Borrowing it
Nothing to install: this file belongs to monarch-initiative/dismech. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/monarch-initiative/dismech/main/.claude/skills/dismech-references/SKILL.mdgit clone --depth 1 https://github.com/monarch-initiative/dismechWrote 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/monarch-initiative/dismech/dismech-references)<a href="https://agentmods.dev/skills/monarch-initiative/dismech/dismech-references"><img src="https://agentmods.dev/badge/skills/monarch-initiative/dismech/dismech-references/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/monarch-initiative/dismech/dismech-references"><img src="https://agentmods.dev/badge/skills/monarch-initiative/dismech/dismech-references.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 | $0.00088 | $0.03047 |
| Opus 5 | $0.00044 | $0.01523 |
| Sonnet 5 | $0.00018 | $0.00609 |
| Haiku 4.5 | $0.00009 | $0.00305 |
Grade A, and why
dismech-references 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 — 314 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Curate Evidence and References
Use this workflow whenever evidence or its cited source changes.
Non-negotiable rules
- Quote an exact substring of the cited source. Do not paraphrase or fabricate a
snippet. - Confirm that the quote substantively supports the precise claim. A matching string from the wrong paper, or an unrelated sentence from the right paper, is not evidence.
- Prefer a result sentence from the abstract or authoritative source record. A paper title usually establishes only that a topic was studied.
- Never create or hand-edit
references_cache/*.md. Generate or regenerate a cache entry withjust fetch-reference <ID>. - Never use fuzzy auto-repair to rewrite snippets. Read the source and copy the exact passage, choose another source, or remove the evidence.
- Treat deep-research output as leads, not ground truth.
Evidence shape
evidence:
- reference: PMID:12345678
supports: SUPPORT
evidence_source: HUMAN_CLINICAL
snippet: "Exact text copied from the cited source."
explanation: "How this passage supports the specific KB claim."
Use supports: SUPPORT, REFUTE, or the value allowed by the schema. Make the
explanation connect the quote to the claim without adding conclusions the
quote does not establish.
Classify evidence_source by the cited study, not by the curator or the claim:
HUMAN_CLINICAL: patients, cohorts, clinical observations, or trialsMODEL_ORGANISM: in vivo non-human animal or organism workIN_VITRO: cells, organoids, explants, or biochemical assaysCOMPUTATIONAL: modeling, simulation, or in-silico analysisOTHER: evidence that does not fit the categories above
Inspect the schema and nearby current entries if a field or enum is uncertain.
Workflow
1. Screen deep-research sources
If evidence came from research/, first read the report's
reference_validation, unresolved_references, needs_review, and
off_topic_references results. Do not curate an unresolved identifier. An
off-topic flag is a reason to inspect the paper, not an automatic rejection.
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 Changed · +68 lines f6316b86b041
- 9d ago First seen · 246 lines · 88 tokens per session scan A 9d7bb927e645
dismech-references is a skill published in the GitHub repository monarch-initiative/dismech (59 stars, last pushed today), licensed BSD-3-Clause. It adds 88 tokens to every session and 3,047 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.
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