Peer Review
K-Dense-AI/claude-scientific-writer
Prepare evidence-bounded, constructive peer-review drafts and structured manuscript assessments.
Compose one publication-grade multi-panel figure. An agent skill from aipoch/open-science.
$ npx skills add aipoch/open-science --skill figure-composer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aipoch/open-science figure-composer --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aipoch/open-science.git skills-src && mkdir -p .claude/skills && cp -r skills-src/resources/skills/figure-composer .claude/skills/figure-composer && rm -rf skills-srcUse ~/.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/
Install the "figure-composer" agent skill from https://github.com/aipoch/open-science/tree/main/resources/skills/figure-composer into .claude/skills/figure-composer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "figure-composer", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aipoch/open-science/tree/main/resources/skills/figure-composerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aipoch/open-science --skill figure-composer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aipoch/open-science figure-composer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/open-science.git skills-src && mkdir -p .agents/skills && cp -r skills-src/resources/skills/figure-composer .agents/skills/figure-composer && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "figure-composer" agent skill from https://github.com/aipoch/open-science/tree/main/resources/skills/figure-composer into .agents/skills/figure-composer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "figure-composer", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aipoch/open-science --skill figure-composer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aipoch/open-science figure-composer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/open-science.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/resources/skills/figure-composer .cursor/skills/figure-composer && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "figure-composer" agent skill from https://github.com/aipoch/open-science/tree/main/resources/skills/figure-composer into .cursor/skills/figure-composer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "figure-composer", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aipoch/open-science.git --path resources/skills/figure-composer--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aipoch/open-science --skill figure-composer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aipoch/open-science figure-composer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/open-science.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/resources/skills/figure-composer .gemini/skills/figure-composer && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "figure-composer" agent skill from https://github.com/aipoch/open-science/tree/main/resources/skills/figure-composer into .gemini/skills/figure-composer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "figure-composer", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aipoch/open-science figure-composerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aipoch/open-science --skill figure-composer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aipoch/open-science.git skills-src && mkdir -p .github/skills && cp -r skills-src/resources/skills/figure-composer .github/skills/figure-composer && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "figure-composer" agent skill from https://github.com/aipoch/open-science/tree/main/resources/skills/figure-composer into .github/skills/figure-composer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "figure-composer", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aipoch/open-science --skill figure-composer -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aipoch/open-science figure-composer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/open-science.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/resources/skills/figure-composer .opencode/skills/figure-composer && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "figure-composer" agent skill from https://github.com/aipoch/open-science/tree/main/resources/skills/figure-composer into .opencode/skills/figure-composer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "figure-composer", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
figure-composerCompose one publication-grade multi-panel figure. An agent skill from aipoch/open-science.
Figure Composer is an agent skill from aipoch/open-science. Compose one publication-grade multi-panel figure. Start from a one-line claim plus immutable data Artifact Version references, or inspect an existing figure and draft its outline directly. Plan a 12-column panel outline, delegate one worker per panel, compose and inspect the result, then run at most three adversarial review rounds while regenerating only affected panels. For a standalone plot use figure-style; for whole-paper figure ordering use paper-narrative.
Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `kernel.py` and `open-science.json`).
It sits in Research & Science, covering Reproducible research. The repository describes itself as: The open-source AI research workbench for scientific research and agent workflows. Local-first, model-agnostic desktop app with extensible skills, MCP tools and connectors… The licence is Apache-2.0.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 51d7079. It shows what the files ask for, not the result of running them.
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.
Ships script files (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Figure Composer loads about 2.9k tokens when it runs. Until then it costs about 122 tokens; SKILL.md has 1,314 words of instructions outside code blocks.
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.
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.
The full file from aipoch/open-science at commit 51d7079, republished under its Apache-2.0 licence (© aipoch). 1,314 words, ~2,904 tokens.
.claude/skills/figure-composer/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.figure-composer is the outer workflow for one multi-panel figure. Use the
figure-style rules while planning and reviewing; every panel worker uses those
rules independently. Run paper-narrative first when the paper-level figure
sequence is still undecided.
