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 mindbox-cloud/agent-skills --skill skill-reviewgit clone --depth 1 https://github.com/mindbox-cloud/agent-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/mindbox-cloud/agent-skills/skill-review)<a href="https://agentmods.dev/skills/mindbox-cloud/agent-skills/skill-review"><img src="https://agentmods.dev/badge/skills/mindbox-cloud/agent-skills/skill-review.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 | $0.00141 | $0.04931 |
| Opus 5 | $0.00071 | $0.02465 |
| Sonnet 5 | $0.00028 | $0.00986 |
| Haiku 4.5 | $0.00014 | $0.00493 |
Grade A, and why
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 6d 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 — 363 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Review Novice — Autonomous Instruction for the Chat Agent
Purpose: You are an AI reviewer of Agent Skills for non-specialists. The user gives you an isolated skill folder (
SKILL.md+ optionalreferences/,scripts/,assets/). Your task is to run an autonomous Standard Review and produce a structured report with issues, overall statistics, recommendations, and an "Antipattern Bingo" section.Mode: Standard Review. Clear report without jargon. The set of sub-agents depends on the selected scope.
Preconditions
- Before Step 0, check
Task,TodoWrite, and file access for the skill. If anything is missing — stop and report what is lacking. - If the user selects logging ON in Step 0, verify file write capability. If write is unavailable — stop and suggest disabling logging.
CRITICAL — Mandatory Rules
- Questions to the user — only in Step 0. Mandatory question: context of use + logging. Ask for log path confirmation only if the user enabled logging.
- A TODO plan is MANDATORY from the very start of the review.
- The TODO plan must cover the full review scope. For every 3–4 check items there should be a separate TODO item. Do not create one giant TODO for the entire review.
- Update statuses as the review progresses:
pending→in_progress→completed. - If the folder is not a valid skill directory (no
SKILL.md) or contains more than one skill — see## Troubleshooting, problem 1. Do not abort the check silently. - On read problems, coverage gaps, or sub-agent failure — capture limitations and perform a residual review. On write problems with
logs=on— notify the user and stop the review. - In sub-agent mode (
>= 500lines), the orchestrator must delegate checklist checks to sub-agents viaTask. Running a full review in the main context instead of launching sub-agents is a workflow violation. Self-performed checklist analysis by the orchestrator is only acceptable as a local fallback after a specific sub-agent fails. - Review goal: understand whether the skill works in the context being reviewed (for the author, for a colleague, in a repository).
- Novice does not compute a maturity stage. Scope is determined by the user's choice. The report shows findings by stage, overall statistics, and recommendations — without a "this is stage N" label.
- Language: conduct the entire review (report, logs, TODO, sub-agent briefs) in the language the user started the conversation in.
- Report tone: language must be understandable to a product owner or manager. Avoid technical checklist jargon. In PASS and N/A sections — list checks without IDs, only human-readable descriptions. In FAIL and WARNING sections — IDs are acceptable for traceability, but must be accompanied by a plain-language description.
What ships with it
10 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.
- references/antipattern-bingo.md 6.0 KB
- references/checklist-lifecycle.md 2.6 KB
- references/checklist-links.md 2.6 KB
- references/checklist-references.md 6.2 KB
- references/checklist-structure.md 5.8 KB
- references/checklist-workflow.md 14 KB
- references/instruction-singlepass.md 33 KB
- references/maturity-diagnostic.md 1.7 KB
- references/report-template.md 6.1 KB
- references/subagent-base-rules.md 2.4 KB
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.
- 6d ago First seen · 363 lines · 141 tokens per session scan A 3de9292cf76a
skill-review is a skill published in the GitHub repository mindbox-cloud/agent-skills (3 stars, last pushed 3mo ago), licensed MIT. It adds 141 tokens to every session and 4,931 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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interview-me
Interview the user one question at a time to resolve ambiguities before or during implementation. Use whenever the user says "interview me", "ask me questions", "make sure you understand", or before starting any task where multiple ambiguous decisions would otherwise be guessed silently. Also invocable as…