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 nimadorostkar/Claude-Skills-collection --skill fact-checkinggit clone --depth 1 https://github.com/nimadorostkar/Claude-Skills-collectionWrote 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/nimadorostkar/claude-skills-collection/fact-checking)<a href="https://agentmods.dev/skills/nimadorostkar/claude-skills-collection/fact-checking"><img src="https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/fact-checking/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/nimadorostkar/claude-skills-collection/fact-checking"><img src="https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/fact-checking.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 | $0.00038 | $0.01300 |
| Opus 5 | $0.00019 | $0.00650 |
| Sonnet 5 | $0.00008 | $0.00260 |
| Haiku 4.5 | $0.00004 | $0.00130 |
Grade A, and why
fact-checking 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.
How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fact-Checking
Purpose
Verify a claim by tracing it to its origin. Most false claims in circulation are not fabrications; they are real findings that have been stripped of their qualifications, or numbers that have acquired a citation through repetition.
When to Use
- Verifying a statistic or a claim before publishing it.
- A number that is widely repeated and never sourced.
- Checking an assertion in a document, an article, or a report.
- Evaluating a claim that seems too clean.
Capabilities
- Tracing a claim to its primary source.
- Detecting circular citation.
- Evaluating study quality and its actual conclusion.
- Identifying the qualifications that were dropped.
- Reporting a verdict with evidence.
Inputs
- The claim, quoted exactly.
- Where it appeared and what it was used to support.
Outputs
- A verdict: supported, unsupported, misleading, or unverifiable.
- The chain of citation, traced.
- What the original source actually says.
Workflow
- Quote the claim exactly — Vague paraphrases are unfalsifiable. "Most projects fail" cannot be checked; "70% of software projects fail" can.
- Follow the citation chain — Each source cites another. Follow it until you reach a primary source, or until it loops, or until it disappears. All three outcomes are informative.
- Read what the original actually says — Very frequently, the original is a limited finding about a specific population that has been generalized into a universal claim by the time it reaches you.
- Check for independence — Twelve sources citing one study is one study.
- Check the qualifications that were dropped — "In a survey of 43 startups in one accelerator cohort" becomes "70% of startups" within three citations.
- Report the chain, not just the verdict — The chain is the evidence.
Best Practices
- A claim with no traceable origin is not established, however widely it is repeated. Repetition is not evidence.
- Numbers that are suspiciously round (90%, 70%, 50%) are frequently rhetorical rather than measured. Check them.
- The most common falsification is not fabrication but the dropping of qualifications: a finding about a specific population, under specific conditions, becomes a universal law.
- Check the date. A statistic that was true in 2011 may have no relationship to the present, and it will still be quoted.
- Check who funded the study, and what they wanted it to show. This does not invalidate it, but it determines how much scrutiny it warrants.
- "Unverifiable" is a legitimate verdict, and a useful one. It is not the same as "false".
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 · 128 lines · 38 tokens per session scan A e1771472395a
fact-checking is a skill published in the GitHub repository nimadorostkar/Claude-Skills-collection (26 stars, last pushed 25d ago), licensed MIT. It adds 38 tokens to every session and 1,300 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 2026-09-03.
Other skills, from other repositories
offensive-crypto-attacks
Systematic methodology for identifying and exploiting cryptographic implementation weaknesses in real-world applications. Covers padding oracle attacks against CBC-mode ciphers with PKCS7 padding (Vaudenay's original attack through modern padbuster automation), ECB mode exploitation including block cut-and-paste and…
offensive-c2-frameworks
Command and Control framework deployment, configuration, and operational tradecraft for red team engagements. Covers Cobalt Strike (malleable C2 profiles, Beacon types HTTP/HTTPS/DNS/SMB, Beacon Object Files for in-memory execution, sleep and jitter tuning, named pipe pivoting), Sliver (implant generation across…
offensive-parameter-pollution
HTTP parameter pollution (HPP) checklist: duplicate parameter injection, backend vs frontend parsing differences, WAF bypass via HPP, server-side vs client-side HPP, and practical exploitation patterns. Use when testing web applications for parameter handling flaws.
offensive-wifi
Wireless / 802.11 attack methodology for red team engagements and wireless security assessments. Covers monitor-mode setup, WPA/WPA2-PSK handshake capture and PMKID attacks, WPA3 SAE downgrade and Dragonblood, WPA-Enterprise (EAP) attacks (MSCHAPv2 cracking, EAP-TLS cert theft, evil-twin RADIUS), Karma / Known Beacons…
offensive-z-wave
Z-Wave attack methodology — sniffing with Z-Force / EZ-Wave / RTL-SDR + ZniffMobile, S0 (legacy) network-key derivation flaw and key reuse, S2 (modern) ECDH commissioning analysis, replay/injection on unauthenticated nodes, default-key brute-force on test deployments, and home-automation hub pivots. Use when targeting…
seo
Optimize for search engine visibility and ranking. Use when asked to "improve SEO", "optimize for search", "fix meta tags", "add structured data", "sitemap optimization", or "search engine optimization".