Every notebook_execute request whose code uses a function named in this skill
includes this skill ID:
{ "kernelSkillIds": ["figure-composer"], "code": "print(figure_outline_schema())" }kernelSkillIds contains the skill ID; function calls belong in code. Call the
named functions directly without an import or discovery step.
claim: the one sentence the figure makes true without surrounding prose.dataVersionIds: immutable Upload or Artifact Version identities grounding
the panels.width_mm: venue column width, commonly 85–89 mm single or 174–183 mm double.rulesVersionId: immutable Artifact Version containing the design rules used
by the composite reviewer.delegatePrefix: short branch-unique prefix for panel and reviewer child names.Run this workflow only in the Main/root agent. Delegated children cannot call
host.delegate, so the whole composer cannot itself be delegated.
figure-style rules.host.viewImage, then have Main
draft and review the outline directly. Current host.llm calls do not accept
images, so do not add a second hidden inference step. Pixels cannot supply
Artifact Version identities; fill data_vid from the provided data.Main produces a panel_outline matching figure_outline_schema():
{
"claim": "…",
"width_mm": 180,
"ncol": 12,
"row_heights_mm": [40, 60, 46, 52],
"panels": [
{
"letter": "a",
"role": "schematic",
"row": 0,
"col": 0,
"colspan": 12,
"chart_family": "schematic overview",
"message": "…",
"data_vid": null,
"ask": "…"
},
{
"letter": "b",
"role": "primary",
"row": 1,
"col": 0,
"colspan": 7,
"chart_family": "scatter + trend",
"message": "…",
"data_vid": "…",
"ask": "…"
}
]
}Outline rules:
data_vid must be one of the supplied immutable Version
identities. Do not invent or rewrite Version IDs.fixed_panel_set: true only when the user explicitly requires the exact
listed panels.Geometry helpers reject duplicate panel letters (case-insensitive), overlapping grid spans, panels outside the grid, and invalid or subpixel grid dimensions. Use unique panel identifiers and non-overlapping positive spans within the grid.
Review the outline before fan-out. Use the schema as a contract; Main does the
reasoning and does not call host.llm to generate the outline again.
Generate each task in Python with panel_task(outline, letter, fig_label). The
returned task contains the complete panel procedure. Pass it unchanged on the
first render and supply the panel's data Version in inputs.
Dispatch from repl_execute. host.delegate accepts at most four children per
atomic call, so send ordered waves of no more than four. Each request uses this
output schema:
const panelOutputSchema = {
type: 'object',
additionalProperties: false,
required: ['panelVersionId', 'labelsUsed'],
properties: {
panelVersionId: { type: 'string', minLength: 1 },
labelsUsed: { type: 'array', items: { type: 'string' } }
}
}Use wait: false, then collect the exact { frameId, attemptId } receipt
handles. A collect timeout ends observation, not the child Attempt: collect
the same handles again while any remain running. Retry only after a terminal
failure or an explicitly rejected output, using a fresh child name. Panel
workers must submit their structured result with host.submitOutput before
finishing. Reject a non-completed/error child, missing or unsatisfied structured
output, a missing or duplicate expected panel_<letter>.png, or a mismatch
between its Artifact versionId and structuredOutput.panelVersionId. MIME
metadata may be absent; the exact filename and Version identity are the binding
checks. Return each wave's validated { letter, versionId } values from the
repl_execute call instead of relying on local const or let declarations to
survive a later call.
Keep finalized Version identities in outline order. Temporary paths are never
the Agent-to-Agent contract. Child names remain occupied after settlement, so
use a unique delegatePrefix and round number.
Generate a producer task with
composition_task(outline, panelVersions, fig_label). Main's newly written
Artifact can remain pending until its turn ends; the producer child publishes a
finalized composite that the reviewer can use. Pass the ordered panel Version
identities in inputs and require this output schema:
{
type: 'object',
additionalProperties: false,
required: ['compositeVersionId'],
properties: { compositeVersionId: { type: 'string', minLength: 1 } }
}The producer resolves the collected Version identities and places the paths in a
small JSON handoff under process.env.OPEN_SCIENCE_HANDOFF_DIR. On its
notebook_execute request, it passes the ordered, de-duplicated panel identities
as artifactVersionInputs. This registers the delegated immutable panel
Versions as the composition Run's provenance inputs; paths remain byte-access
implementation details and must never replace Version identities in this field.
