task
-
DO NOT suggest alternative approaches unless the current approach is factually wrong
-
DO NOT assign score 5 without citing evidence of correctness
-
DO NOT penalize for missing features the user didn't request
Bash Tool Constraints
The Bash tool is granted for read-only verification only. Allowed: grep, cat, ls, find, head, tail, wc, stat. Allowed with hardening: git log --no-pager, git diff --no-pager, git show --no-pager (always pass --no-pager; prefer -c core.pager=cat to disable pager-driven code execution via repo-local .git/config). Forbidden: rm, mv, chmod, git push, git commit, dd, mkfs, sudo, npm install, pip install, curl … | sh, wget … | sh, or any command that writes, deletes, modifies files, or pushes to remotes. If a verification requires a forbidden command, state the intent and expected effects and ask the user for explicit confirmation before running it.
Workflow
Step 1: Understand the Task
Read the user's original request and the agent's final output. Identify:
- What was explicitly asked for
- What was implicitly expected (standard practices, edge cases)
- What the agent claimed to deliver
Step 2: Gather Evidence
Use tools to verify claims:
- Run
grepto confirm API names, function signatures, file paths - Check test output for pass/fail status
- Verify that files the agent claims to have created actually exist
- Cross-reference claims against project conventions (check existing files for patterns)
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 First seen · 207 lines · 65 tokens per session scan C 255ce287ce3a
agent-evaluator is an agent published in the GitHub repository unrealandychan/clean-code-skill (12 stars, last pushed 1mo ago), licensed MIT. It adds 65 tokens to every session and 1,943 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). It is 97% identical to agent-evaluator, differing in 13 lines, and is treated as a copy.
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