Write

Write

Match Signals

• Use when an accepted baseline and at least one meaningful result already exist, and the main blocker is now drafting, revising, bundling, or tightening a paper/report.
• Strong triggers: draft a paper/report, revise a section, synchronize claim-evidence support, prepare a paper bundle, or upgrade an existing draft into a stronger conference submission.
• If the task is specifically "upgrade an existing draft toward top-conference / oral quality", use the Draft To Top Conference Oral section below.
• Do not use when the evidence base is still weak or unstable, the main need is new experiments / baselines / ideation, or the request is only literature search.

One-Sentence Summary

• Refresh the paper contract first, then draft section-by-section from durable evidence; if evidence, figures, or citations are not ready, repair or route back instead of writing around the gap.

Pre-write Revision Strategy Gate

Before editing a manuscript, first produce a concrete revision strategy from the current evidence state. Do not begin polishing prose until the strategy separates:

• evidence gaps: require new analysis, rerun, or claim downgrade
• manuscript-mapping gaps: completed results missing from main text, table, figure, or appendix
• unsupported writing: claims present in the draft without durable result artifacts
• narrative / positioning gaps: weak framing, novelty boundary, contribution logic
• citation gaps: too few or weak references for the claimed scope
• metadata drift: matrix, ledger, outline, figures, tables, and manuscript disagree

For each issue, choose exactly one action:

• run or request analysis
• downgrade or remove the claim
• add result to main text
• move result to appendix with a clear bridge
• add or repair a table/figure
• add verified citations
• repair the paper contract before writing
• route to review / decision instead of writing

Never make an unsupported claim sound more convincing. If evidence is missing, either obtain evidence, narrow the claim, or mark the blocker.

Workflow

1. Refresh control state first. Run memory.list_recent(scope='quest', limit=5) plus one writing-relevant memory.search(...). If restart context is unclear, use artifact.get_quest_state(detail='summary'), artifact.read_quest_documents(...), or artifact.get_conversation_context(...).
2. Lock the paper contract before heavy prose. Keep paper/selected_outline.json, paper/evidence_ledger.json, and paper/paper_experiment_matrix.md or .json aligned. Use artifact.get_paper_contract(detail='full') as the default paper-reading surface when section rows, experiment rows, or analysis rows matter. Use artifact.get_paper_contract_health(detail='full') when outline state, experiment rows, or evidence ownership may be stale. Use artifact.submit_paper_outline(mode='candidate'|'select'|'revise', ...) instead of leaving outline choice only in prose. When several paper shapes are plausible, record one or more outline candidates with artifact.submit_paper_outline(mode='candidate', ...), then select or revise explicitly with artifact.submit_paper_outline(mode='select'|'revise', ...); do not force extra outline rounds once the selected outline is good enough for the current writing job.
3. Validate the outline before drafting. Run artifact.validate_academic_outline(detail='full'). If it fails, use paper-outline or artifact.submit_paper_outline(mode='revise', ...) to repair the paper idea, claims, evidence boundaries, and analysis plan before prose work. When it passes, run artifact.compile_outline_to_writing_plan(detail='full') and draft from those jobs.
4. Sort source material before drafting. Ask: is this a claim, an experiment setting, a reproducibility detail, implementation plumbing, artifact history, or a user/operator instruction? Claims and experiment settings may become manuscript text. Reproducibility details usually go to appendix. Artifact history and user/operator instructions should not appear in the manuscript.
5. Refresh literature and citation truth. Run breadth -> shortlist -> depth. Use DeepXiv or OpenAlex for discovery when available, then retrieve BibTeX from DOI or arXiv, not from memory. Keep paper/references.bib machine-usable and audit it before bundle submission. If DeepXiv is declared available by the system prompt, prefer it for paper-centric discovery and shortlist triage before broad web search when it can answer the question directly. If DeepXiv is declared unavailable, do not try to force it; stay on the legacy route. Use artifact.arxiv(paper_id=..., full_text=False) for actual arXiv paper reads before escalating to full text.
6. Plan displays before prose. If a section needs a paper-facing measured figure, use paper-plot first. Use figure-polish only after a durable first-pass render exists. Sync resulting figure paths and takeaways back into paper/evidence_ledger.json, paper/paper_experiment_matrix.md, and the draft.
7. Route Nature companion work by paper surface. Open a nature-* skill only after the current section job, evidence rows, and unresolved fields are known. Use the companion skill to produce a bounded section/figure/deck deliverable, then return to write to integrate it into the draft, evidence ledger, figure/table catalog, references, and bundle status.
8. Draft by section jobs, not one long stream. Write introduction / related work / method / experiments / analysis / conclusion as separate jobs. Write the abstract late, after evidence order and section roles stabilize. For oral-grade upgrades, follow the Draft To Top Conference Oral section below.
9. Validate before output and route if needed. Refresh claim-evidence, packaging, appendix bridges, artifact.validate_manuscript_language(detail='full'), and artifact.validate_manuscript_coverage(detail='full'). A short memo is only artifact.submit_paper_bundle(package_type='draft_checkpoint', ...); use submission_package only when submission_ready=true.

