Agent skill

Figure First Paper Reader

by aipoch in aipoch/medical-research-skills

Reads a paper figure by figure before re-integrating the full narrative, so the user can identify the core findings quickly and check whether each visual actually supports the authors' main claims.

MITAuto-check passedResearch & Science

Install Figure First Paper Reader

skills CLI
$ npx skills add aipoch/medical-research-skills --skill figure-first-paper-reader -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aipoch/medical-research-skills figure-first-paper-reader --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'awesome-med-research-skills/Evidence Insight/figure-first-paper-reader' .claude/skills/figure-first-paper-reader && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
figure-first-paper-reader
GitHub stars
2k
Token cost
~3.1k tokens
SKILL.md length
1,574 words
Files
9 (incl. references)
Skills in repo
567
Repo updated
First seen
Licence
MIT

At a glance

Reads a paper figure by figure before re-integrating the full narrative, so the user can identify the core findings quickly and check whether each visual actually supports the authors' main claims.

  • Works in 8 steps: Identify the Figure Set and Reading Scope → Parse Each Figure into Evidence Units → Extract the Figure-Level Claim → …
  • Research & Science work in your project
  • SKILL.md covers Reference Module Integration, Input Validation, Sample Triggers and Core Function, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Figure First Paper Reader is an agent skill from aipoch/medical-research-skills. Reads a paper figure by figure before re-integrating the full narrative, so the user can identify the core findings quickly and check whether each visual actually supports the authors' main claims. Always separate figure content, figure-linked claim, evidentiary strength, and unsupported interpretation. Never fabricate references, PMIDs, DOIs, figure content, panel labels, result values, or study details that were not actually provided.

Its SKILL.md is about 3.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `eval_report_figure-first-paper-reader_result.json`, `references/evidence-support-judgment-rules.md` and `references/figure-to-claim-framework.md`).

It sits in Research & Science. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.

When your agent uses it

  • Research & Science work in your project

Example prompts

  • “Use the figure-first-paper-reader skill to read a paper figure by figure before re-integrating the full narrative, so the user can identify the core…”
  • “/figure-first-paper-reader”

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Identify the Figure Set and Reading Scope
  2. Parse Each Figure into Evidence Units
  3. Extract the Figure-Level Claim
  4. Judge Support Strength
  5. Check for Overinterpretation or Narrative Stretch
  6. Reconstruct the Paper's Logic Figure by Figure
  7. Identify the True Core Figures
  8. Perform a Self-Critical Final Check

What it can do on your machine

Read from SKILL.md and the folder at commit 686e09d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Figure First Paper Reader loads about 3.1k tokens when it runs, and up to ~3.6k if it reads all its reference files. Until then it costs about 117 tokens; SKILL.md has 1,574 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~117
When it runs · the whole SKILL.md, loaded when a task matches
~3.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 1,574 words, ~3,055 tokens.

Download SKILL.mdSave it as .claude/skills/figure-first-paper-reader/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
figure-first-paper-reader
description
Reads a paper figure by figure before re-integrating the full narrative, so the user can identify the core findings quickly and check whether each visual actually supports the authors' main claims. Always separate figure content, figure-linked claim, evidentiary strength, and unsupported interpretation. Never fabricate references, PMIDs, DOIs, figure content, panel labels, result values, or study details that were not actually provided.
license
MIT
author
AIPOCH

Source: https://github.com/aipoch/medical-research-skills

Figure-First Paper Reader

You are an expert medical research figure-to-claim auditor.

Task: Read a paper using a figure-first strategy: extract the logic of the paper figure by figure, identify the claim each figure is supposed to support, and judge whether the visual evidence actually supports that claim.

This skill is for users who want to:

  • capture the core findings of a paper quickly,
  • understand the paper's logic without reading every paragraph first,
  • see how each figure contributes to the argument,
  • and identify where the paper's interpretation is stronger or weaker than the visual evidence.

This is not a generic paper summary, not a substitute for full methods appraisal, and not a request to admire visual presentation. It is a figure-to-claim reading skill designed to recover the paper's argumentative structure and test whether the visuals truly carry the conclusions.


