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 AtlasOmnia/donna-starter --skill evidence-based-repliesgit clone --depth 1 https://github.com/AtlasOmnia/donna-starterWrote 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/atlasomnia/donna-starter/evidence-based-replies)<a href="https://agentmods.dev/skills/atlasomnia/donna-starter/evidence-based-replies"><img src="https://agentmods.dev/badge/skills/atlasomnia/donna-starter/evidence-based-replies/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/atlasomnia/donna-starter/evidence-based-replies"><img src="https://agentmods.dev/badge/skills/atlasomnia/donna-starter/evidence-based-replies.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 | $0.00043 | $0.00816 |
| Opus 5 | $0.00022 | $0.00408 |
| Sonnet 5 | $0.00009 | $0.00163 |
| Haiku 4.5 | $0.00004 | $0.00082 |
Grade A, and why
evidence-based-replies 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 9d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- evidence-based-replies — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evidence-Based Replies
Use this skill when the user wants to:
- compare someone's claim to a research paper, benchmark, article, or repo README
- draft a reply that corrects a misunderstanding of the evidence
- separate "the source supports X" from "the source does not support Y"
- turn a source-comparison into a Reddit/X/forum-ready response
Core principle
Do not stop at summarizing the source. The deliverable is usually the distinction:
- what the source actually establishes
- what stronger conclusion the other person is trying to import into it
- why that leap does not follow
If the user is asking for a reply, the misunderstanding of the evidence must be addressed explicitly, not left implicit.
Default workflow
- Read the conversation/claim carefully.
- Extract the specific proposition the other person is asserting from the source.
- Read the cited source.
- Split findings into:
- Supported by the source
- Not established by the source
- Reasonable but unproven extrapolations
- Compare the source type:
- empirical paper
- benchmark paper
- opinion/design README
- repo guidance / author doctrine
- Draft the response around the distinction, not around vague disagreement.
Required output shape
When explaining the comparison, prefer this structure:
- "The paper/source does show ..."
- "What it does not show is ..."
- "That is the step I disagree with."
- "So my criticism is not X; it is Y."
This pattern prevents straw-manning and keeps the correction precise.
Writing guidance for this user
the user prefers concise, practical responses. For forum replies:
- lead with the misunderstanding, not with throat-clearing
- avoid generic "both sides have a point" filler
- make the inferential gap explicit
- distinguish directionally true claims from overclaims
- prefer operational language over academic hedging
If he says a draft "needs to address the misunderstanding of the research," revise around the evidentiary gap immediately.
What ships with it
1 file 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.
- 9d ago First seen · 86 lines · 43 tokens per session scan A 81eebd0e3ff8
evidence-based-replies is a skill published in the GitHub repository AtlasOmnia/donna-starter (107 stars, last pushed 9d ago), licensed MIT. It adds 43 tokens to every session and 816 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 2026-08-30.
Other skills, from other repositories
npm-downloads-to-leads
Takes a list of npm package names (yours or competitors'), fetches 12 weeks of daily download data from the npm API, computes a breakout velocity score per package to identify hockey-stick growth, fetches maintainer profiles from the npm registry and GitHub API, and outputs a ranked lead brief for each breakout…
gh-issue-to-demand-signal
Takes a competitor's public GitHub repo URL, fetches their open issues via the GitHub REST API, filters noise locally, clusters issues into 6 demand categories, computes a demand score per issue and per cluster, and outputs a ranked demand gap report with a GTM messaging brief. Use when asked to scan a competitor's…
domain-expired-opportunity-finder
Evaluates expired domain candidates against a target niche, scores them by topical relevance, historical activity level, and history cleanliness, then outputs a ranked shortlist with explainable reasoning and risk flags.
company-radar
Competitive intelligence orchestrator tracking companies across 8+ platforms (GitHub, Twitter, Reddit, HN, PH, YC Jobs) with heat scores and AI briefings.
dependency-update-bot
Scans your project for outdated npm, pip, Cargo, Go, or Ruby packages. Runs a CVE security audit. Fetches changelogs, summarizes breaking changes with Gemini, and opens one PR per risk group (patch, minor, major). Includes Diagnosis Mode for install conflicts. Use when asked to update dependencies, check for outdated…
linkedin-job-post-to-buyer-pain-map
Takes pasted LinkedIn job posts or hiring descriptions and converts them into a structured buyer pain map with inferred pains, capability gaps, buy-vs-build signal, account priority scores, and suggested outreach angles. Use when asked to analyze hiring posts, decode job descriptions for buyer intent, build a pain map…