claim-writing

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Blind-rewrite a citing sentence (citance) from another paper into a single atomic, independently-verifiable claim (SciFact's annotation protocol) — never looking at the cited paper's content while rewriting. Use this when you have a specific citing sentence and want it decomposed into checkable atomic claims, as the first step before rationale-selection and claim-label-prediction.

AI & Automation 392 stars 34 forks Updated 1 weeks ago Apache-2.0

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Skill Content

# Claim Writing Blind rewrite of a citance into an atomic verifiable claim — first step of the SciFact 3-chain. ## Execution Subagent — spawned via spawn-agent skill. ## Input Requirement This Package Cannot Auto-Supply SciFact's own method requires a citance — a sentence FROM ANOTHER PAPER that cites the paper under study. `paper-fetch` only ever retrieves the text of the single paper being read; it has no mechanism to discover or supply a citance about that paper. Callers using this SOP must supply `citance` themselves (e.g. from a specific citation-verification task they already have in hand) — this SOP cannot be exercised end-to-end starting only from a `paper_ref`, unlike every other SOP in this package. Do not "fix" this by having paper-fetch search for citing sentences; that would break paper-fetch's decoupled, single-purpose design (spec §9). <!-- BEGIN available-tables (generated) --> ## Available SOPs | SOP | When to use | | --- | --- | | spawn-agent | Spawn a customized CC subagent with full MCP tool access. | <!-- END available-tables (generated) -->

Details

Author
yogsoth-ai
Repository
yogsoth-ai/de-anthropocentric-research-engine
Created
6 months ago
Last Updated
1 weeks ago
Language
HTML
License
Apache-2.0

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claim-writing

Blind-rewrite a citing sentence (citance) from another paper into a single atomic, independently-verifiable claim (SciFact's annotation protocol) — never looking at the cited paper's content while rewriting. Use this when you have a specific citing sentence and want it decomposed into checkable atomic claims, as the first step before rationale-selection and claim-label-prediction.

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