A review process for SkillsBench tasks, which are benchmark tasks used to test coding agents. It checks the task rules, runs benchmark configurations, examines agent work, and produces review files.

It is for reviewing a local task or pull request, classifying its track, running policy checks and benchmarks, auditing agent trajectories, and creating a report and review bundle.

It gives reviewers evidence for deciding whether a task is valid, works as intended, and was completed without cheating or incorrectly using skills.

How benchflow-ai/skillsbench configures Claude Code and Codex

About the project

SkillsBench is a benchmark for measuring how effectively AI agents use modular skills—folders containing instructions, scripts, and resources—to complete specialized tasks. It helps researchers and developers evaluate both skill quality and agent behavior, including tasks that require combining multiple skills. The catalogue’s skills and instructions are evaluated as part of this workflow.

benchflow-ai/skillsbench · 1,867 stars · on GitHub · skillsbench.ai

Reuse

Borrowing it

Nothing to install: this file belongs to benchflow-ai/skillsbench. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/benchflow-ai/skillsbench/main/.agents/skills/task-review/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/benchflow-ai/skillsbench

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/task-review/github.svg)](https://agentmods.dev/skills/benchflow-ai/skillsbench/task-review)

Your own site

<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/task-review"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/task-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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/task-review"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/task-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 141 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 4,444 The whole file, excluding the scripts and references it only reads on demand.

Security scan B 2 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 8 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

high Agent Snooping · line 87
Skill reads from agent configuration directories (.claude/, .codex/, .gemini/). These directories may contain API keys, personal settings, and other credentials that the skill has no legitimate need to access.

Fix: Remove all code or instructions that access agent configuration directories (.claude/, .codex/, .gemini/). If configuration values are needed, pass them explicitly as parameters or environment variabl
high Agent Snooping · line 87
Skill reads from agent configuration directories (.claude/, .codex/, .gemini/). These directories may contain API keys, personal settings, and other credentials that the skill has no legitimate need to access.

Fix: Remove all code or instructions that access agent configuration directories (.claude/, .codex/, .gemini/). If configuration values are needed, pass them explicitly as parameters or environment variabl
high Agent Snooping · line 100
Skill reads from agent configuration directories (.claude/, .codex/, .gemini/). These directories may contain API keys, personal settings, and other credentials that the skill has no legitimate need to access.

Fix: Remove all code or instructions that access agent configuration directories (.claude/, .codex/, .gemini/). If configuration values are needed, pass them explicitly as parameters or environment variabl
high Agent Snooping · line 87
Skill reads from agent configuration directories (.claude/, .codex/, .gemini/). These directories may contain API keys, personal settings, and other credentials that the skill has no legitimate need to access.

Fix: Remove all code or instructions that access agent configuration directories (.claude/, .codex/, .gemini/). If configuration values are needed, pass them explicitly as parameters or environment variabl
high Privilege Escalation · line 107
Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.

Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
medium Rogue Agent · line 107
Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.

Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
medium Rogue Agent · line 144
Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.

Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
medium Agent Snooping · line 203
Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.

Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

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	$0.00141	$0.04444
Opus 5.5	$0.00056	$0.01778
Sonnet 5.5	$0.00028	$0.00889
Haiku 4.5	$0.00014	$0.00444

Measured 1mo ago against content hash 0e0c6d1cd259, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade B, and why

task-review scanned grade B 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.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/fetch_pr.sh, scripts/package_traj.sh, scripts/parse_results.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

1. The user's own configs: `cat ~/.codex/config.toml` (often pins a Codex model + reasoning effort), `~/.claude/settings.json` for Claude.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

| `verifier/test_outputs.py` imports a network client (`exa_py`, `requests`, `urllib`, `httpx`, `googleapiclient`) used during verification | **research-track** |

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

task-review — 95% identical, 7 lines differ

.agents/skills/task-review/SKILL.md · 206 lines

How it starts

The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SkillsBench Task Review

End-to-end review of a SkillsBench task PR. Two artifacts are produced: a human-readable .txt report, and a pr<N>.zip bundle that mirrors the format reviewers post on PRs (see PR #560 comment for the reference structure).

Workflow

1. fetch       → pull PR files into a workspace (no git checkout)
2. route       → classify task track; pick the track-specific rubric
3. policy      → static checks against rubric (no execution)
4. benchmark   → 5 configs: oracle + claude×{skills,no} + codex×{skills,no}
5. audit       → read trajectories: skill use, cheating, root cause of failures
6. report      → fill report-template.txt and bundle pr<N>.zip

Each step is described below. Run them in order — never skip benchmark to write a verdict, never skip audit to interpret results.

Step 1 — Fetch the PR

scripts/fetch_pr.sh <pr_number> <workspace>
# → echoes the task dir path; writes <workspace>/pr-<N>.meta.json with PR metadata.

Use gh API + raw download. Do not gh pr checkout or git pull — keep the local clone clean. For a local-path review, skip this step and pass the task directory directly to step 3.

Step 2 — Route to a track

A SkillsBench task belongs to one of three tracks. The track determines what "verifiable" means and which policy items apply. Always classify before running policy checks — applying the wrong rubric is the most common reason a review goes sideways.

Signal	→ Track
`task.md` frontmatter declares live network/API-key use for the agent or verifier	research-track
`verifier/test_outputs.py` imports a network client (`exa_py`, `requests`, `urllib`, `httpx`, `googleapiclient`) used during verification	research-track
Agent output is a non-text artifact (`.pdf`, `.mp3`, `.wav`, `.pptx`, `.docx`, `.mp4`, `.png`) and tests open / decode it	multimodal-track
Otherwise (deterministic tests over text/JSON/CSV from a frozen `environment/data/` bundle)	standard-track (default)

Read the full file on GitHub · 206 lines

Files

What ships with it

12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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 · 206 lines · 141 tokens per session scan B 0e0c6d1cd259

Subscribe to this mod's changes

task-review is a skill published in the GitHub repository benchflow-ai/skillsbench (1,867 stars, last pushed today), licensed Apache-2.0. It adds 141 tokens to every session and 4,444 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it B with 2 findings (reads agent configuration directories, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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skillsbench: Skill for Claude Code