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-review)<a href="https://agentmods.dev/commands/uipath/coder_eval/coder-eval-review"><img src="https://agentmods.dev/badge/commands/uipath/coder_eval/coder-eval-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-review"><img src="https://agentmods.dev/badge/commands/uipath/coder_eval/coder-eval-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 | $0.00014 | $0.01670 |
| Opus 5.5 | $0.00006 | $0.00668 |
| Sonnet 5.5 | $0.00003 | $0.00334 |
| Haiku 4.5 | $0.00001 | $0.00167 |
Grade A, and why
coder-eval-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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context
If $ARGUMENTS is empty or blank, resolve the run to review per the "No target given" rule in .claude/shared/run-layout.md — discover the run root, then take latest if that symlink resolves and the newest run directory by name if it does not. Tell the user which run you picked and how you got there before reading anything.
You are producing post-run reviews for a coder_eval evaluation run. The target path is: $ARGUMENTS
For each failed task in the run you write a structured review.json next to that task's task.json, plus a small review_index.json digest at the run root for fast aggregation. Output is JSON only — no narrative.
Step 1: Load the suggested vocabulary
Read src/coder_eval/resources/tags.yaml (relative to the repo root). It has a top-level tags: list of {name, definition, examples} entries. Prefer these names when classifying — but the vocabulary is a suggestion, not a strict allowlist. If nothing fits, emit a kebab-case slug that does. Drift is caught by a lint, not blocked at write time.
If the vocabulary file is missing or unparseable, continue with an empty suggestion list (don't abort) — drift lint will surface every tag you emit.
Step 2: Discover failed tasks
The run layout (runs/<run_id>/<variant_id>/<task_id>/<NN>/…, <NN> a zero-padded replicate index) is defined in .claude/shared/run-layout.md.
- Read
<run_path>/run.jsonif present (for context —run_id,start_time). - Glob
<run_path>/*/*/*/task.jsonand read each one. - Read
<run_path>/analysis.mdif present — it already diagnoses many failures; lean on its findings rather than re-deriving them. - Skip any task whose
final_statusis"NOT_GRADED"—coder-eval executeproduced it, no criterion ran, andweighted_scoreisnull. It is neither a pass nor a failure, and comparingnull < 0.9would book every ungraded row as a failure to review. - Of the rest, a task counts as failed if
final_status != "SUCCESS"orweighted_score < 0.9. Skip passing tasks for now (we may extend to passing tasks later — the schema supports it).
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 · +1 lines 163d0abbd035
- 1mo ago First seen · 104 lines · 14 tokens per session scan A 1ff86c493206
coder-eval-review is a command published in the GitHub repository UiPath/coder_eval (151 stars, last pushed yesterday), licensed Apache-2.0. It adds 14 tokens to every session and 1,670 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
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usage-add
PitWay: Accumulate measured planning or qa token usage onto a milestone.
verify
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aitask-audit-wrappers
Audit and port aitask skill wrappers across code-agent trees, plus helper-script whitelist coverage.
checklist
Generate a custom checklist for the current feature based on user requirements.