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 psylch/better-skills --skill better-skill-reviewgit clone --depth 1 https://github.com/psylch/better-skillsWrote 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/psylch/better-skills/better-skill-review)<a href="https://agentmods.dev/skills/psylch/better-skills/better-skill-review"><img src="https://agentmods.dev/badge/skills/psylch/better-skills/better-skill-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/skills/psylch/better-skills/better-skill-review"><img src="https://agentmods.dev/badge/skills/psylch/better-skills/better-skill-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 | $0.00133 | $0.01643 |
| Opus 5 | $0.00067 | $0.00822 |
| Sonnet 5 | $0.00027 | $0.00329 |
| Haiku 4.5 | $0.00013 | $0.00164 |
Grade A, and why
better-skill-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 12d 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Review
Language
Match user's language: Respond in the same language the user uses.
Overview
Review an agent skill through three layers: automated linting (hard rules), contextual finding evaluation (agent judges with context), and structured semantic review (deep analysis against best practices). Optionally fix issues and verify fixes through independent subagent validation.
Workflow
Progress:
- Step 1: Identify the skill
- Step 2: Review (linting + profile + findings + semantic)
- Step 3: Present findings
- Step 4: Fix gate
- Step 5: Verify & iterate
Step 1: Identify the Skill
Accept the skill location as a directory path containing SKILL.md. Auto-detect if the current working directory contains one.
Step 2: Review
Run both tools, then evaluate.
2a. Automated linting:
python3 {SKILL_DIR}/scripts/validate.py run --path <skill-path>
Output: checks (hard-rule verdicts → linter grade) + findings (soft detections needing judgment).
2b. Profile extraction:
bash {SKILL_DIR}/scripts/analyze.sh analyze <skill-path>
Note skill level (l0/l0plus/l1) and feature flags.
2c. Contextual findings review:
Judge each finding using its context_hint. See references/semantic_dimensions.md § Finding Judgment Table for decision criteria. Promote real issues to warnings; dismiss the rest with a brief note.
2d. Semantic review:
Read the skill's SKILL.md fully, then score each dimension (0-3). Read references/semantic_dimensions.md for the full checklist per dimension:
| Dimension | What it evaluates |
|---|---|
| 5.1 Description Quality | Trigger phrases, length, voice, specificity |
| 5.2 Workflow Design | Steps, decision points, SKILL.md length |
| 5.3 Runtime Robustness | Preflight, degradation, troubleshooting (L0+/L1 only) |
| 5.4 Script Quality | JSON output, error handling, exit codes (scripts only) |
| 5.5 UX Practices | Language, checklist, completion report (applicability matrix) |
| 5.6 Setup Flow Integrity | Bootstrap safety, live validation, credential security |
What ships with it
6 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.
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.
- 12d ago First seen · 173 lines · 133 tokens per session scan A ec52f70e99f1
better-skill-review is a skill published in the GitHub repository psylch/better-skills (5 stars, last pushed 6mo ago), licensed MIT. It adds 133 tokens to every session and 1,643 once invoked, about $0.0007 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 2026-08-31.
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