Check whether numeric claims marked with Evidence aliases in an Artifact agree with the linked Evidence content and context.
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Run score Not tested
See how to installReview the instructions the agent will receive before you install.
Run on the same locked Artifact with its supplied Evidence Bundle. In the bounded Deep pipeline, this local Evidence comparison runs before Citation source verification.
[evN] alias in the same sentence or Markdown table cell.INCONCLUSIVE when the Evidence excerpt does not contain enough context; do not report
insufficient content as a value mismatch.Return only the required structured result. Use a concrete COMPUTATION_* finding code such as
COMPUTATION_EVIDENCE_VALUE_MISMATCH, COMPUTATION_EVIDENCE_SCOPE_MISMATCH,
COMPUTATION_EVIDENCE_INTERPRETATION_OVERREACH, or COMPUTATION_EVIDENCE_INSUFFICIENT.
Preserve the supplied Evidence alias and provide one concise reason; do not invent a separate
correction field that the review protocol cannot persist.
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Prepare, launch, monitor, and summarize the real RFdiffusion to ProteinMPNN to Protenix antibody pipeline on a local or remote ScienceDiscovery Runner with sandboxed Ascend NPUs.
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Independent multi-dimensional assessor for material design candidates. Loads configurable scoring rubrics to evaluate candidates from different expert perspectives. Each dispatch produces structured scores, pros/cons, and verification data without sharing results with other assessors.
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Read, diagnose, and change the CI pipeline: GitHub Actions on pull requests, the merge queue, the nightly schedule and the release tag. Use when a job fails, when editing .github/workflows/, when asking which layer runs what, when reproducing a pipeline failure locally, or when a job needs the bubblewrap sandbox. Running the layers before proposing a change, and reading the result a proposal receives, belong to create-github-pr.
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Verify cited paper identity and decide whether claims in an Artifact are supported by their linked Evidence using a governed source snapshot.
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Use this skill when you need to write and execute Python/R code to process, transform, and analyze data, delivering reproducible computational results with complete code-level methodology documentation. Supports statistical analysis, data transformation, visualization, method justification, and structured result output.
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Open or update a pull request on GitHub's openJiuwen-ai/sciencediscovery: run the UT/ST/E2E layers locally, push the branch to the operator's own GitHub fork, write a body that says what was verified with numbers, apply exactly one release:* label so the release note can classify it, then read the pull request and its Actions run back. Use when asked to create a PR, submit a change for review, when a branch is ready to propose, when labelling a pull request for the release note, or when reading a GitHub Actions result on a pull request. This is the only path for proposing a change: gitcode.com is a read-only mirror with no pipeline of its own. Titles and bodies are English. For filing an issue, or for the gh commands this procedure assumes, read the github skill first.
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