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Research Publication Pipeline

SkillDev tools

Use when selecting, starting, or resuming an evidence-gated research route for a top computer-science venue or Nature-family journal; source-grounded paper reading, AI-for-biology data feasibility, scoop checks, venue fit, baseline headroom, frozen protocols, controlled iterations, claim locking, negative-result handling, preparing a full working manuscript with figures, or curating a reproducible public code release. The workflow completes its local research-to-manuscript scope without another skill; compute, locked-test access, canonical mutation and external writes require their own authorization.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Research Publication Pipeline skill

What this skill tells your AI

The instructions your AI receives, as published by gxcaesar/open-research-skills in skills/research-publication-pipeline/SKILL.md and read by ahel’s review.

Turn a research idea into a sequence of falsifiable decisions. Keep feasibility, novelty, contribution lane, venue fit, empirical headroom, and final claim support separate. A polished story cannot substitute for a failed gate.

This public edition is a human-facing scientific workflow. It does not contain a remote launcher, private infrastructure, opaque control state, or publication automation.

Select one mode

ModeResponsibilityRead first
surveyMap papers, data, task definitions, current incumbents, failure modes, credible contribution routes, or publication patterns under a bounded search or supplied corpusreferences/survey-and-planning.md; add the paper-card component for one source or references/exemplar-corpus-calibration.md for a multi-paper exemplar corpus
planFreeze the project charter, lane, hypothesis, decision-relevant checks, resources, and stop rulesreferences/survey-and-planning.md
pilotRun the smallest real-data test that can invalidate feasibility or the load-bearing premisereferences/pilot-and-monitoring.md
developMeasure headroom and test one registered mechanism at a time under the frozen protocolreferences/protocol-headroom-and-development.md
monitorObserve an authorized run from its outputs, detect anomalies, and separate progress from completionreferences/pilot-and-monitoring.md
freezeLock protocol and candidate, verify evaluation readiness, then protect the final test boundaryreferences/frozen-evaluation.md
claim-lockConvert the frozen result into supported, narrowed, refuted, and not-run claimsreferences/frozen-evaluation.md and references/evidence-claims-and-handoff.md
handoffSelect a terminal scientific outcome and transfer a locked contract to manuscript or figure workreferences/evidence-claims-and-handoff.md
manuscriptWrite, illustrate, render and inspect a complete evidence-linked working manuscript and local candidate packagereferences/standalone-manuscript.md
public-releaseCurate and rehearse a clean, runnable public code artifact without publishing itreferences/public-code-release.md

Use one primary mode per pass and return to an earlier mode when its underlying decision is invalidated. A mode name records the scientific boundary being resolved; it does not claim that an experiment ran or an external action occurred.

Start or resume

Resolve SKILL_DIR as the directory containing this SKILL.md. Every bundled script, reference, template, and component is below that directory; never resolve through the package parent. Run scripts by their resolved skill-local paths rather than assuming the user's working directory.

For a new project, create an empty workspace:

python3 "$SKILL_DIR/scripts/init_publication_project.py" /path/to/project \
  --project-id example-study \
  --title "A falsifiable research question" \
  --domain single-cell \
  --contribution-lane sota-method

Choose one contribution lane at intake:

  • sota-method: a mechanism is expected to beat the strongest matched comparator on a frozen task and representation.
  • discovery: the central output is a scientific finding with an independent validation path.
  • benchmark: the central output is a consequential missing resource or corrected evaluation contract with a credible venue precedent.

Do not change lanes because the original route became difficult. Record a new route decision and return to intake.

When resuming, read project.json, all eight records named in START_HERE.md, current project authority, and the newest actual result before trusting a narrative status. Modification time is not authority.

Run the smallest relevant check:

python3 "$SKILL_DIR/scripts/validate_publication_project.py" /path/to/project \
  --target working --format text

The targets are cumulative scientific boundaries:

TargetWhat it checks
workingPortable structure and explicit unresolved work
pilotAuthority, data feasibility, lane-specific scoop verdict, venue fit, and hypothesis
developmentFrozen protocol, baseline parity, open measured headroom, candidate order, and locked-test isolation
handoffTerminal outcome, result comparison, claim locking, limitations, and specialist readiness
public-releaseHandoff plus a curated, inspected public-release/ tree

A pass means the records satisfy this contract. It does not prove scientific truth, novelty, venue acceptance, or permission to act externally.

