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 agentmods add skills/duthaho/skillhub/factchecknpx skills add duthaho/skillhub --skill factcheckgit clone --depth 1 https://github.com/duthaho/skillhubWrote 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/duthaho/skillhub/factcheck)<a href="https://agentmods.dev/skills/duthaho/skillhub/factcheck"><img src="https://agentmods.dev/badge/skills/duthaho/skillhub/factcheck.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 | $0.00213 | $0.01662 |
| Opus 5 | $0.00106 | $0.00831 |
| Sonnet 5 | $0.00043 | $0.00332 |
| Haiku 4.5 | $0.00021 | $0.00166 |
Grade A, and why
factcheck 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 5d 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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
factcheck — do the sources say that?
/factcheck <path | URL> — audit a document's claims against its sources
/factcheck <path> focus <section/topic> — audit only part of a long document
Answer one question: for each claim this document makes, is there a source that actually asserts it? The documented failure mode of cited writing — human and agent alike — is not missing links; it's links that resolve to pages that don't say that. A working URL is the weakest form of evidence there is. This audit replaces "it has citations" with "here is the passage."
Step 0 — Scope the audit
Read the document (WebFetch if a URL; ask for a paste if it's paywalled). Then size the job and say which tier you picked:
- Small (≤ ~10 checkable claims): verify inline, no sub-agents — the fan-out below would cost more than it saves.
- Standard: fan out, batching ~5–8 claims per verifier.
- Focused: the user named a section or topic → extract only there, note in the audit header that the rest was not examined.
If the document has no citations at all, say so up front — the audit's question shifts from "does the cited source say this" to "does support for this exist anywhere", and UNSUPPORTED becomes the default grade to beat.
Step 1 — Extract the checkable claims
Walk the document and number every checkable claim: factual, specific, and in principle verifiable — statistics, quotes, "X said/announced Y", version numbers, benchmark results, historical facts, "studies show".
For each claim record: a short restatement, its locator (section heading or line), the cited source if any, and whether it's date-sensitive (anything with "currently", "latest", a version, or a number that drifts).
Skip pure opinion and analysis — but flag opinion dressed as fact ("it is widely known that...") as a finding in its own right, ungraded.
Step 2 — Adversarial verification (fan out)
Spawn verifier sub-agents (subagent_type: "Explore"), each with a batch
of claims and the same standing instruction: try to refute each claim,
not confirm it — a verifier hunting for agreement finds it whether it
exists or not. Per claim:
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.
- 5d ago First seen · 144 lines · 213 tokens per session scan A 518000eeb594
factcheck is a skill published in the GitHub repository duthaho/skillhub (9 stars, last pushed 12d ago), licensed MIT. It adds 213 tokens to every session and 1,662 once invoked, about $0.0011 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.
Other skills, from other repositories
session-deep-dive
Deep qualitative analysis of high-signal sessions. Spawns subagents with v2 template, synthesizes patterns, compares against known findings. Use after /session-scan.
brainstorm
Brainstorm Elixir/Phoenix features — explore ideas, compare approaches, gather requirements. Use when vague idea, not sure how to approach, or want to discuss before plan.
tidewave-integration
Tidewave MCP runtime tools — debugging, smoke testing, live state inspection, SQL queries, hex docs. Use when evaluating code in a running Phoenix app.
plugin-dev-workflow
Guide plugin development workflow — editing skills, agents, hooks, or eval framework in this repo. Use when modifying files in plugins/elixir-phoenix/, lab/eval/, or lab/autoresearch/. Ensures changes pass eval, lint, and tests before committing.
security
Enforce Elixir/Phoenix security — auth, OAuth, sessions, CSRF, XSS, SQL injection, input validation, secrets. Use when editing auth files, login flows, RBAC, or API keys.
techdebt
Analyze Elixir/Phoenix technical debt — duplicates, refactoring opportunities, credo issues. Use when asked about code quality, cleanup, or what to improve.