---
name: figure-composer
description: '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`.'
license: Apache-2.0
---

# Figure Composer — narrative → panels → compose → adversarial loop

`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.

## Open-Science Notebook call

Every `notebook_execute` request whose `code` uses a function named in this skill
includes this skill ID:

```json
{ "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.

## Inputs

- `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.

## Entry points

- **From a claim:** Main writes the outline in step 1 from the claim, data, and
  `figure-style` rules.
- **From an existing figure:** inspect it with `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.

## 1. Narrative → panel outline

Main produces a `panel_outline` matching `figure_outline_schema()`:

```json
{
  "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:

- A is the context-free hook: schematic or hero, normally full width.
- B carries the claim: it should make the sentence true on its own.
- Remaining panels add evidence in descending importance.
- Use one row per sub-claim, normally 5–10 panels, and a 12-column grid.
- Every non-schematic `data_vid` must be one of the supplied immutable Version
  identities. Do not invent or rewrite Version IDs.
- Set `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.

## 2. Fan out panel workers

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:

```javascript
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.

## 3. Compose and bind the producer Run

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:

```javascript
{
  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.

## 3.5 Look before review

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:

```javascript
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.

## 4. Adversarial review loop

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:

1. Accept when the verdict is `accept` or `minor_revision`, there are no
   `BLOCKER`s, and there are at most two `MAJOR`s.
2. Save `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.
3. Call `group_fixes_by_panel(review)` and compute
   `regen = (affected | set(fixb)) & {p["letter"] for p in outline["panels"]}`.
4. Regenerate only `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`.
5. Keep every clean panel's exact Version identity. Compose a new revision with
   a fresh producer child only after every regenerated panel passes the same
   identity checks. Review only that new composite Version.

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.

## Anti-patterns

- Do not regenerate clean panels.
- Do not manufacture findings.
- Verify review anchors on the composite, not only on isolated panels.
- Remove labels that a reader with field context would find redundant.