Synthetic demonstration

To inspect a complete local record contract without using real research material, run the bundled demonstration from this installed skill directory:

python3 examples/run_demo.py OUTPUT_DIRECTORY

OUTPUT_DIRECTORY must be a new directory outside this skill. The command prints the observed PASS status for pilot, development, and handoff. It does not run a real experiment, access a locked test, authorize an action, publish anything, or demonstrate scientific effectiveness. Read examples/README.md for expected output and the generated-workspace boundary; the workspace is a runtime output, not release content.

Add --with-public-release to rehearse the bundled synthetic code release: package, fresh unpack, run its fixed example and tests, compare the result, then validate the curated tree. This optional path records actual local command observations, not a real research experiment or external publication. It uses the existing Python environment.

Reference router

Read only what the current boundary needs:

TaskRead
authority, data feasibility, novelty, contribution lane, or venue routereferences/intake-and-routing.md
bounded field survey, paper reading, charter, or execution planreferences/survey-and-planning.md
translating an agreed plan into verifiable tasks, resuming implementation, or combining this workflow with Superpowersreferences/research-execution-discipline.md
multi-paper exemplar corpus, publication-pattern calibration, or cross-paper figure/section precedentreferences/exemplar-corpus-calibration.md
pilot design, retrainability probe, authorized-run observation, or anomaly handlingreferences/pilot-and-monitoring.md
benchmark freeze, baselines, headroom, candidate design, iteration, or recoveryreferences/protocol-headroom-and-development.md
evaluation lock, baseline parity, known-answer guard, lockbox exposure, or frozen decisionreferences/frozen-evaluation.md
source status, claims, negative results, manuscript handoff, or public releasereferences/evidence-claims-and-handoff.md
complete manuscript, figures, declarations, response or local submission candidatereferences/standalone-manuscript.md and references/standalone-figures.md
curated code tree, clean-room rehearsal, documentation, or release readinessreferences/public-code-release.md

Open current primary sources for literature claims and current official instructions for venue rules. A cached reference explains the method but cannot establish a current deadline, policy, or format rule.

Stage 1: resolve authority and evidence

Record the source that defines the active project before ideating. Current explicit user scope and structured project status outrank an old README or plan. A withdrawn, superseded, frozen, or provenance-only artifact may be audited but must not silently become the active submission base.

In evidence/source-register.json, use only:

  • VERIFIED when the source was opened and the cited location was inspected;
  • UNVERIFIED when it has not been checked;
  • COULD_NOT_OPEN when access failed;
  • NOT_FOUND when a dated search found no candidate source.

Only VERIFIED sources support a passing gate. Keep locators and inspected sections precise. Do not infer facts from a title, search result, neighboring project, or remembered citation.

Stage 2: make three independent intake judgments

Complete intake/intake.json in this order:

  1. data_feasibility: prove the required variables coexist in linkable samples, count the true independent units, name the strongest cheap baseline, and define a leakage-safe split.
  2. scoop: search the exact contribution lane and return IDENTICAL, ADJACENT, or UNCERTAIN. Adjacent work constrains the delta but does not kill the topic.
  3. venue_fit: match the contribution shape and necessary evidence to a current venue and article type. Weak venue fit is not an identical-work verdict.

Then freeze one hypothesis with endpoint, direction, minimum relevant effect, uncertainty method, validation path, and kill criterion. A pilot tests feasibility; it does not prove novelty or submission readiness.

Refresh the current incumbent at intake and immediately before protocol freeze. A later method or corrected implementation can change the comparator set and practical headroom without making the original survey dishonest.

Stage 3: measure headroom before method complexity

Freeze protocol/protocol.json before controlled iteration. It must name the exact data versions, preprocessing boundary, independent-unit split, leakage guard and known-bad guard test, primary metric implementation, baselines and tuning parity, uncertainty unit, selection and checkpoint rules, finite budgets, locked-test policy, allowed changes, and four-way stop rules.

Before aggregate scoring, run the known-answer and leakage guard cases described in references/frozen-evaluation.md. Abort evaluation if a guard fails. Record every lockbox exposure, including structural inspection that reveals labels, ordering, or other outcome-bearing information.

Reproduce the strongest cheap and field comparator before proposing a new architecture. Record development/headroom.json for the exact task and strongest available representation. OPEN requires a measured gap above both the noise floor and the minimum claim-worthy margin. If that gap is closed, change the question or stop; tuning cannot manufacture headroom.

Stage 4: run controlled, failure-directed iteration

Register causal candidates in development/iteration-ledger.json. Each candidate names a diagnosed failure node, one minimal mechanism, its predicted slice, a matched control, and a falsifier. For a SOTA-method lane, register at least two mechanism-level alternatives, but do not register a second architecture while lower construction rungs remain unresolved.