Paper Quality Reminder

Do not let structural readiness stand in for paper quality.

• Compile success, section count, figure/table count, and draft_checkpoint_ready mean only that a package exists.
• A mature empirical draft needs a reader-facing thesis, central insight, scoped claims, novelty boundary, reviewer objections, and a mapped analysis plan from paper-outline.
• Before calling a full manuscript strong, check the actual ready experiment/analysis group count from artifact.validate_manuscript_coverage(detail='full').
• Normally expect 5-10 ready paper-facing experiment/analysis groups total; if the user asked for a concrete count such as 4-8 analyses, treat that as the active tracked target.
• If the count is below the target, either route to analysis-campaign, write an explicit analysis-budget waiver that downgrades the paper scope, or narrow the claims. Do not hide the shortage with prose.
• If duplicate item ids, stale outline refs, or pending main-text rows inflate the count, repair the paper contract before writing claims from those rows.
• Apply the publishability stop-loss rule: if the current evidence, novelty boundary, or reader value cannot support a defensible paper after reasonable claim narrowing, stop drafting and route to decision for a recommended stop or branch; record any narrowed non-paper objective as the next direction. If the recommended action is stop because paper quality is too low, ask the user to confirm before ending the paper objective. Consider user publication, scope, cost, or non-paper preferences before routing, and ask when the preference would change the route. Do not use polished prose to keep an unpublishable paper line alive.

Tool Use

• artifact.get_paper_contract_health(detail='full'): use when a weak section may actually be caused by stale outline state, unresolved experiment rows, or unclear evidence ownership.
• artifact.get_paper_contract(detail='full'): use by default before drafting any section, table, or analysis prose that depends on concrete main-experiment rows, analysis rows, or section-level result_table content.
• artifact.validate_manuscript_coverage(detail='full'): use before bundle submission or finalize; it checks sections, displays, ready analysis groups, PDF, and checklist state.
• artifact.validate_academic_outline(detail='full'): use before serious drafting; it checks whether the outline has a paper idea, scoped claims, evidence boundaries, method, evaluation plan, and enough planned analyses.
• artifact.compile_outline_to_writing_plan(detail='full'): use after the outline is valid; it turns the outline into section-level writing jobs.
• artifact.validate_manuscript_language(detail='full'): use after major prose edits and before submission; it catches route/user/worktree/port/batch wording that should not be in main text.
• artifact.get_quest_state(detail='summary'), artifact.read_quest_documents(...), artifact.get_conversation_context(...): use when restart context is unclear, when exact durable wording matters, or when you need file truth instead of chat recollection.
• artifact.submit_paper_outline(mode='candidate'|'select'|'revise', ...): use when outline choice or outline repair becomes durable enough that the paper line should follow it.
• artifact.create_analysis_campaign(...): use only when a real paper-facing evidence gap needs follow-up analysis; do not use it for prose cleanup, citation chores, or generic "improve the paper" tasks.
• artifact.submit_paper_bundle(...): use explicit package_type: draft_checkpoint, review_package, or submission_package only after coverage is submission-ready.
• artifact.interact(...) or other durable artifact updates: use when the writing pass materially changes paper status, route choice, or bundle readiness and the change should survive beyond chat.
• bash_exec(...): use for any real shell/CLI work such as LaTeX compile, bibliography checks, rg/find/ls, figure-generation scripts, PDF render/proofing, git inspection, or reproducibility checks. Do not describe command plans as if they ran; run them through bash_exec when execution is actually needed.
• memory.list_recent(...) and memory.search(...): use at the start of substantial writing passes, before route changes, and before repeating search or drafting patterns that may already have reusable lessons.
• memory.write(...): use only for reusable lessons such as citation retrieval rules, packaging traps, figure-integration lessons, or section-rewrite heuristics; do not store one-off draft text, transient wording, or current-section notes that should live in files.

