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 SerhiiKorniienko/bullshit-detector --skill explaingit clone --depth 1 https://github.com/SerhiiKorniienko/bullshit-detectorWrote 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/serhiikorniienko/bullshit-detector/explain)<a href="https://agentmods.dev/skills/serhiikorniienko/bullshit-detector/explain"><img src="https://agentmods.dev/badge/skills/serhiikorniienko/bullshit-detector/explain/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/serhiikorniienko/bullshit-detector/explain"><img src="https://agentmods.dev/badge/skills/serhiikorniienko/bullshit-detector/explain.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 | $0.00080 | $0.00411 |
| Opus 5 | $0.00040 | $0.00205 |
| Sonnet 5 | $0.00016 | $0.00082 |
| Haiku 4.5 | $0.00008 | $0.00041 |
Grade A, and why
explain 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 12d 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.
What it actually says
explain
Make the content understandable without dumbing it down dishonestly.
Workflow
- Get the text (via
fetch-contentskill script if it's a URL, else web fetch or paste). - Pick the depth — from the user's request, or ask one short question if genuinely unclear:
- ELI5 — analogies, zero jargon, the core mechanism only
- Practitioner — assumes general technical literacy, focuses on how it works and what to do with it
- Deep dive — mechanisms, edge cases, history, competing views
- Explain, structured as:
- The one-sentence version first
- The mechanism: how it actually works, step by step
- Glossary: every jargon term the content uses without defining, one line each
- What the content assumes you know — the missing prerequisites that made it confusing
- Where the content's own explanation is wrong or oversimplified, if it is — flag it, don't repeat it
Rules
- Explaining ≠ endorsing. If the content's claim is contested, present the explanation and note the contest ("the video asserts X; the standard view is Y").
- Analogies must survive scrutiny — say where the analogy breaks.
- If the user points at a specific segment ("the part at 12:30", "section 3"), explain that segment in the context of the whole, not in isolation.
- Don't pad: a concept that takes three sentences gets three sentences.
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.
- 12d ago First seen · 30 lines · 80 tokens per session scan A 9426ce012d6c
explain is a skill published in the GitHub repository SerhiiKorniienko/bullshit-detector (142 stars, last pushed 8d ago), licensed MIT. It adds 80 tokens to every session and 411 once invoked, about $0.0004 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
ai-hallucination-fact-check-protocol
Design a fact-checking protocol for AI-generated text, extending SIFT with AI-specific adaptations for hallucination detection. Use when students need to verify AI claims and citations.
cred1
Look up domain credibility scores using the CRED-1 open dataset. Use when checking if a news source or website is reliable, flagged as misinformation, or has credibility concerns.
fact-check-social-media-posts
Verify claims in social media posts by checking evidence, evaluating source independence, and flagging rhetorical fallacies.
hr-onboarding
A new-hire onboarding plan as a single page — first week schedule, buddy + manager intro, learning track, equipment checklist, and "you're set when…" outcomes. Use when the brief mentions "onboarding", "new hire", "first week plan", or "入职".
book-mirror
Take any book (EPUB/PDF), produce a personalized chapter-by-chapter analysis. Each chapter is preserved in detail (The Chapter) and mirrored back to the reader's actual life (The Mirror) using brain context. The mirror observes and resonates — a friend pointing out parallels, NOT a consultant rearranging the reader's…
miniapp
Build a tiny interactive HTML playground only when someone asks to see, play with, or step through a mechanism.