Use the fixed order:

recipe_parity -> objective_alignment -> data_or_representation
-> ensemble -> test_time_compute -> architecture

One cycle tests one registered load-bearing change. Record actual observations with locators, failed work, work not run, and scientific inference in separate fields. Do not tune on the locked test, promote a secondary metric, hide failed trials, shop seeds, weaken baselines, or remove an unfavorable dataset after seeing results.

Two misses on the frozen predicted slice kill that mechanism, not the whole route. If headroom, budget, and a registered alternative remain, pivot. Route-level stopping is limited to measured closed headroom, exhausted frozen budget surfaced for human review, or a newly verified lane-identical scoop. An integrity anomaly requires a new protocol; it is not evidence that the scientific question failed.

Stage 5: evaluate once and lock claims

Freeze the selected candidate before opening the locked test. Locked-test access, remote compute, and benchmark submission always require separate explicit authorization outside this local record. Evaluate with the frozen data, split, metric, comparator, seed aggregation, and uncertainty unit. Keep a failed final evaluation visible.

Apply frozen criteria as the exact logical conjunction registered in the protocol; do not replace all-required conditions with a convenient subset after seeing results. Distinguish an underpowered check from a measured miss using the preregistered resolution and uncertainty rule, not post-hoc optimism.

In claims/claim-register.json, every included result claim must have:

  • SUPPORTED or NARROWED status;
  • exact scope and verified evidence sources;
  • result locators and uncertainty;
  • separate observed facts, inference, limitations, and work not run.

A refuted claim is excluded or reported as a negative result. It is never rewritten as a positive claim through framing.

Stage 6: route the handoff

Choose one terminal outcome in handoff/handoff.json:

  • MANUSCRIPT: the frozen evaluation and route-specific validation support scoped claims;
  • NEGATIVE_RESULT: preserve a refuted or narrowed claim and its evidence;
  • RETURN_TO_INTAKE: reframe a framing failure, hold a data gap, or respond to an identical scoop;
  • STOPPED: measured headroom is closed or the frozen budget is exhausted.

For a full research-to-paper request, continue from the locked outcome to standalone manuscript production. The internal paper-reading component and the following optional specialists can enhance this work:

NeedCapability
paper understandinginternal components/paper-card/guide.md
handing a running project to another personinternal components/project-handover/guide.md
conference manuscript, abstract, statistics reporting, or rebuttalprepare-conference-manuscripts
journal manuscript, abstract, statistics reporting, data availability, or revisionprepare-journal-manuscripts
scientific figures and flowchartsbuild-scientific-visualizations
Chinese funding proposalwriting-funding-proposals

Read each selected skill or component before using it. No specialist is required for this skill's own research-to-manuscript scope. Their absence is not permission to invent venue rules or scientific evidence, and is not a reason to stop at a handoff record.

When an authorized manuscript handoff or working-draft scope includes figure production, or the user requests figures directly, new or redesigned flowchart, architecture, motivation, method and mechanism figures default to destination-style GPT Image 2.5 concepts followed by native editable PPTX using available tools directly via standalone figures. The optional visualization skill adds specialist compound layouts and design helpers to that same route. Keep locked scientific content and destination policy; measured panels retain their source-data plotting route. Follow the scoped boundaries in evidence, claims, and handoff. A pilot or status-only task does not itself request figure production.

Public release boundary

Follow references/public-code-release.md. Build public material only inside the project's relative public-release/ directory from an explicit allowlist. Include useful code, configuration, small examples, dependency versions, data-access instructions, expected outputs, tests, licence, citation, and honest limitations. Do not copy the publication workspace, internal decision records, credentials, hidden prompts, execution records, private project evidence, or automation traces into that tree.

The public-release validator inspects the curated tree. Publishing a repository, creating a release, uploading files, mutating a canonical manuscript, submitting a benchmark result, or submitting a paper remains a separate external action requiring explicit authorization and direct service evidence.

Report status precisely

Lead with the current decision, then report:

  • observed commands, results, paths, and source locators;
  • failed and not-run work;
  • inference and its uncertainty;
  • the next scientific gate;
  • any exact authorization boundary.

Keep module completion, manuscript readiness, public-release readiness, and actual publication as different states.

Signals

GitHub stars
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Sep 2026
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skill
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research-publication-pipeline
Source
github.com/gxcaesar/open-research-skills