Interaction Discipline

Follow the shared interaction contract injected by the system prompt. For ordinary active work, prefer a concise progress update once work has crossed roughly 6 tool calls with a human-meaningful delta, and do not drift beyond roughly 12 tool calls or about 8 minutes without a user-visible update.

AVOID / Pitfalls

• Do not start with background explanation or overview prose; start with contract health, section job, and evidence state.
• Do not keep drafting while outline, evidence ledger, or experiment matrix are stale.
• Do not treat paper_contract_health as a substitute for reading the actual section result_table, evidence rows, or experiment-matrix rows.
• Do not draft around missing evidence, unstable baselines, or unresolved non-optional experiment rows.
• Do not hand-write BibTeX, citations, metrics, or method details from memory.
• Do not improvise a new plotting stack inside write when paper-plot should own the first-pass figure.
• Do not use nature-polishing to make unsupported, stale, or overbroad claims sound stronger.
• Do not use nature-data to invent repositories, accession numbers, DOIs, licences, embargoes, access committees, or ethics approvals.
• Do not use nature-paper2ppt unless the user asked for an actual presentation deck.
• Do not merge experiments and analysis into one undifferentiated result dump when they need distinct reviewer-facing jobs.
• Do not treat evidence_ready or analysis_ready as equivalent to manuscript_ready or submission_ready.
• Do not submit a paper-shot memo as a final paper package; checkpoint it and continue writing/review.
• Do not use rows that are not clearly bound to the current selected_outline_ref / active paper line.
• Do not keep revising a paper line whose publishability has collapsed; record the blocker and route to decision instead of accumulating more draft text.
• Do not keep appending new material to the top control block until it turns back into prose-heavy documentation; keep the top short and use the longer guidance below only when the task actually matches it.
• Do not paste or paraphrase user requests, route decisions, branch/worktree state, checklist language, command names, prompt state, or artifact-management history into manuscript prose.
• Do not write phrases such as the user requested, the latest user requirement, paper restart, this quest, the agent, the worktree, we were told, he accepted, paper should, or remaining work on this manuscript inside a paper draft.
• Do not use arithmetic endpoint/batch shorthand such as 64 + 64 or 64+64 in manuscript prose, titles, abstracts, captions, or conclusions.
• Do not let figure captions contain tool recommendations, website promotion, TODOs, or polish notes.