The producer calls compose_figure, verifies notebook completion, and keeps the
actual returned runId. It publishes the final PNG with
write_artifact_file({ filename: "figure.png", producerRunId: composeResult.runId });
never substitute a round number or locally invented Run identity. This binds the
composite Artifact to the run that last wrote its bytes. Fail the workflow if
any panel Version cannot be validated in the active Project; never silently
compose with an unregistered provenance input.
Collect the exact producer Attempt and require completed status, satisfied
structured output, and exactly one figure.png Artifact whose versionId
matches structuredOutput.compositeVersionId. Use that finalized composite
Version for inspection and review. The producer submits the structured result
with host.submitOutput and finishes normally.
compose_figure requires each input image to match its panel_px dimensions
exactly. A mismatch raises before the output is saved; regenerate the panel at
the requested size. Images are never stretched to fit. Use the exact figsize
expressions generated by panel_task, rather than rounded inch measurements,
and verify the saved PNG dimensions.
Call compose_crops in Python and inspect every crop before formal review.
host.viewImage never upscales and caps the output long edge at 1568 pixels;
omit maxSize when native pixels are required.
One repl_execute invocation can attach at most four images. Split five or more
crops into ordered batches of no more than four, and let each invocation finish
successfully before starting the next; a failed enclosing invocation discards
every image staged by that invocation. For each cropBatch, use the current
camelCase API:
if (cropBatch.length > 4) throw new Error('viewImage crop batch exceeds four images')
for (const [letter, box] of cropBatch) {
await host.viewImage(
{ versionId: compositeVersionId },
{ crop: { unit: 'pixels', left: box[0], top: box[1], right: box[2], bottom: box[3] } }
)
}
return { inspectedPanels: cropBatch.map(([letter]) => letter) }Check contrast, smallest marks, leader crossings, color identity, legend binding, seams, panel-letter overlap, gutter bleed, and resize artifacts. Fix an obvious defect before formal review.
Run at most three rounds. An independent reviewer Attempt is required before
returning any composite. Generate the reviewer task with
composite_review_task(...) and its outputSchema with
review_schema(). Pass the task unchanged to one reviewer; include the
composite, optional previous composite, rulesVersionId, and every non-null
panel data Version in inputs. Collect the exact receipt and use only validated
structuredOutput as the review object. The reviewer submits it with
host.submitOutput; do not replace formal review with Main's own inspection.
After each result:
accept or minor_revision, there are no
BLOCKERs, and there are at most two MAJORs.previous_outline = copy.deepcopy(outline) before applying
outline_revisions explicitly. Then call
apply_outline_revisions(outline, revisions, previous_outline=previous_outline).
This includes new panels and every panel whose pixel dimensions changed, even
when a shared row-height change names only one panel. Pass the same dpi and
gutter_mm as composition if overriding their defaults. Removed panels are
excluded; drop their entries from the collected panel Versions.group_fixes_by_panel(review) and compute
regen = (affected | set(fixb)) & {p["letter"] for p in outline["panels"]}.regen. Build each retry task as
panel_task(outline, letter, fig_label) + fixb.get(letter, "") and add: “Do not
over-correct: preserve everything the previous version got right.” Include
the prior panel Version when one exists and its data Version in inputs.Stop when accepted, or when outline_revisions is empty and new findings are
only carve-out exceptions to the previous round; that is the over-labeling
signal. Otherwise stop after round three. If the current composite was not
accepted, report the unresolved findings rather than return an older composite
as the final result.
After acceptance, verify the composite's provenance contains the current panel
Versions. Return that finalized figure.png Artifact with a user-visible link;
do not publish a duplicate root Artifact.
© aipoch, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 2 other files in resources/skills/figure-composer of aipoch/open-science.
