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 magnus919/agent-skills --skill de-spingit clone --depth 1 https://github.com/magnus919/agent-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/magnus919/agent-skills/de-spin)<a href="https://agentmods.dev/skills/magnus919/agent-skills/de-spin"><img src="https://agentmods.dev/badge/skills/magnus919/agent-skills/de-spin/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/magnus919/agent-skills/de-spin"><img src="https://agentmods.dev/badge/skills/magnus919/agent-skills/de-spin.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 | $0.00092 | $0.02248 |
| Opus 5 | $0.00046 | $0.01124 |
| Sonnet 5 | $0.00018 | $0.00450 |
| Haiku 4.5 | $0.00009 | $0.00225 |
Grade A, and why
de-spin 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 10d 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
De-Spin
Use this skill to determine whether a persuasive message earns its conclusion. The goal is calibrated judgment, not reflexive distrust: distinguish supported, false, misleading, complicated, and unknown without turning missing evidence into proof of deception.
Non-negotiable rules
- Judge claims and evidence, not the speaker’s body language, confidence, political identity, or presumed motive.
- A literally true sentence may still be misleading when its likely implication, baseline, conditions, or typical outcome is withheld.
- Do not call a claim false unless credible evidence directly contradicts it. Use unsupported or unknown when evidence is absent or inaccessible.
- Treat repetition, reposts, and a network of affiliated outlets as one evidence stream until independent origins are established.
- Match verification effort to stakes. Slow down before health, financial, legal, security, reputational, or irreversible decisions.
Workflow
1. Define the decision and claim boundary
State what decision the message is trying to move: belief, purchase, share, vote, authorization, or action. Extract each checkable claim separately. Do not audit a paragraph as one unit when it contains several factual assertions.
Classify each claim:
- Factual: observable or measurable now or historically.
- Predictive: about a future outcome; evaluate assumptions and base rates.
- Causal: says X caused Y; requires more than correlation or anecdote.
- Normative: value judgment; clarify values rather than pretending it is a fact.
- Identity or motive: usually cannot be resolved from the message alone; do not speculate.
2. Make the implied claim explicit
For each factual, predictive, or causal claim, write five fields:
| Field | Question |
|---|---|
| Literal claim | What exactly was said? |
| Likely implication | What would a reasonable person infer? |
| Missing context | Which denominator, baseline, timeframe, eligibility rule, or counterexample could change that impression? |
| Required evidence | What source, data, method, or record would make this checkable? |
| Disconfirming evidence | What would show the claim is wrong or materially incomplete? |
What ships with it
5 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.
- 10d ago First seen · 142 lines · 92 tokens per session scan A f209d2cbf869
de-spin is a skill published in the GitHub repository magnus919/agent-skills (76 stars, last pushed today), licensed MIT. It adds 92 tokens to every session and 2,248 once invoked, about $0.0005 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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