Constraints

• Keep these files aligned when they exist: paper/selected_outline.json, paper/evidence_ledger.json, paper/paper_experiment_matrix.md or .json, paper/references.bib, paper/claim_evidence_map.json, paper/paper_bundle_manifest.json.
• If a section depends on experiment or analysis evidence, draft from the current paper contract rows, not from remembered summaries.
• If method, system, or implementation details are mentioned, treat the current codebase, configs, scripts, logs, and durable outputs as the primary truth surface; comments, plans, TODOs, and old draft wording are only hints until verified.
• User requirements and control files are allowed to constrain the writing route, but they are not evidence and are not manuscript text.
• Main text should usually describe serving and evaluation setup as a benchmark, comparison budget, evidence source, or evaluation protocol, not as local operator configuration. If exact throughput settings matter, put them in an appendix or reproducibility table.
• Any shell, CLI, Python, bash, node, git, npm, uv, LaTeX, or file-inspection execution in this stage must go through bash_exec(...).
• Use artifact.create_analysis_campaign(...) only for real paper-facing evidence gaps, not for prose cleanup or citation chores.
• Use artifact.submit_paper_bundle(...) only after draft, bibliography, and bundle metadata are durable enough to hand off.
• A mature empirical paper usually needs 5-10 paper-facing experiment/analysis groups unless scoped otherwise; if fewer, justify or route to analysis-campaign.
• A user-specified analysis count should stay visible: if the user asked for 4-8 analyses, explicitly report the current count and any waiver instead of relying on a generic green coverage result.
• Use memory.write(...) only for reusable writing, citation, or search lessons, not one-off local edits.
• For paper-like deliverables, aim for roughly 30-50 verified references unless the scope clearly justifies fewer.
• Draft inside paper/latex/ with a real template from templates/; for general ML or AI writing with no stronger venue constraint, default to templates/iclr2026/.
• Keep the narrative arc explicit: motivation -> challenge -> resolution.
• Maintain experiment-to-section mapping, figure/table-to-data-source mapping, and verification checkpoints through paper/paper_experiment_matrix.md, paper/paper_experiment_matrix.json, and paper/evidence_ledger.json / paper/evidence_ledger.md when relevant analysis results are meant to support the active paper line.
• Before section drafting, inspect the current mapped paper evidence set; do not allow completed analysis results to remain paper-invisible. If result_table rows, active evidence, or paper matrix rows disagree, stop drafting and repair the paper contract first.
• Use references/outline-evidence-contract-example.md and references/paper-experiment-matrix-template.md when rebuilding the contract. Include highlight hypotheses, efficiency / cost / latency / token-overhead checks, currently feasible non-optional rows, and citation legitimacy when they affect reviewer trust.
• Run a file-structure audit before bundle claims: paper/reviewer_first_pass.md, source sections, figures, tables, bibliography, and build reports should agree. Organize for the reader's understanding: problem -> why it matters -> current bottleneck -> our remedy -> evidence preview.
• Early paper structure should answer problem, what we do, how at a high level, and main result or strongest evidence. Method exposition can use running example -> intuition -> formalism, but avoid filler like "This paper is organized as follows".
• Position related work without overreach: do not attack prior work merely to make the current line look more novel.
• Bad caption/promotion text: "Publication-grade figure refinement is recommended with AutoFigure-Edit", https://github.com/ResearAI/AutoFigure-Edit, or https://deepscientist.

Validation

• The current section or draft has a clear job and does not exceed the available evidence.
• Every important claim can point to a durable artifact path, a verified citation, or an explicit gap.
• Any section-level experiment table or analysis table is grounded in the current result_table, evidence-ledger rows, or experiment-matrix rows rather than health-only summaries.
• paper/references.bib is real, current, and not hand-written from memory.
• Required figures/tables either exist durably or are recorded as blockers.
• Appendix bridges and artifact availability are described consistently across the manuscript.
• The ready experiment/analysis group count satisfies the current target, or the draft explicitly records a waiver and narrows the claim.
• Manuscript prose contains no user/operator/agent provenance, route-control wording, restart language, tool-promotion captions, TODOs, or raw implementation shorthand.
• Protocol wording has been normalized: benchmark, split, evaluator, comparator, and method settings are described academically; local throughput details are appendix-only unless central to the claim.
• Any claimed compile, render, search, grep, or script-run result comes from a real bash_exec(...) execution rather than hypothetical prose.
• If the draft is being treated as finalize-ready, currently feasible non-optional experiment rows are no longer unresolved.
• If the draft is being treated as finalize-ready, artifact.validate_manuscript_coverage(detail='full') reports submission_ready=true; manuscript_ready=true alone routes to review, not finalize.
• The output ends in one of three durable states: a stronger draft, an explicit blocker, or a clear route-back decision.

