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 rampstackco/claude-skills --skill evidence-based-reviewsgit clone --depth 1 https://github.com/rampstackco/claude-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/rampstackco/claude-skills/evidence-based-reviews)<a href="https://agentmods.dev/skills/rampstackco/claude-skills/evidence-based-reviews"><img src="https://agentmods.dev/badge/skills/rampstackco/claude-skills/evidence-based-reviews/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/rampstackco/claude-skills/evidence-based-reviews"><img src="https://agentmods.dev/badge/skills/rampstackco/claude-skills/evidence-based-reviews.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00168 | $0.02482 |
| Opus 5 | $0.00084 | $0.01241 |
| Sonnet 5 | $0.00034 | $0.00496 |
| Haiku 4.5 | $0.00017 | $0.00248 |
Grade A, and why
evidence-based-reviews 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 11d 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 — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evidence-Based Reviews
Produce product reviews and buying guides whose claims match their evidence. The method is evidence synthesis with a disclosed basis, and one rule anchors everything: never claim hands-on time that did not happen.
Most review sites fail this rule quietly. "We tested" appears above content assembled from spec sheets, and readers have learned to smell it. The honest alternative is stronger, not weaker: synthesis of owner experience at scale, verified specifications, and triangulated expert sources is demonstrable original analysis, and disclosing it builds the trust that fabricated testing destroys.
When to use
- Writing product reviews or buying guides when hands-on access is partial or absent
- Setting up the review methodology for a new review or affiliate site
- Adding evidence disclosure to existing review content
- Auditing review content for claims its evidence cannot support
- Deciding whether Review or Product schema is honest for a given piece
- Aligning review content with Google's reviews system and FTC disclosure expectations
When NOT to use
- General content writing and editing (use
content-and-copy; this skill governs the evidence and claims layer of review content specifically) - Defining how the brand sounds (use
brand-voice) - Optimizing the review page itself for search (use
seo-onpage) - Per-piece editorial briefs (use
content-brief-authoring) - Instructional how-to content that teaches a procedure or concept to a first-time reader, such as a tutorial or an explainer: a teaching piece of this kind is owned by its writing, its structure, and its search craft, with the evidence discipline riding alongside as a constraint on its claims, so this skill is one input among several rather than the single choice for it
If genuine hands-on testing at scale exists, with instrumentation and protocols, this skill still applies: the tiers do not change, the methodology block simply states tier 4 and the testing protocol becomes the disclosed basis.
What ships with it
2 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.
- 11d ago First seen · 168 lines · 168 tokens per session scan A d827133c0797
evidence-based-reviews is a skill published in the GitHub repository rampstackco/claude-skills (838 stars, last pushed 3d ago), licensed MIT. It adds 168 tokens to every session and 2,482 once invoked, about $0.0008 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 2026-08-30.
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