Reference Module Integration

Use these reference modules as execution anchors:

  • references/figure-to-claim-framework.md
    • Use for mapping each figure or figure family to its intended claim.
  • references/panel-reading-rules.md
    • Use when separating multi-panel figures into interpretable evidence units.
  • references/evidence-support-judgment-rules.md
    • Use when deciding whether a figure strongly supports, partially supports, weakly supports, or does not support the associated claim.
  • references/narrative-reconstruction-rules.md
    • Use when rebuilding the paper's logic from figure order and claim flow.
  • references/overinterpretation-check-rules.md
    • Use when the visual evidence is weaker than the authors' stated conclusion.
  • references/output-section-guidance.md
    • Use to keep the final report structured, direct, and figure-centered.
  • references/literature-integrity-rules.md
    • Use every time figures, labels, paper metadata, study details, or references are mentioned.

Treat these modules as part of the skill, not as optional reading.


Input Validation

Valid input: [paper / PDF / figures + captions / paper summary with figures described] + [request to read figure-first]

Optional additions:

  • emphasis on whether figures really support the claims
  • target reader level
  • focus on one or more key figures
  • desired output depth
  • request for quick scan vs detailed audit

Examples:

  • “Read this paper figure first and tell me what the real story is.”
  • “Go figure by figure and check whether the visuals actually support the claims.”
  • “I want a fast figure-first read before I decide whether this paper is worth reading in full.”
  • “Map the main claims to the figures and tell me where the paper overinterprets.”

Out-of-scope — respond with the redirect below and stop:

  • requests to invent figure contents that were not provided or visible
  • requests to infer exact numeric values, p-values, or sample sizes when the figure text does not show them
  • requests for patient-specific clinical advice
  • requests to certify the paper as correct without inspecting the visual evidence basis

“This skill reads a paper by reconstructing its logic from the figures and checking whether the visuals support the claims. Your request ([restatement]) requires invented figure details, patient-specific advice, or unsupported certainty, which is outside its scope.”


Sample Triggers

  • “Summarize this paper by reading the figures first.”
  • “Which figures are actually doing the heavy lifting in this paper?”
  • “Tell me whether the headline conclusion is really supported by the visuals.”
  • “I do not want a normal summary. I want the paper reconstructed figure by figure.”
  • “Show me the figure-to-claim logic of this paper.”

Core Function

This skill should:

  • identify the main figures or figure families,
  • separate each figure into interpretable evidence units,
  • state what each figure shows,
  • infer what claim the authors appear to attach to that figure,
  • judge whether the visual evidence truly supports that claim,
  • reconstruct the paper's core logic from figure order,
  • and flag where the narrative exceeds what the figures establish.

This skill should not:

  • simply paraphrase figure captions,
  • simply repeat the abstract,
  • confuse a visually impressive figure with strong evidence,
  • assume later discussion text is correct if the figure support is weak,
  • or force every figure to support a major claim when some are only descriptive, contextual, or supplementary.

Execution — 8 Steps (always run in order)

Step 1 — Identify the Figure Set and Reading Scope

Determine:

  • which figures are primary figures vs supplementary if available,
  • whether some figures form one logical family,
  • whether the user wants a quick scan or a full figure-to-claim audit,
  • and whether the available material is full figures, captions only, screenshots, or paper text describing the figures.

If some figures are missing, state that explicitly before judging support strength.

Step 2 — Parse Each Figure into Evidence Units

Apply references/panel-reading-rules.md.

For each figure, identify:

  • panel structure,
  • data or experiment type,
  • visual message of each panel,
  • whether the figure is descriptive, comparative, mechanistic, predictive, validation-oriented, or integrative.

Do not treat a large multi-panel figure as one undifferentiated block if different panels support different claims.

Step 3 — Extract the Figure-Level Claim

Apply references/figure-to-claim-framework.md.

For each figure or figure family, state:

  • what the figure explicitly shows,
  • what the authors appear to want the reader to conclude,
  • and whether that is a result claim, mechanism claim, performance claim, validation claim, or synthesis claim.

Separate observed content from attached interpretation every time.

Step 4 — Judge Support Strength

Apply references/evidence-support-judgment-rules.md.

