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.
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.
npx skills add benchflow-ai/skillsbench --skill find-bugsgit clone --depth 1 https://github.com/benchflow-ai/skillsbenchWrote 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/skills/benchflow-ai/skillsbench/find-bugs)<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/find-bugs"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/find-bugs.svg" alt="Measured on agentmods" 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 | $0.00040 | $0.00630 |
| Opus 5 | $0.00020 | $0.00315 |
| Sonnet 5 | $0.00008 | $0.00126 |
| Haiku 4.5 | $0.00004 | $0.00063 |
Grade A, and why
find-bugs 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 3d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Find Bugs
Review changes on this branch for bugs, security vulnerabilities, and code quality issues.
Phase 1: Complete Input Gathering
- Get the FULL diff:
git diff master...HEAD - If output is truncated, read each changed file individually until you have seen every changed line
- List all files modified in this branch before proceeding
Phase 2: Attack Surface Mapping
For each changed file, identify and list:
- All user inputs (request params, headers, body, URL components)
- All database queries
- All authentication/authorization checks
- All session/state operations
- All external calls
- All cryptographic operations
Phase 3: Security Checklist (check EVERY item for EVERY file)
- Injection: SQL, command, template, header injection
- XSS: All outputs in templates properly escaped?
- Authentication: Auth checks on all protected operations?
- Authorization/IDOR: Access control verified, not just auth?
- CSRF: State-changing operations protected?
- Race conditions: TOCTOU in any read-then-write patterns?
- Session: Fixation, expiration, secure flags?
- Cryptography: Secure random, proper algorithms, no secrets in logs?
- Information disclosure: Error messages, logs, timing attacks?
- DoS: Unbounded operations, missing rate limits, resource exhaustion?
- Business logic: Edge cases, state machine violations, numeric overflow?
Phase 4: Verification
For each potential issue:
- Check if it's already handled elsewhere in the changed code
- Search for existing tests covering the scenario
- Read surrounding context to verify the issue is real
Phase 5: Pre-Conclusion Audit
Before finalizing, you MUST:
- List every file you reviewed and confirm you read it completely
- List every checklist item and note whether you found issues or confirmed it's clean
- List any areas you could NOT fully verify and why
- Only then provide your final findings
Output Format
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.
- 3d ago First seen · 76 lines · 40 tokens per session scan A edad456696ad
find-bugs is a skill published in the GitHub repository benchflow-ai/skillsbench (1,747 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 40 tokens to every session and 630 once invoked, about $0.0002 per session on Opus 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 2026-09-03.
Other skills, from other repositories
code-review
Paranoid architect review of code changes for bugs, security, missing tests, and undocumented assumptions. Works on local git diffs OR a GitHub pull request (e.g. owner/repo N). For PRs, can post findings as line-level review comments.
parallel-pr-review
Use when asked to "review the open PRs", review a batch or stack of pull requests, or run a recurring PR-review pass on a repo — especially with many PRs, stacked branches, conflicts, or security-sensitive changes. Covers grouping, fan-out to review subagents, verdict synthesis, and posting.
qa-review
QA review for code changes — test coverage analysis, edge case identification, test plan generation, regression detection, test health tracking over time.
review-readiness
PR readiness dashboard — tracks which reviews have been completed per branch and gates merge decisions. Shows code review, tests, security, QA, and linting status.
security-review
Security audit for code changes and PRs — OWASP top 10, auth flows, data handling, secrets exposure, supply chain risks. Writes findings as actionable items.
review-checklist
Pre-merge review checklist based on recurring AI reviewer feedback patterns.