# Read Claim > Deep extraction of all verifiable claims from a research paper. Actively proposes implicit claims, splits compound statements, and flags cross-reference inconsistencies. - Skill: `qinghonglin/read-claim` (Agent Skill) - Install (CLI): `npx skillmds@latest add qinghonglin/read-claim` - Raw SKILL.md: https://api.skillmd.com/api/skills/qinghonglin/read-claim/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Research & Search - License: MIT - Author: QinghongLin (https://skillmd.com/u/qinghonglin) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/qinghonglin/read-claim --- # Extract Claims Extract all claims the authors make about their own work — both explicit and implicit. Actively look for hidden claims, split compound statements, and check cross-reference consistency. ## Workflow ``` - [ ] Step 1: Read full paper text - [ ] Step 2: Extract explicit claims - [ ] Step 3: Extract implicit claims - [ ] Step 4: Split compound claims - [ ] Step 5: Cross-reference check - [ ] Step 6: Save report ``` ## Step 1: Read Full Paper Text ``` Read {paper_dir}/metadata/{arxiv_id}/mathpix/{arxiv_id}.md ``` **Read the entire document — do not split by section.** ## Step 2: Extract Explicit Claims A **claim** is any assertion the authors make about their own work that could in principle be validated. **Not a claim**: - Background statements ("Transformers have achieved success in NLP") - Descriptions of other work ("As shown in [10], ...") - Definitions ("We define ego-video as first-person footage") - Writing quality issues (grammar, typos) — these belong in `read-txt`, not here Each claim: ```json { "id": 1, "source": "abstract", "quote": "exact sentence or phrase from the paper", "claim": "concise restatement of what is being asserted", "evidence_type": ["experiment"] } ``` **`source`**: section where the claim appears (`abstract`, `introduction`, `method`, `experiments`, `conclusion`, `appendix`) **`quote`**: exact original text — do not paraphrase **`claim`**: clean one-sentence restatement of the assertion **`evidence_type`** *(array — a claim may belong to multiple types)*: | Value | Meaning | |-------|---------| | `experiment` | Should be validated by the paper's own experiments | | `related_work` | Involves another paper — cited fact, baseline comparison, or novelty claim | | `theoretical` | Supported by mathematical derivation or proof | | `code` | Verifiable by inspecting the released code | Every claim MUST map to at least one type. If unsure, apply this priority: - Can it be checked by reading code/configs? → `code` - Can it be checked against tables/figures? → `experiment` - Is it a "should have done but didn't" ablation? → `experiment` - Can it be checked against published literature? → `related_work` - Is it a formal argument or derivation? → `theoretical` **Hints for `related_work`**: assign when the claim cites or characterizes another paper, compares against a baseline, or asserts novelty ("first to", "pioneering"). Often combined with `experiment` when backed by the paper's own tables. ## Step 3: Extract Implicit Claims Actively look for assertions that are **implied but not directly stated**: ### Numeric implications - If abstract says "75.1% accuracy" and Table 2 also shows 75.1%, this implies "abstract matches Table 2" — extract as an `experiment` claim - If a figure caption says "our method converges faster", extract the convergence claim ### Scope overclaims - "effective" without qualifier → implies works in all settings - "state-of-the-art" → implies tested against all relevant baselines - "lightweight" → implies compared in model size / FLOPs - "scalable" → implies tested at multiple scales - Note what would be needed to fully support the claim in `implicit_reason` ### Method-result gaps - Method section describes a component, but experiments don't ablate it → extract as: "Component X contributes to performance" (implicit, untested) - A loss term is described but no ablation shows its effect → extract ### Comparative implications - "outperforms X" → implies same evaluation protocol as X - "with only 256K data" → implies others use more data (extract the comparison) - "zero-shot" → implies no task-specific fine-tuning (verify definition matches standard usage) ```json { "id": 33, "source": "experiments", "quote": "ShowUI achieves state-of-the-art grounding performance", "claim": "ShowUI outperforms all published methods on Screenspot grounding at time of submission", "evidence_type": ["experiment", "related_work"], "implicit_reason": "SOTA claim implies comparison against all relevant published baselines, but paper only compares against 5 methods" } ``` ## Step 4: Split Compound Claims A single sentence often packs multiple independently verifiable assertions. **Always split** by the smallest verifiable unit: - "We achieve 75.1% on ScreenSpot, 70.0% on AITW, and competitive results on Mind2Web" → **3 claims** - "Our method is lightweight (2B) and uses less data (256K)" → **2 claims** (model size, data size) - "Token selection reduces tokens by 33% and speeds up training by 1.4x" → **2 claims** (reduction rate, speedup) Each sub-claim gets its own `id` and may have different `evidence_type`. ## Step 5: Cross-Reference Check Scan for **internal consistency** issues between sections: - Abstract numbers vs. table numbers — do they match exactly? - Method description vs. code/config (if mentioned) — any discrepancy? - Figures/tables referenced in text — do the cited values match what's shown? - Contribution list in intro vs. what experiments actually validate Extract these as claims with `evidence_type: ["experiment"]`: ```json { "id": 45, "source": "abstract vs experiments", "quote": "75.1% accuracy in zero-shot screenshot grounding", "claim": "Abstract accuracy 75.1% matches Table 2 ShowUI row average", "evidence_type": ["experiment"] } ``` ## Step 6: Save Report Output: `{paper_dir}/reports/check_claim.json` ```json { "summary": { "total_claims": 50, "by_evidence_type": { "experiment": 25, "related_work": 10, "theoretical": 3, "code": 8 } }, "results": [ { "id": 1, "source": "abstract", "quote": "exact text", "claim": "restatement", "evidence_type": ["experiment"] } ] } ``` ## Coverage Rule **Err on the side of over-extraction** — downstream skills will filter. A missed claim cannot be verified later. Aim for 60+ claims on a typical 10-page paper. ## Tips - Look for "we show", "we propose", "we achieve", "we demonstrate", "outperforms", "state-of-the-art", "first", "novel" - Claims can appear anywhere — abstract, method, conclusion, captions, appendix - Every number in the abstract should appear as a claim and be cross-referenced against the tables - Passive voice often hides claims: "performance is improved by 3%" → who improved it? If the authors, it's a claim - Qualifiers matter: "slightly better" vs "significantly better" vs "better" — extract the qualifier as part of the claim - Figures are a rich source of implicit claims: trend lines, convergence curves, qualitative examples all assert something - Do NOT flag writing issues (grammar, typos) — that is `read-txt`'s job - **Ignore PDF parsing artifacts** in quotes: broken hyphens (`ex-\nploratory`), joined words from line breaks (`turnlevel`), LaTeX math (`$14.9 \%$`). Clean up the quote to match the actual paper text when extracting.