Open the folder on GitHubat commit 51d7079
Figure Composer 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Figure Composer this skillaipoch/open-science | 5.5k | — | ~2.9k | Automated safety check: Pass | Apache-2.0 | |
| Peer ReviewK-Dense-AI/claude-scientific-writer | 2.4k | 2 repos | ~3.1k | Automated safety check: Notes | MIT | |
| CHARLS Paper Reproduction Guidexjtulyc/MedgeClaw | 617 | 1 repos | ~1.8k | Automated safety check: Pass | None | |
| Add Bactopia Toolbactopia/bactopia | 522 | — | ~4.1k | Automated safety check: Pass | MIT | |
| Modeling Code and Result Contractsyushui2022/MathModel-Skill | 452 | — | ~1.4k | Automated safety check: Pass | MIT | |
| Light Research OrchestratorLight0305/Light-skills | 641 | — | ~3.8k | Automated safety check: Pass | MIT |
K-Dense-AI/claude-scientific-writer
Prepare evidence-bounded, constructive peer-review drafts and structured manuscript assessments.
xjtulyc/MedgeClaw
Guides an agent through reproducing papers built on the CHARLS health and retirement survey, from variable mapping to cognition, depression and isolation scores.
bactopia/bactopia
Scaffold a complete Bactopia Tool across all three tiers -- module, subworkflow, and workflow entry point under workflows/bactopia-tools/.
yushui2022/MathModel-Skill
Generates result-evidence contracts, tables and runnable q1 to q3 modeling code scaffolds for a math modeling paper from a model route, a data plan and cleaned data.
Light0305/Light-skills
Coordinates and recovers multi-stage Light research projects from a single passport file, with checkpoints, stale-work tracking and rerouting only when you approve.
K-Dense-AI/scientific-agent-skills
Plans and audits runs of the HypoGeniC and HypoRefine packages, which propose hypotheses from labeled text datasets, with local checks before any model call.
aipoch/open-science
Creates, revises, evaluates and publishes skills in the Open-Science app through its native host.skills composer, with optional test prompts and benchmarks.
aipoch/open-science
Prepares setup instructions and a named activation file for a user-managed software environment on an Open-Science SSH or Slurm compute host.
aipoch/open-science
Handles /Customize requests by sending Skill work to the internal skill-creator and managing Specialist agents through the JavaScript host.agents SDK.
aipoch/open-science
Publication-grade correctness and legibility rules for final-deliverable scientific figures, not exploratory plots.
aipoch/open-science
Judge and reshape the story told by an entire paper figure deck.
aipoch/open-science
Teaches an agent to inspect Open-Science's JavaScript control REPL, check which host.* calls are allowed, and find project files, sessions and agent frames.
Categories
Compose one publication-grade multi-panel figure. An agent skill from aipoch/open-science. Figure Composer is an agent skill from aipoch/open-science. Compose one publication-grade multi-panel figure.
Figure Composer fits situations like: tasks that involve Reproducible research.
Run `npx skills add aipoch/open-science --skill figure-composer -a claude-code`. Or copy the skill folder (resources/skills/figure-composer in aipoch/open-science) into .claude/skills/figure-composer in your project. Claude Code loads it when a task matches its description.
Run `npx skills add aipoch/open-science --skill figure-composer -a codex`. Or copy the skill folder (resources/skills/figure-composer in aipoch/open-science) into .agents/skills/figure-composer in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aipoch/open-science --skill figure-composer -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-composer, .gemini/skills/figure-composer, .github/skills/figure-composer and .opencode/skills/figure-composer in your project.
Going by SKILL.md and its folder, Figure Composer needs Python for the scripts in its folder. Our summary lists: Python 3.
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.
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.
Figure Composer is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.9k 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.
Skills that share tags, products or a category with Figure Composer: Peer Review (K-Dense-AI/claude-scientific-writer, 2.4k stars), CHARLS Paper Reproduction Guide (xjtulyc/MedgeClaw, 617 stars), Add Bactopia Tool (bactopia/bactopia, 522 stars) and Modeling Code and Result Contracts (yushui2022/MathModel-Skill, 452 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
aipoch (a GitHub organization) maintains it in aipoch/open-science, which has 5,475 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on October 8, 2026.
Source: aipoch/open-science on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.