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 RelationalAI/rai-agent-skills --skill dev-skills-reviewgit clone --depth 1 https://github.com/RelationalAI/rai-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/relationalai/rai-agent-skills/dev-skills-review)<a href="https://agentmods.dev/skills/relationalai/rai-agent-skills/dev-skills-review"><img src="https://agentmods.dev/badge/skills/relationalai/rai-agent-skills/dev-skills-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/relationalai/rai-agent-skills/dev-skills-review"><img src="https://agentmods.dev/badge/skills/relationalai/rai-agent-skills/dev-skills-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 | $0.00048 | $0.02004 |
| Opus 5.5 | $0.00019 | $0.00802 |
| Sonnet 5.5 | $0.00010 | $0.00401 |
| Haiku 4.5 | $0.00005 | $0.00200 |
Grade A, and why
dev-skills-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 2mo 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RAI Skills Review
Litmus Test: Agent Usability
The ultimate quality gate. Everything below serves this — if an agent can't discover, navigate, adapt, and execute from the skill alone, the skill isn't done.
- Discovery: Given a realistic user task, does the skill's
descriptioncause it to trigger (and not trigger for unrelated tasks)? - Navigation: Can an agent find the right section/example within the skill in 1-2 lookups (not wandering)?
- Pattern adaptation: Given a novel problem, can an agent locate a relevant example pattern and adapt it to a new domain without hallucinating API calls?
- Self-sufficiency: Can an agent go from skill content to working code without needing external docs, clarification, or guessing?
- Negative test: Does the skill clearly redirect the agent when the task is out of scope (via "When NOT to use" pointers)?
Structure
- YAML frontmatter with
nameanddescription(one line, imperative mood, trigger-ready, under 1024 characters) - Description answers two questions: (1) WHAT the skill covers, framed from user-intent angle not implementation mechanics; (2) WHEN Claude should invoke it, including cases where the user doesn't name the domain directly ("even if they don't mention X"). One sentence, both halves present.
-
SKILL.mdat root,references/for deep-dive,examples/if applicable -
## Summarywith What, When to use, When NOT to use, Overview -
## Quick Referencenear top — tables/code blocks, not prose -
## Common Pitfallstable (Mistake / Cause / Fix) captures counterintuitive, environment-specific facts the agent would get wrong without being told — not generic advice -
## Examplestable linking to example files -
## Reference fileswith "when to use" framing - Stability classification (
v1-STABLEorv1-SENSITIVE) below title
Content Quality
- SKILL.md body under 500 lines
- One term per concept throughout (no synonym alternation)
- Examples don't contradict any documented rule/pattern
- Reference files use same API style as SKILL.md
- Progressive disclosure: metadata (L1) -> instructions (L2) -> bundled resources (L3)
- References one level deep from SKILL.md (no deep nesting)
- Degrees of freedom match task fragility (narrow bridge = specific; open field = general)
- No explaining the obvious: omit what the agent already knows (general concepts, standard libraries, common protocols) — every token should earn its place
- Concise over exhaustive: stepwise guidance with a working example beats encyclopedic coverage — if content covers every edge case, check whether most are better left to agent judgment
- Defaults over menus: when multiple tools/approaches apply, one is the default with brief escape hatch — not equal-weight lists of options
- Short, generic parentheticals: keep inline "e.g." examples short and generic. Drop overly-specific example phrases unless they disambiguate a rule — when in doubt, cut them.
- Extracted content keeps an entry point: when content moves to a reference file (line-count, depth, or scope reasons), SKILL.md retains (a) an inline summary or canonical table for the extracted topic, (b) a specific load-trigger pointer naming what's in the reference file, AND (c) a Reference Files table row. The agent must still discover the topic from SKILL.md alone.
- Grounded, not generic: guidance reflects specific APIs, conventions, and failure modes — if a paragraph could apply to any project ("follow best practices", "handle errors appropriately"), cut or replace it with the project-specific rule it's standing in for
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.
- 2mo ago First seen · 108 lines · 48 tokens per session scan A bc56befa2e5d
dev-skills-review is a skill published in the GitHub repository RelationalAI/rai-agent-skills (4 stars, last pushed 2d ago), licensed Apache-2.0. It adds 48 tokens to every session and 2,004 once invoked, about $0.0002 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 2026-08-31.
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