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 agentsope/SkillAlchemy --skill agentsop-bio-fraud-forensicsgit clone --depth 1 https://github.com/agentsope/SkillAlchemyWrote 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/agentsope/skillalchemy/agentsop-bio-fraud-forensics)<a href="https://agentmods.dev/skills/agentsope/skillalchemy/agentsop-bio-fraud-forensics"><img src="https://agentmods.dev/badge/skills/agentsope/skillalchemy/agentsop-bio-fraud-forensics/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/agentsope/skillalchemy/agentsop-bio-fraud-forensics"><img src="https://agentmods.dev/badge/skills/agentsope/skillalchemy/agentsop-bio-fraud-forensics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 120 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00167 | $0.02990 |
| Opus 5.5 | $0.00067 | $0.01196 |
| Sonnet 5.5 | $0.00033 | $0.00598 |
| Haiku 4.5 | $0.00017 | $0.00299 |
Grade A, and why
agentsop-bio-fraud-forensics 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 1mo 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bio-Fraud Forensics · 生物医学论文数据造假筛查
A screening methodology for life-science papers. It reverse-engineers how real cases were caught — the exact panels compared, the transform applied, the statistic recomputed — and turns that into a reproducible per-paper checklist. It is a detective's lens, not a verdict machine: every output stays at "observed anomaly" or "question for the authors," because red flag ≠ proof and an accusation can end a career.
Activation Rules
Trigger when:
- "Check this paper / figure / Western blot for manipulation," "does this data look faked," "screen for image duplication."
- A user shares a figure, blot, microscopy panel, supplementary
.xlsx, or a DOI and asks if it's trustworthy. - "Is this a paper mill?", "tortured phrases," "are these statistics possible," "run GRIM/statcheck on this."
- "Where do I check if this paper has been flagged / retracted?" (verification routing).
- Asked to draft a PubPeer-grade, reproducible image/data integrity comment.
Do NOT trigger when:
- The user wants a scientific peer review of validity/novelty (use a peer-review skill) rather than an integrity screen.
- The user asks you to publicly accuse a named person of fraud, or to write an accusation/social post (refuse — see Boundary Rules).
- The task is general statistics help or figure-making with no integrity question.
- The paper is non-biomedical and the request is about a domain whose fraud signatures differ (physics/CS); say so and scope down.
Agentic Protocol
Run this as a chain-of-steps. Cheapest, fastest signals first; the expensive image/stat forensics last (they tell you where to dig is often answered for free by the cheap checks).
Step 1 — Scope & status. Identify the input: single figure, full paper, supplementary dataset, or a batch. Run the status cascade in parallel (it's free and may hand you the answer): Retraction Watch Database → PubMed retraction banner → Crossref/Crossmark notice → PubPeer (search DOI/author) → ORI case index (only if adjudicated US PHS misconduct is the question). Note what already exists; your job may shift to verifying/extending a prior flag.
What ships with it
12 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.
- examples/demo_screening.md 4.2 KB
- README.md 2.9 KB
- references/R01-misconduct-taxonomy.md 20 KB
- references/R02-image-forensics.md 19 KB
- references/R03-statistical-forensics.md 19 KB
- references/R04-exposure-sites-method.md 21 KB
- references/R05-evidence-red-lines.md 21 KB
- references/R06-screening-workflow.md 22 KB
- references/R07-paper-mill-signals.md 20 KB
- references/research_notes.md 7.9 KB
- references/sop_models.md 17 KB
- USAGE.md 8.3 KB
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.
- 1mo ago First seen · 137 lines · 167 tokens per session scan A 299d4d5bb4eb
agentsop-bio-fraud-forensics is a skill published in the GitHub repository agentsope/SkillAlchemy (429 stars, last pushed 7d ago), licensed MIT. It adds 167 tokens to every session and 2,990 once invoked, about $0.0007 per session on Opus 5.5. 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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