xuzhougeng/wisp-science/skills/figure-composer/SKILL.md
figure-composer
Compose or improve a publication-grade multi-panel scientific figure from a claim, concrete data paths, or an existing image. Use for figure outlining, parallel panel rendering, exact-grid composition, visual inspection, and adversarial figure review. Use figure-style for one standalone plot and paper-narrative for whole-paper figure ordering.
- Source repository stars
- 560
- Declared platforms
- 0
- Static risk flags
- 0
- Last source update
- 2026-07-28
- Source checked
- 2026-07-28
Decision brief
What it does—and where it fits
Load figure-style with this skill. The sidecar provides pure geometry, composition, task-building, and review-schema helpers. It does not call models, delegate Agents, resolve artifacts, or inspect images from Python.
Not for
- Tasks that require unconfirmed production actions or broad system permissions.
- Environments where the pinned source and install steps cannot be inspected.
Compatibility matrix
Platform support, with evidence labels
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
Inspect first. Install second.
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/xuzhougeng/wisp-science --skill "skills/figure-composer"Inspect the Agent Skill "figure-composer" from https://github.com/xuzhougeng/wisp-science/blob/95d2c13d1665d46a388b5bdc998dcce0d5ec2eee/skills/figure-composer/SKILL.md at commit 95d2c13d1665d46a388b5bdc998dcce0d5ec2eee. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
What the source asks the agent to do
- 01
Workflow
1. Build an outline matching figureoutlineschema(). Put real paths in datapath; use null for schematics. 2. Make panel a the conceptual hook and panel b the primary evidence. Use a 12-column grid and one row per sub-claim. 3. Build one instruction per panel with paneltask(...).…
Build an outline matching figureoutlineschema(). Put real paths inMake panel a the conceptual hook and panel b the primary evidence. Use aBuild one instruction per panel with paneltask(...). - 02
Inputs
Require a one-sentence claim, target width in millimetres, and concrete project-relative or absolute data paths. Never use artifact ids as paths. For an existing figure, inspect the real image with viewimage and write the outline yourself; pixels cannot reveal the source data pa…
Require a one-sentence claim, target width in millimetres, and concrete project-relative or absolute data paths. Never use artifact ids as paths. For an existing figure, inspect the real image with viewimage and write t… - 03
Outline example
Review the “Outline example” section in the pinned source before continuing.
Review and apply the “Outline example” source section. - 04
Boundaries
Use delegatetasks only as an explicit Wisp tool; never call delegation from
Use delegatetasks only as an explicit Wisp tool; never call delegation fromUse viewimage only on a concrete local image file.Keep data preparation in normal project files. Use runincontext only when
Permission review
Static risk signals and limitations
No configured static risk pattern was detected
This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.
Evidence record
Why each signal appears
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 77/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 560 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Provenance and original SKILL.md
- Repository
- xuzhougeng/wisp-science
- Skill path
- skills/figure-composer/SKILL.md
- Commit
- 95d2c13d1665d46a388b5bdc998dcce0d5ec2eee
- License
- AGPL-3.0
- Collected
- 2026-07-28
- Default branch
- main
View the original SKILL.md
Figure composer
Load figure-style with this skill. The sidecar provides pure geometry,
composition, task-building, and review-schema helpers. It does not call models,
delegate Agents, resolve artifacts, or inspect images from Python.
Inputs
Require a one-sentence claim, target width in millimetres, and concrete
project-relative or absolute data paths. Never use artifact ids as paths. For an
existing figure, inspect the real image with view_image and write the outline
yourself; pixels cannot reveal the source data path.
Workflow
- Build an outline matching
figure_outline_schema(). Put real paths indata_path; usenullfor schematics. - Make panel
athe conceptual hook and panelbthe primary evidence. Use a 12-column grid and one row per sub-claim. - Build one instruction per panel with
panel_task(...). - If
delegate_tasksis advertised, submit the independent panel tasks as one batch. Grant each task the minimum advertised capabilities needed, normallyvisualizationplusproject_read. Require a concrete PNG filename in each output schema. If delegation is unavailable, render the panels sequentially withpython. - Compose returned paths with
compose_figure(...). Do not pass placeholder markers to the composer. - Use
compose_crops(...)with Pillow to save temporary crop files, then callview_imageon the composite and every crop. Fix seams, clipped labels, aliases, empty space, and misplaced panel letters before review. - Build one reviewer instruction with
composite_review_task(...). Delegate it withimage_inspection,project_read, andreasoningwhen those capability ids are advertised; otherwise perform the review in the current Agent. - Apply outline revisions and regenerate only affected panels. Stop after three rounds or when there are no blockers and at most two major findings.
Outline example
{
"claim": "Treatment restores the disease-associated trajectory.",
"width_mm": 180,
"ncol": 12,
"row_heights_mm": [42, 60],
"panels": [
{
"letter": "a",
"role": "schematic",
"row": 0,
"col": 0,
"colspan": 12,
"chart_family": "study schematic",
"message": "The experiment tests trajectory rescue.",
"data_path": null,
"ask": "Show cohorts, treatment, sampling, and comparison."
},
{
"letter": "b",
"role": "primary",
"row": 1,
"col": 0,
"colspan": 12,
"chart_family": "trajectory plot",
"message": "Treatment moves cells toward the healthy trajectory.",
"data_path": "results/trajectory.csv",
"ask": "Plot disease, treated, and healthy cells with confidence bands."
}
]
}
Boundaries
- Use
delegate_tasksonly as an explicit Wisp tool; never call delegation frompython. - Use
view_imageonly on a concrete local image file. - Keep data preparation in normal project files. Use
run_in_contextonly when a deterministic render or preprocessing job is long enough to require a persisted Run; Agent delegation itself is not a Run. - Save the accepted composite to a stable project path and report that path.
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