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paper-memory-builder

Convert a paper draft + figures + Zotero metadata into reusable .paper/claims.yml and .paper/figures.yml files so the academic-writing-skills skill can do writing, revision, and audit passes without re-reading the manuscript every time. Use when the user asks to "build paper memory", "extract claims from this manuscript", "extract claims, supporting evidence, and figure key numbers", or "prepare this paper for AI-assisted writing". NOT for summarizing cited papers in a literature cluster — that's `paper-summarize`. This skill is for the user's own manuscript draft only.

personAuthor: TashanworldhubOpenAPI
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paper-memory-builder

Bridge between research-hub and academic-writing-skills. Reads a manuscript draft (Word, LaTeX, Markdown, Obsidian paper folder) plus the figures it references, and writes structured .paper/claims.yml + .paper/figures.yml so the writing skill can reason about the paper without parsing the manuscript on every call.

This skill does not edit the manuscript itself. That's the writing skill's job. We just produce the memory layer it consumes.

When to use

Trigger phrases:

  • "Build paper memory for this manuscript."
  • "Extract claims, figures, and evidence from this paper folder."
  • "Prepare reusable memory for writing and revision."
  • "I'm starting a rebuttal — give me the claims layer first."

Not for:

  • Writing the rebuttal itself — academic-writing-skills.
  • Building the orientation memo — research-project-orienter.
  • Comparing papers — literature-triage-matrix.
  • Verifying a NotebookLM brief — notebooklm-brief-verifier.

Inputs

In priority order:

  1. .paper/ existing files — if claims.yml already exists, parse it; this run should refresh, not replace human edits.
  2. The manuscript file — usually one of:
    • paper/manuscript.docx / manuscript.tex / manuscript.md
    • Obsidian paper note under raw/<paper-cluster>/manuscript.md
    • Word/LaTeX in a sibling repo specified by the user
  3. Figure files under figures/ or outputs/figures/ — read filenames + captions; don't OCR images.
  4. .research/project_manifest.yml — for project context (research question, datasets, current_stage). Use to anchor claims in the project's overall question.
  5. .research/literature_matrix.md — for citation key lookup if the manuscript references "Smith 2024" but you need to disambiguate.

Scanning the paper repo for evidence artifacts (v0.3.16+)

Beyond the manuscript + figures, real research repos typically contain sibling artifacts that populate claims[].evidence_artifacts for non-figure evidence. When scanning, look for:

  • Simulation / experiment outputs — *.csv, *.parquet, *.npz, *.h5, *.json log files under outputs/, results/, or repo-root sibling dirs. Common patterns: <experiment_id>_log.csv, run_log.csv, adaptation_log.csv. These back claims like "χ²=891, p<0.0001 across 50 runs" (the chi-squared output came from the per-agent decision log, not from a figure).
  • Analysis scripts — *.py, *.R, *.jl, *.ipynb files that produce evidence numbers. The script itself is rarely the evidence artifact, but its OUTPUT path is. Trace the script → output pairing if the manuscript cites a number computed by a script.
  • Drawio / SVG framework diagrams — *.drawio, *.svg sources for conceptual figures (e.g. framework architecture, decision-flow diagrams). These often back claim text like "Figure 1 shows the module architecture" even when the embedded image in the .docx is rendered from the drawio source.
  • Reviewer-response artifacts — Review Response-YYYYMMDD.docx files (operator-side response prep). Not consumed by paper-memory-builder directly but listed here as a typical sibling artifact; academic-writing-skills reviewer-response workflow uses these.

Populate claims[].evidence_artifacts with the artifact PATH (relative to the paper repo root), not the artifact contents. Example:

- id: C8
  text: "Chi-squared test on coping-appraisal keywords yields χ²=891, p<0.0001..."
  evidence_artifacts:
    - "outputs/llm-abm_decision_log.csv"        # raw per-agent text used in chi-sq
    - "scripts/analyze_appraisal_keywords.py"   # script that ran the test
    - "Result section §4.2 (chi-squared paragraph)"  # manuscript anchor
  figure_or_table: ["TabS5"]
  status: draft

This makes the audit trail traceable end-to-end: claim → manuscript sentence → figure/table reference → underlying data file → analysis code. Cross-plugin consumers like academic-writing-skills (claim- evidence audit) can then verify the chain is intact before accepting the claim as supported.

Outputs

Write to <project-root>/.paper/:

  • claims.yml — every paper-level claim, with evidence pointers + status. Schema: references/yaml-schemas.md.
  • figures.yml — every figure inventory, with key numbers + supported claims. Schema: references/yaml-schemas.md.
  • revision_history.yml — append-only log of revision rounds. Schema + append-vs-overwrite rules: references/revision_history_schema.md.

Do not touch journal_format.md, reviewer_comments.md, or style_overrides.md — those belong to academic-writing-skills.

Token-saving behavior

  • Read manuscript ONCE per session, extract claims + figures, then reference .paper/*.yml in subsequent writing turns.
  • Pass-through claim text exactly as in the manuscript; do not rephrase. The writing skill will polish later.
  • For figures, read just the caption + filename; don't OCR or describe visual content.
  • After running, hand off cleanly: tell the user "claims.yml and figures.yml ready. Load academic-writing-skills next for any writing/revision/audit pass."

Output format for the user

[paper-memory-builder]
  Read manuscript: paper/manuscript.docx (8 pages, 12 figures)
  Wrote: .paper/claims.yml (9 claims; 2 marked at risk)
  Wrote: .paper/figures.yml (12 figures; 8 mapped to claims, 4 are context)
  Suggested next: load academic-writing-skills for revision/audit passes.

What NOT to do

  • Don't edit the manuscript file. Read-only.
  • Don't paraphrase claim text. Copy exactly from the manuscript.
  • Don't fabricate figures or claims that aren't in the source.
  • Don't emit an unsupported claim as status: draft — see the anti-leakage rule below.
  • Don't write to .paper/journal_format.md, reviewer_comments.md, or style_overrides.md. Those are owned by academic-writing-skills.
  • Don't write to .research/ — that's the workspace layer, not the paper layer.
  • Don't extract claims from cited works — only from THIS paper.

Anti-leakage rule (binding contract)

A claim with empty or absent evidence_artifacts MUST have status: gap plus a one-line gap_reason. Never emit such a claim as status: draft or status: supported.

This is the contract that prevents an unsupported claim from leaking into the downstream writing/audit pipeline as if it were evidenced.

How it manifests in normal use:

  • The manuscript intro asserts something the experiment section never backs up → emit it as status: gap with a gap_reason like "intro claim with no matching E-run output". The writing skill then surfaces it as [MATERIAL GAP] rather than treating it as evidenced prose.
  • A claim has evidence pointers but you're not yet sure they back it fully → still status: draft; document the doubt in risk: rather than emptying evidence_artifacts.
  • A claim was dropped from the latest revision → keep the row, flip status: rejected; do not delete (audit trail).

The contract is enforced by scripts/check_claims_schema.py against the JSON Schema at references/claims.schema.json. Run the validator manually after editing .paper/claims.yml by hand:

python scripts/check_claims_schema.py <path-to-claims.yml>

See also

  • references/yaml-schemas.md — .paper/claims.yml and .paper/figures.yml schemas
  • references/revision_history_schema.md — .paper/revision_history.yml schema + append-only audit-trail rules