Paper Narrative

Paper Narrative — manuscript → brief → figure arc → editorial loop

paper-narrative is the outermost figure workflow. It judges the paper-level story before figure-composer designs any one figure. The inputs are the work itself: a manuscript (or abstract), figure captions, and the current full deck.

Open-Science Notebook call

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

{ "kernelSkillIds": ["paper-narrative"], "code": "print(paper_brief_schema())" }

kernelSkillIds contains the skill ID; function calls belong in code. This request is complete as written: call the named functions directly and do not add an import or discovery step.

Required inputs and trust labels

Keep these inputs distinct throughout the workflow:

• manuscriptVersionId: immutable manuscript Artifact Version (an abstract-only manuscript is allowed) and the reviewed manuscript text read from it.
• abstractText: reviewed abstract text when available; use it for bounded brief reasoning while retaining the full manuscript Version as source provenance.
• captionsVersionId: immutable captions Artifact Version and the reviewed per-figure caption or claim text read from it.
• deckVersionId: immutable deck Artifact Version containing every current figure in review order.
• rulesVersionId: immutable design-rules Artifact Version, used only as a reference so the editor judges story rather than visual craft.
• figureDataVersionIds: immutable data Artifact Versions grouped by figure.
• figureWidthMmByFigure: reviewed positive venue width for each figure; the downstream composer must not invent this physical output constraint.

Manuscript, captions, deck, and data are source inputs. Every brief, review, arc, move, omission, and proposed analysis is model-generated and requires human review. Never describe generated text as manuscript evidence or source data. Preserve the input Version identities when publishing or delegating downstream work.

1. Reason from manuscript and captions

Load the reviewed manuscript/abstract and captions content into the JavaScript control-plane request. Obtain paper_brief_schema() in Python first. Then call the current tool-less Host model and require JSON only:

const briefSchema = paperBriefSchemaFromNotebook
const Ajv2020 = require('ajv/dist/2020').default
const validateBrief = new Ajv2020({ allErrors: true }).compile(briefSchema)
const briefSourceText = abstractText || manuscriptText
let repair = ''
let brief
for (let attempt = 1; attempt <= 2; attempt += 1) {
  const prompt =
    `Return JSON only. The complete paper_brief JSON Schema is:\n${JSON.stringify(briefSchema)}\n` +
    `Manuscript Artifact Version: ${manuscriptVersionId}\n` +
    `Captions Artifact Version: ${captionsVersionId}\n` +
    `Reviewed abstract/manuscript source:\n${briefSourceText}\n\nCaptions/claims:\n${captionsText}\n\n` +
    `Pitch is the grandest supportable one-sentence claim, not the method. ` +
    `Vision is the killer application: what readers can now do. ` +
    `Name the audience and the single most-arresting image.` +
    repair
  if (Buffer.byteLength(prompt, 'utf8') > 64 * 1024) {
    throw new Error(
      'paper brief prompt exceeds host.llm 64 KiB UTF-8 limit; provide a reviewed abstract or shorter captions'
    )
  }
  const briefDraft = await host.llm(prompt)
  if (briefDraft.stopReason !== 'end_turn') {
    throw new Error(`paper brief inference stopped with ${briefDraft.stopReason}`)
  }
  let candidate
  let problem
  try {
    candidate = JSON.parse(briefDraft.text)
    if (validateBrief(candidate)) {
      brief = candidate
      break
    }
    problem = JSON.stringify(validateBrief.errors)
  } catch (error) {
    problem = error instanceof Error ? error.message : String(error)
  }
  if (attempt === 2) throw new Error('invalid paper brief after corrective retry')
  repair =
    `\nPrevious response was invalid: ${problem}. Repair it and return JSON only. ` +
    `Previous response:\n${briefDraft.text.slice(0, 8000)}`
}

host.llm does not enforce a caller-provided schema. The code therefore checks the UTF-8 request budget, requires stopReason === "end_turn", parses JSON, and validates with the same bundled Ajv 2020 implementation used elsewhere in the control plane. Prefer the reviewed abstract because a full manuscript commonly exceeds the hard 64 KiB prompt limit; never silently truncate source text. If a corrective retry still fails, stop. Do not fill missing required fields with guesses. After validation, attach the immutable figure/data references from the source claim table. Then review every field — pitch, vision, audience, most-arresting asset, and every figure claim — before continuing. Fix unsupported wording explicitly; never silently treat the first model draft as approved.

