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 yogsoth-ai/de-anthropocentric-research-engine --skill atomize-claimgit clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engineWrote 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/yogsoth-ai/de-anthropocentric-research-engine/atomize-claim)<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/atomize-claim"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/atomize-claim/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/yogsoth-ai/de-anthropocentric-research-engine/atomize-claim"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/atomize-claim.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00025 | $0.00248 |
| Opus 5.5 | $0.00010 | $0.00099 |
| Sonnet 5.5 | $0.00005 | $0.00050 |
| Haiku 4.5 | $0.00003 | $0.00025 |
Grade A, and why
atomize-claim 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.
What it actually says
atomize-claim
Purpose
Split a compound claim into atomic propositions that can receive separate evidence and confidence judgments.
Input contract
required: [compound_claim]
optional: [argument_context, domain_terms, evidence_records]
constraints: [atomic claims retain logical connectors and scope qualifiers]
Procedure
- Identify subjects, predicates, qualifiers, conditions, and logical connectors.
- Split independent propositions while preserving dependency and quantifier scope.
- Mark implicit premises and ambiguous terms.
- Emit an ordered atomic claim set with recomposition rules.
Output contract
produces: [atomic_claims, logical_connectors, implicit_premises, recomposition_map]
delta_fields: [findings, uncertainties, open_questions]
Quality gates
- Recombining the atoms preserves the original meaning.
- Each atom is independently evidence-addressable.
Failure and counterexamples
Do not split a definition or condition from the proposition it qualifies.
Provenance map
resolved: atomize-claim
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 · 47 lines · 25 tokens per session scan A 9b55da1cd7a2
atomize-claim is a skill published in the GitHub repository yogsoth-ai/de-anthropocentric-research-engine (505 stars, last pushed 4d ago), licensed Apache-2.0. It adds 25 tokens to every session and 248 once invoked, about $0.0001 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 2026-09-24.
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