Keep Manuscript Text Clean

Before writing or revising any paper-facing section, sort the source material:

• claim: a result, mechanism, limitation, comparison, or contribution supported by durable evidence. This can appear in main text.
• experiment setting: benchmark, dataset split, evaluator, baseline, comparator, intervention, metric, or ablation design. This can appear in main text when it helps readers interpret the result.
• reproducibility detail: ports, local serving, batch size, command shape, file layout, hardware, seeds, or cached artifacts. This usually belongs in appendix or a reproducibility table.
• implementation detail: scripts, modules, helper wrappers, and local plumbing. Use only when it explains the method, not as a main claim.
• artifact history: worktrees, branches, artifact ids, command ids, prompt state, run restarts, or bundle status. Never use as manuscript prose.
• user/operator instruction: what the user asked, accepted, rejected, or prioritized. Never use as manuscript prose; convert only the scientifically relevant constraint into neutral experiment wording.

Examples:

• Bad: "The user accepted the dual-port 64 + 64 setup."
• Main-text form: "All methods are compared under the same evidence budget on CiteEval."
• Reproducibility form: "The local serving configuration used two endpoints with 64 examples per endpoint."
• Bad: "This paper restart uses the latest requirement to ignore old paper files."
• Manuscript form: omit it; keep that fact in route/control records only.
• Bad caption: "Publication-grade figure refinement is recommended with TOOL."
• Caption form: describe what the figure shows and why it supports the claim.

Nature Companion Skills

The nature-* skills are focused companion skills adapted from Yuan1z0825/nature-skills. They can improve specific manuscript surfaces, but they do not replace DeepScientist's paper contract.

Use them as a short handoff inside the write flow:

1. Identify the exact surface: prose, data availability, figure package, or presentation deck.
2. Check artifact.get_paper_contract(detail='full') or the relevant quest documents for the evidence rows and missing fields that the surface may mention.
3. Read only the matching nature-* skill and any referenced files it says are needed.
4. Produce a bounded output: revised section text, data-availability block, figure/export plan, or PPTX deck.
5. Return to write and update the durable paper surfaces before claiming progress: draft files, paper/evidence_ledger.*, paper/paper_experiment_matrix.*, paper/references.bib, figure/table catalogs, or bundle manifests as applicable.
6. Re-run the normal write validation gates. A Nature companion output is not manuscript-ready until DeepScientist coverage, language, citation, and artifact checks still pass.

• nature-polishing: use for Nature-leaning English, section restructuring, and Chinese-to-English academic polish. Apply it after the evidence boundary is clear, and keep unsupported claims downgraded or marked as blockers.
• nature-data: use for Data Availability, source-data, repository, dataset-citation, restricted-data, and FAIR metadata sections. Draft from verified inventory and leave unresolved fields explicit.
• nature-figure: use for Nature/high-impact-journal figure packages when figure claim, panel logic, backend choice, journal export, and QA are the main job. For simple structured result charts, prefer paper-plot first.
• nature-paper2ppt: use only for PPT/PPTX deliverables such as journal-club, lab-meeting, or paper-sharing decks. The expected output is a real deck plus lightweight verification.

Routing examples:

• Result paragraph reads flat but evidence is solid -> read nature-polishing, revise only the section job, then validate claim-evidence support.
• Data Availability is missing or vague -> read nature-data, inventory datasets and repositories, draft unresolved fields explicitly, then sync the section and references.
• A main figure must satisfy Nature-style multi-panel export expectations -> read nature-figure; if the job is only a simple result chart, stay with paper-plot plus figure-polish.
• User asks for a journal-club deck from a paper -> read nature-paper2ppt; keep it outside the manuscript bundle unless the user asks to attach it as a deliverable.