2. Review the full deck as a handling editor

Generate the task with narrative_review_task(reviewedBrief, deckVersionId, rulesVersionId) and obtain narrative_review_schema() in Python. Dispatch one reviewer from repl_execute. All three work inputs are explicit alongside the deck; the schema makes the expected model result reviewable:

const collectStructuredBatch = async (requests) => {
  const receipts = await host.delegate(requests, { wait: false })
  const children = await host.collect(
    receipts.children.map(({ frameId, attemptId }) => ({ frameId, attemptId })),
    { returnWhen: 'all', timeoutSeconds: 1800 }
  )
  return children.map((child) => {
    if (!child || child.status !== 'completed' || child.error) {
      throw new Error(
        `delegated workflow failed: ${child?.error ?? child?.status ?? 'missing child'}`
      )
    }
    if (child.structuredOutputUnsatisfied || child.structuredOutput === undefined) {
      throw new Error('delegated workflow returned no schema-valid structuredOutput')
    }
    return child.structuredOutput
  })
}

let narrativeRound = 1
const request = {
  name: `paper-narrative-editor-r${narrativeRound}`,
  task: reviewTask,
  inputs: [manuscriptVersionId, captionsVersionId, deckVersionId, rulesVersionId],
  outputSchema: reviewSchema
}
const [review] = await collectStructuredBatch([request])

Require a completed child and a schema-valid result. Human-review the result as an editorial recommendation, not a fact extraction. Preserve all of the original narrative judgments:

• hook_verdict: whether Figure 1 alone earns external review, why, what it is, and what it should become.
• arc: hook → mechanism → evidence → application; off-arc material moves to supplement unless a reviewed exception is justified.
• figure_moves: panels whose correct figure changes, with the reason.
• missing_panels: what to show, the concrete analysis to run, and the closest source-data hint. Search existing project artifacts before proposing new work.
• kill_list: content to demote to supplement/caption or delete.
• boldest_defensible_fig1: the strongest supportable Figure 1 claim, never a merely louder unsupported claim.

3. Hand the reviewed arc to figure-composer

After human review, build root-level composition specifications only for arc figures that actually need a visual revision. A figure needs recomposition when it gains or loses a moved panel, receives an accepted missing-panel analysis, has no existing composite_vid, or its reviewed claim/layout differs from the current figure. Record any additional human-approved layout changes in explicitlyReviewedRecomposeFigures; do not treat a new narrative order alone as a reason to redraw a figure. Reuse the exact existing composite_vid for every untouched figure. Do not delegate the whole figure-composer: delegated children cannot call host.delegate, while the composer must fan out panel workers. Remain in the Main/root agent, load figure-composer, and complete its workflow for each changed specification in review order. Each specification must include:

1. that entry's exact reviewed one_line claim;
2. every reviewed moved-in panel whose to_fig matches the arc figure and every moved-out panel whose from_fig matches it, so the source composition removes the transferred material;
3. the immutable data Artifact Version references grounding the claim and moved panels; and
4. any accepted missing-panel analysis result after it has actually been run and published as an Artifact Version; and
5. the reviewed physical width_mm for that figure.

Build inputs as an order-preserving union: the target figure's source-data Versions, every moved item's from_fig source-data Versions, and the published missing-analysis Versions for the target. Deduplicate identities. A brief figure's composite_vid identifies rendered figure output; it is not source data and must never be substituted for these input references.

After the human decision and analysis run, keep the independently reviewed acceptedMissingPanelRecommendations. Populate publishedMissingAnalysisVersionIdsByRecommendation only from successful Artifact writes, then map every accepted recommendation to its published Version. Each resolved entry carries the reviewed target_fig, what_to_show, and exact version_id. Fail closed if any accepted recommendation has no verified published Version; never derive redraws directly from all model-proposed review.missing_panels.