Paper narrative

Use this skill before figure-composer. The sidecar only builds schemas and self-contained reviewer instructions. Model reasoning happens in the current Agent or an explicitly delegated Wisp Agent, never inside Python.

Workflow

1. Read the abstract, introduction, captions, and concrete figure paths.
2. Build an instruction with paper_brief_task(...). Produce a brief matching paper_brief_schema() in the current Agent. If delegate_tasks is advertised, the brief may instead be assigned to one reasoning task with a structured output schema.
3. Review the entire brief. Preserve supplied composite_path values and fix unsupported claims before continuing. The brief and review instructions include JSON figure records so each path stays associated with its claim; keep those records when delegating, including paths with spaces or Unicode.
4. If the deck is a PDF, use pdf-explore to render the relevant pages to local images. Pass their concrete paths to narrative_review_task(...).
5. Inspect the images with view_image. Optionally delegate one handling-editor task with the minimum advertised reasoning, project_read, and image_inspection capabilities and narrative_review_schema().
6. Act on the result:
   • use arc as the main-figure order;
   • apply figure_moves;
   • turn missing_panels into explicit analyses;
   • demote or remove the kill_list;
   • send boldest_defensible_fig1 to figure-composer.
7. Re-review the revised deck. Converge when the hook verdict is yes and no figure moves or missing panels remain.

Use run_in_context only for deterministic analyses requested by missing_panels. Narrative reasoning and Agent delegation are not Runs.

Boundaries

• Do not pass artifact markers where a path is required.
• Do not call another model from python.
• Do not claim the deck was inspected unless every relevant page was rendered and viewed.