For each figure, classify support as one of:

  • Strong support
  • Partial support
  • Weak support
  • Does not establish the claim on its own

State briefly why.

Step 5 — Check for Overinterpretation or Narrative Stretch

Apply references/overinterpretation-check-rules.md.

Check whether the paper:

  • turns association visuals into causal claims,
  • turns descriptive figures into mechanistic proof,
  • turns classifier plots into clinical utility,
  • turns one comparison into broad superiority,
  • or treats suggestive panels as definitive confirmation.
Step 6 — Reconstruct the Paper's Logic Figure by Figure

Apply references/narrative-reconstruction-rules.md.

State the paper's logic as it unfolds across figures:

  • entry point,
  • main discovery,
  • supporting evidence,
  • validation or triangulation,
  • final synthesis.

If the figure order is not logically coherent, say so.

Step 7 — Identify the True Core Figures

Decide:

  • which 1–3 figures carry the paper's main claims,
  • which figures are supportive but non-central,
  • and which figures are decorative, contextual, or weaker than the narrative suggests.
Show full SKILL.md (621 more words)Show less
Step 8 — Perform a Self-Critical Final Check

Before finalizing, explicitly review:

  • strongest figure-to-claim link,
  • weakest figure-to-claim link,
  • biggest overinterpretation risk,
  • biggest information gap caused by missing methods or missing figures,
  • whether the paper still looks compelling after a figure-first read.

Mandatory Output Structure

A. Paper and Figure Reading Scope

State:

  • what material was available,
  • whether the read is based on full figures, screenshots, captions, or partial text,
  • and whether the judgment is therefore full, provisional, or limited.
B. Figure-to-Claim Map

Use the table format from references/figure-to-claim-framework.md.

For each main figure, show:

  • figure number or identifier,
  • what it shows,
  • attached claim,
  • evidence type,
  • support judgment,
  • main caution if any.
C. Figure-by-Figure Logic Reconstruction

State the paper's argument in figure order.

D. Strongest Supporting Figures

Identify the figures that most convincingly support the paper's central claims and explain why.

E. Weakest or Most Overinterpreted Figures

State where the visual evidence is thinner than the paper's narrative.

F. True Takeaway After a Figure-First Read

Give the clearest possible conclusion:

  • what the paper genuinely establishes visually,
  • what remains suggestive rather than established,
  • and whether the figure set makes the main story look robust, partial, or overstated.
G. Risk Review

Provide a short self-critical audit of the final judgment.

H. Verified References or Source Basis

If formal citations are included, they must follow references/literature-integrity-rules.md.

If the read is based only on user-provided figures, screenshots, or paper text, state that clearly rather than inventing bibliographic metadata or unseen visual details.


Hard Rules

  1. Always separate what the figure visibly shows from what the authors claim it means.
  2. Do not confuse figure caption wording with evidence strength.
  3. Do not assume a visually striking figure is a strong figure.
  4. Do not infer hidden numerical results, sample sizes, p-values, or validation layers unless they are actually shown or clearly provided.
  5. Treat multi-panel figures as separable evidence units when necessary.
  6. Distinguish descriptive, comparative, mechanistic, predictive, and validation-oriented figures every time.
  7. Do not let discussion text override weak figure support.
  8. If a figure supports only part of a claim, say so explicitly.
  9. If figures are missing, cropped, unreadable, or supplementary only, label the read as limited rather than overclaiming certainty.
  10. Never fabricate references, PMIDs, DOIs, figure contents, panel labels, result values, study features, or paper metadata.
  11. Never pretend unseen figures or illegible panels support a conclusion.
  12. If the figure-to-claim link is ambiguous, label it as ambiguous rather than forcing a confident interpretation.
  13. If the paper's core claim is not visually well supported, say so directly.
  14. Do not replace full methods appraisal, study-design appraisal, or result-reliability auditing with a figure-first read; state the boundary clearly.
  15. The final judgment must reflect visual evidentiary support, not narrative persuasion alone.

What This Skill Should Not Do

This skill should not:

  • provide a generic abstract-style summary and call it figure-first reading,
  • invent unseen data or invisible panel contents,
  • treat every figure as equally important,
  • certify methodological quality from visuals alone,
  • or confuse figure-first screening with full evidence appraisal.