Potentially Reference-Worthy, Code-Grounded Facts

• Implementation surfaces can be worth citing in prose when they are verified from the current repo state: entrypoints, module boundaries, dataflow stages, control loops, evaluator wiring, and ablation switches that materially affect the claim.
• Config truth can be worth citing when it changes interpretation: actual loss terms, objective weights, decoding or inference settings, comparison toggles, dataset filters, and default runtime modes taken from checked configs or scripts.
• Reproducibility and trust details can be worth citing when they are real: executable scripts, artifact paths, checkpoint conventions, dependency constraints, hardware assumptions, and run-time limits that the current code or logs actually expose.
• Failure-boundary details can be worth citing when they are visible in code or artifacts: guardrails, unsupported regimes, fallback paths, assertions, evaluator exclusions, or branch-specific limitations that materially narrow the claim.
• Concrete traces can be worth citing when they are generated artifacts rather than imagination: logs, examples, case-study outputs, prompt traces, or render outputs produced by the current code path.
• If a detail is only present in comments, TODOs, planning notes, stale branches, or remembered conversation, do not write it as fact.
• If code and manuscript wording disagree, resolve to code plus durable outputs first, then rewrite the manuscript to match.
• If a path exists in code but was not exercised by the evidence package, label it as implemented or available, not as experimentally validated behavior.

Reference Routing

• Read references/oral_package_patterns.md when the draft needs a clearer oral-style evidence package.
• Read references/oral_writing_principles.md when the narrative spine, reader onboarding, or reviewer-facing tone is weak.
• Read references/experiments_analysis_patterns.md when experiments and analysis need clearer job separation.
• Read references/section_rewrite_checklist.md before treating a rewritten section as stable enough for bundling or review.

Draft To Top Conference Oral

Overview

Use this skill when a paper already exists in draft form and the real problem is not "write a paper from zero" but "turn this draft into something that reads like a top-conference oral paper."

This skill is for the transition:

• from dense draft to memorable paper
• from correct content to reviewer-facing writing
• from result dump to staged evidence
• from overloaded pages to intentional pacing
• from LLM-like compression to human-like editorial judgment
• from isolated main text to a deliberate oral package with appendix support

Do not use this skill to invent missing evidence. If the draft has real evidence gaps, narrow claims or route to more experiments instead of hiding the weakness with better prose.

What This Skill Optimizes

This skill is specifically about oral-paper upgrade work, not generic prose cleanup. It optimizes:

• story spine and claim scope
• reader onboarding and early intuition
• evidence budget across main text and appendix
• figure and table role clarity
• division of labor between displays and prose
• experiments versus analysis separation
• trend-first, mechanism-aware data analysis
• reviewer-concern handling
• page pacing and readability
• limitations, reproducibility, and trust signaling

Read references/oral_package_patterns.md early when deciding what to add, cut, move, or split.

When to Use This Skill

Use this skill when:

• A full or partial scientific draft already exists
• The user wants to upgrade a draft to conference-ready or oral-quality writing
• The paper has results but the story, writing, figures, or analysis feel weak
• The draft reads like a compressed summary, lab note, or LLM reconstruction
• The task is to improve abstract, introduction, method explanation, result writing, figure/table communication, or analysis depth
• The user wants the paper to feel more like ICLR/NeurIPS/ICML/CVML oral quality
• Two paper versions exist and the job is to distill what made the stronger version feel more oral-ready, then reuse those patterns

Do not use this skill when:

• There is no meaningful draft yet
• The core task is literature search only
• The real blocker is missing experiments, missing baselines, or missing results
• The request is for formal peer review rather than revision and upgrade

Workflow

1. Audit the draft before rewriting

Read the current abstract, introduction, method, experiments, analysis, conclusion, and appendix if present.

Extract:

• C1-C3: the 1 to 3 core claims
• strongest current evidence
• weakest current evidence
• likely rejection reasons
• which parts are writing problems versus evidence problems

Classify the draft weakness into one or more of:

• story
• writing
• method exposition
• figure/table communication
• experiment analysis
• claim calibration
• reproducibility/trust signaling

If the main issue is evidence, do not proceed as if this were only a writing problem.

2. Build an oral delta map before line editing

Use references/oral_package_patterns.md to compare the current draft against an oral-ready target.

