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.
git clone --depth 1 https://github.com/UiPath/coder_evalWrote 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/uipath/coder_eval/coder-eval-code-review)<a href="https://agentmods.dev/commands/uipath/coder_eval/coder-eval-code-review"><img src="https://agentmods.dev/badge/commands/uipath/coder_eval/coder-eval-code-review/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/uipath/coder_eval/coder-eval-code-review"><img src="https://agentmods.dev/badge/commands/uipath/coder_eval/coder-eval-code-review.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 | $0.00017 | $0.02210 |
| Opus 5.5 | $0.00007 | $0.00884 |
| Sonnet 5.5 | $0.00003 | $0.00442 |
| Haiku 4.5 | $0.00002 | $0.00221 |
Grade A, and why
coder-eval-code-review 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.
How it starts
The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context
- Current git status: !
git status --short - Current branch: !
git branch --show-current - Uncommitted changes: !
git diff --name-only && git diff --name-only --cached
Your Task
Run a thorough code review using multiple AI models in parallel, then fix all high-confidence medium-severity and above findings.
Cost note: This command runs make verify + a multi-model review (gemini-3 + gpt-5 via MCP, plus an Opus sub-agent) + automatic fixes. Expensive in time and tokens. Use this for changes you're about to ship; for broad codebase audits use /coder-eval-code-review-full; for quick local checks, run targeted tools (ruff, pyright, pytest) directly.
Input: $ARGUMENTS
Determining Scope
If input was provided: Interpret it as a description of what was changed. Use it to identify the relevant files — search the codebase, read recent commits, check git status — then read those files in full.
If no input was provided: Review all locally modified files (unstaged + staged, not yet committed). Identify them from git diff --name-only and git diff --name-only --cached. If there are no uncommitted changes, review the files changed in the most recent commit (git diff HEAD~1 --name-only).
Read all identified files in full before launching any review.
Severity Standard
Tag every finding 🔴 Critical / 🟠 High / 🟡 Medium / 🔵 Low. Calibrate by impact if shipped, not by fix difficulty. When torn between two levels, pick the lower one. Use the anchors below to keep ratings reproducible across runs and across reviewers.
| 🔴 Critical | 🟠 High | 🟡 Medium | 🔵 Low |
|---|---|---|---|
Data loss; secrets/credentials leak; security hole reachable in production; crash on the golden path; silently-wrong EvaluationResult |
Wrong behavior on a common path; race condition; resource leak (subprocess, tempdir, file handle); bare except swallowing a specific error class; logic fix landing without a regression test |
Design issue (KISS/DRY/CLAUDE.md violation); Checklist hit outside a hot path; weak test that wouldn't catch the regression; missing extra="forbid" on a config model |
Style or naming nit; missing internal docstring; redundant comment; example in --help is stale |
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 · 155 lines · 17 tokens per session scan A aee8c8373420
coder-eval-code-review is a command published in the GitHub repository UiPath/coder_eval (151 stars, last pushed yesterday), licensed Apache-2.0. It adds 17 tokens to every session and 2,210 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.
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