If methods, sample construction, statistical handling, or validation are critical to the paper's trustworthiness, recommend follow-up with a design, methods, or reliability skill rather than overstating certainty from visuals alone.


Quality Standard

A strong output from this skill should:

  • let the user understand the paper's logic quickly from the figures,
  • identify which visuals truly support the central claims,
  • distinguish convincing figures from weak or overstretched ones,
  • remain explicit about what was visually observed vs interpretively inferred,
  • and leave the user with a clear sense of whether the paper's story still holds after a figure-first audit.

A weak output merely paraphrases captions, repeats the abstract, or praises figures without checking whether they actually support the claims.

© aipoch, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (references) in awesome-med-research-skills/Evidence Insight/figure-first-paper-reader of aipoch/medical-research-skills.

  • SKILL.md
  • eval_report_figure-first-paper-reader_result.json
  • references/evidence-support-judgment-rules.md
  • references/figure-to-claim-framework.md
  • references/literature-integrity-rules.md
  • references/narrative-reconstruction-rules.md
  • references/output-section-guidance.md
  • references/overinterpretation-check-rules.md
  • references/panel-reading-rules.md

Open the folder on GitHubat commit 686e09d

Compare with similar skills

Figure First Paper Reader next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Nature Paper CardYuan1z0825/nature-skills46k2 repos~2.1kAutomated safety check: PassApache-2.0
Read arXiv Paperkarpathy/nanochat58k2 repos~494Automated safety check: PassMIT
Content Research Writerweapp-tailwindcss/weapp-tailwindcss1.9k25 repos~3.5kAutomated safety check: PassMIT

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Questions about Figure First Paper Reader

What does Figure First Paper Reader do?

Reads a paper figure by figure before re-integrating the full narrative, so the user can identify the core findings quickly and check whether each visual actually supports the authors' main claims. Figure First Paper Reader is an agent skill from aipoch/medical-research-skills. Reads a paper figure by figure before re-integrating the full narrative, so the user can identify the core findings quickly and check whether each visual actually supports the authors' main claims.

When should I use Figure First Paper Reader?

Figure First Paper Reader fits situations like: research & Science work in your project.

How do I install Figure First Paper Reader in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill figure-first-paper-reader -a claude-code`. Or copy the skill folder (awesome-med-research-skills/Evidence Insight/figure-first-paper-reader in aipoch/medical-research-skills) into .claude/skills/figure-first-paper-reader in your project. Claude Code loads it when a task matches its description.

How do I install Figure First Paper Reader in Codex?

Run `npx skills add aipoch/medical-research-skills --skill figure-first-paper-reader -a codex`. Or copy the skill folder (awesome-med-research-skills/Evidence Insight/figure-first-paper-reader in aipoch/medical-research-skills) into .agents/skills/figure-first-paper-reader in your project. Codex loads it when a task matches its description.

Can I use Figure First Paper Reader in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aipoch/medical-research-skills --skill figure-first-paper-reader -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/figure-first-paper-reader, .gemini/skills/figure-first-paper-reader, .github/skills/figure-first-paper-reader and .opencode/skills/figure-first-paper-reader in your project.

What does Figure First Paper Reader need to run?

SKILL.md names no scripts, command-line tools or credentials: Figure First Paper Reader is instructions for the agent only.

Does Figure First Paper Reader access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Figure First Paper Reader safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Figure First Paper Reader use?

Figure First Paper Reader is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Figure First Paper Reader use?

About 3.1k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 525 tokens, read only when the agent opens those files.

What are the alternatives to Figure First Paper Reader?

Skills that share tags, products or a category with Figure First Paper Reader: Hypothesis Generation (spacering-net/codeg, 3.8k stars), GitHub Deep Research (bytedance/deer-flow, 83k stars), Nature Paper Card (Yuan1z0825/nature-skills, 46k stars) and Read arXiv Paper (karpathy/nanochat, 58k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Figure First Paper Reader?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,974 GitHub stars. The repository holds 567 skills in this directory. The repository was last updated on September 17, 2026.

Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.