Label the biggest gaps. Typical gaps include:

• weak reader onboarding
• no early intuition or mechanism figure
• one page trying to carry too many claims
• tables acting as storage rather than argument
• experiments and analysis collapsed into one results block
• analysis that only repeats numbers without extracting the trend
• no memorable case study or failure-mode analysis
• appendix functioning as a dump instead of a supplement package
• claim language that extends beyond the strongest evidence zone
• artifact availability described inconsistently across sections

When two versions of the paper exist, explicitly write the delta:

• what the stronger version added
• which added elements improved persuasion rather than merely adding length
• which patterns are reusable in the current rewrite

3. Reallocate the evidence budget

Top-conference oral papers are not just more polished. They spend pages and displays where reviewer friction is highest.

Before rewriting paragraphs, decide:

• which figures or tables belong in the main text
• which evidence blocks should become standalone subsections
• what must move to appendix
• where to place the appendix bridge in the main text
• which exact facts live in displays versus surrounding prose
• which core claim or reviewer question each main-text display is responsible for defending
• whether method defense is taking budget away from objection handling

Default main-text priorities:

• one early intuition or mechanism figure
• one main result display
• one interpretive analysis or tradeoff display
• one practical-value or objection-handling block when it is central to the claim
• one memorable qualitative example or case-study display when available

If the paper's central claim is comparative, benchmark-driven, or baseline-beating, the "main result display" must stay competitor-inclusive.

That usually means:

• named baselines or nearest neighbors remain visible in the main text
• the metric spread needed to justify the comparative wording remains visible
• the reader can verify the claimed ranking or scope without reconstructing it from prose alone

Do not collapse a broad benchmark story into a self-only summary table if the prose still makes broad comparative claims.

When the gold oral package keeps both a compact setup or baseline taxonomy and a competitor-inclusive benchmark surface in main text, preserve both jobs in the rewrite. Do not jump straight from prose setup to compressed averages if the reviewer still needs to see who was compared, under which regime, and where the main ranking or boundary actually appears.

When the paper has multiple proof obligations, do not present them as one continuous "results" stream.

Instead, turn the main empirical body into explicit reviewer-question blocks, where each block has:

• one concrete question the reviewer would naturally ask
• one short setup line that states the regime or slice being tested
• one named baseline, counterfactual, or comparison target when the draft package or staged artifacts provide one
• one dominant display
• one dominant takeaway
• one explicit appendix bridge for overflow evidence
• a clear handoff to the next question

If the strong paper or staged package already separates a section into named internal jobs, preserve that internal scaffold in the rewrite.

Do not collapse those jobs into one continuous wall of prose when reviewers need to inspect them separately.

This is especially important for:

• related work sections that need a distinct closest-comparator contrast
• method sections that need separate blocks for workflow, component design, supervision, and action realization
• experiments sections that need visibly separate headline evaluation, transfer breadth, and mechanism-validation blocks

When the paper's credibility depends on first proving that a metric, proxy, or diagnostic predicts reviewer-relevant outcomes, allocate a standalone validation block before intervention or design-guidance blocks.

Do not bury that proof inside later intervention subsections or leave analysis with only mechanism commentary if the draft package signals validation as the bridge into the rest of the paper.

If the draft package or staged artifacts separate several intervention families, keep them separate in the rewrite.

Each intervention family should still preserve:

• its own setup line
• its own baseline or counterfactual when one exists
• its own dominant display
• its own headline result
• its own appendix bridge

If the evidence package carries multiple transfer fronts, keep at least one non-headline transfer benchmark or cross-setting validation in the main experiments section beyond the primary deployment or headline benchmark.

When the gold oral package uses multiple main-text displays to answer distinct reviewer questions, keep one explicit main-text boundary, robustness, or scope-setting display in addition to the headline comparison block. Do not push every non-headline empirical check into appendix overflow if the central claim still depends on visible claim-boundary evidence.

Only move exhaustive rows, per-task detail, and secondary checks to the appendix; do not narrow the main paper to one deployment table plus appendix overflow when the central claim depends on visible generalization breadth.

When the method makes a core claim operational, reserve method-local evidence for that claim.

For claims about open-ended actions, executable control, retrieval-grounding, tool use, or interaction loops, include at least one concrete method artifact when available:

• a compact code snippet
• a local worked example
• an input-output trace
• a method-local schematic
• a small table that makes the mechanism inspectable

Do not push all operational concreteness into experiments or appendix material.

Move exhaustive material to appendix:

• full result tables
• hyperparameter sweeps
• annotation protocol details
• extended examples
• extra proofs and implementation detail

Default appendix blueprint when the paper is mature enough:

• methodology overflow that defends setup, measurement choices, and regime inventory
• full-results overflow that keeps task-level or slice-level evidence inspectable
• enlarged-display overflow for figures, tables, and curves that reviewers may need to inspect closely
• literature overflow when related work has secondary breadth that would crowd the main text
• transfer-overflow evidence when main experiments keep the headline transfer block but not all transfer rows
• tuned baselines or sensitivity checks
• protocol transparency or prompt detail when the gold package uses them to make the empirical story auditable
• formal-properties or metric-support material when the main text relies on a new metric, proxy, or diagnostic
• qualitative examples
• failure cases
• separate compliance or broader-impacts support when the gold package keeps that job distinct
• reproducibility and artifact details

Before drafting, record which main-text section must point to each appendix bucket.

Method, experiments, and analysis should each know which overflow material they are delegating and where the bridge sentence will appear.

Related work should also know whether it needs a bridge to an extended-literature appendix lane.

Generic appendix references are not enough when the manuscript relies on overflow evidence for credibility.

Each important bridge should name a precise appendix destination such as:

• a labeled subsection
• a labeled table or figure
• a titled overflow lane that will later receive a stable label

Do not write only "see the appendix" when the claim depends on protocol detail, method implementation detail, transfer overflow, extended literature, or worked traces.

When compressing a strong paper, do not let the appendix degrade into a light method bridge.

The appendix should still look like a reviewer-support package with explicit jobs, especially when the main text has compressed:

• setup details that make comparisons interpretable
• extra analyses that answer likely objections
• qualitative or human-evaluation evidence
• supporting tables that defend the main claim's breadth

4. Rewrite the paper in oral-paper order

Top-conference oral papers stage information in the order that minimizes reviewer friction.

Rewrite in this order:

1. story spine
2. abstract and introduction
3. method and related work
4. main results
5. analysis
6. figures and tables with surrounding prose
7. conclusion, limitations, appendix bridge

When writing the paper in a sectioned workflow, use this concrete generation order:

1. section_plan
2. introduction
3. related_work
4. method
5. experiments
6. analysis
7. appendix
8. limitations
9. conclusion
10. abstract
11. integration

Use section_plan as an internal control document, not as manuscript prose. It should record:

• C1-C3
• which section owns the headline proof or validation burden for each main claim
• the chosen main-text display program
• the first-page evidence stack: at least one problem-scale anchor and one solution-shape anchor when staged artifacts support both
• likely reviewer objections
• the study regime inventory that must stay visible in main text
• the closest-work novelty boundary
• appendix overflow jobs
• the appendix bridge map from method, experiments, and analysis into those jobs
• any related-work-to-appendix bridge lane
• any non-headline transfer benchmark that must remain in main text
• any method-local operational artifact that must not be demoted
• any closest-comparator contrast that must remain explicit in related work
• any section-internal scaffold that must survive compression
• the exact appendix labels or label candidates each main-text bridge should point to
• any analysis taxonomy terms that must be defined before interpretation
• one concise job description for each section
• which concrete staged displays or authored tables will answer each objection

Write the abstract last, after the paper's actual evidence order has stabilized.

In sectioned mode, keep main.tex as the canonical top-level document and keep body prose in separate section files. Do not collapse the manuscript back into one giant draft while writing. Use the final integration pass only to repair consistency, sharpen transitions, synchronize claim wording, and remove staging artifacts from the prose.

Do not reserve essential evidence allocation for integration. Each body section should already be locally complete enough that an interrupted integration pass does not erase key reviewer-defense blocks or appendix bridges.

5. Apply oral-level writing rules

Use the principles in references/oral_writing_principles.md.

The most important rules are:

• optimize for reader guidance, not maximum compression
• every section must have a job
• every paragraph should do one main thing
• signpost transitions explicitly
• explain why a result matters, not only what the number is
• let displays carry detailed values whi

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