Academic experiments

Skill joshua-zyy/academic-paper-writer/skills/academic-experiments

面向 CS / AI / ML 领域的证据驱动、分节推进的论文写作 Agent Skill。

Install

npx -y skills add joshua-zyy/academic-paper-writer --skill academic-experiments

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its author says it does

Copied from the file, not written here

Audit, run, or verify experimental evidence for CS/AI/ML papers. Produces Evidence Inventory with evidence_type annotations (newly_run/preexisting_artifact/user_claim) and Protocol Risk assessments. Use when: checking if experiment results are reproducible, auditing existing experiment artifacts, running minimal reproducible commands, evaluating checkpoints without full retraining, documenting protocol risks like data leakage or missing baselines. Triggers on: 复核实验, run experiments, 实验结果, experiment evidence, verify results, 实验验证, evidence inventory, protocol risk, 跑实验, check results, reproduce experiments, 实验审计.

SKILL.md

3.1 KB, as published. Nobody here has run it

Academic Experiments

将此 skill 视为"实验取证代理"，目标是建立最短且可信的证据链，而不是尽量多跑实验。

Router Protocol

Read manifest.yaml. It declares always_load files, axes, and references.on_demand.
Read every file listed under always_load. These are the skill's binding rules — not reference material.
Apply the loaded material as constraints:
- stance.md defines non-negotiable rules, evidence type semantics, failure degradation, and scope.
- red-lines.md defines absolute prohibitions. Do not negotiate these.
- output-contract.md defines deliverables per mode and claim-readiness classification.
- anti-patterns.md defines known failure modes and their correct alternatives.
Detect the mode using the manifest's mode axis: experiment-evidence-pass, evidence-inventory-only, or minimal-reproducible-run. Align evidence type semantics to ../shared/core/evidence-policy.md.
Echo the selected mode to the user before executing.
Reach for references/ only when the manifest's references.on_demand condition is satisfied.

Modes

Mode	Use when
`experiment-evidence-pass`	Full audit: inventory + run + record + risk analysis
`evidence-inventory-only`	Inventory existing artifacts only, no execution
`minimal-reproducible-run`	Execute minimal reproducible command (e.g. eval existing checkpoint)

Agent Dispatch

agents/experiment_agent.md is dispatched by academic-paper-writer orchestrator at Step 4. The agent may run experiments but must not modify project source code or data files, nor write paper prose independently.

Independent Use

Input	Mode	Priority	Behavior
`repo_path` + no run mode	experiment-evidence-pass	2 (path trigger)	Full audit: inventory → env → minimal run → risk
`repo_path` + "inspect only"	evidence-inventory-only	1 (explicit)	Inventory only, no commands
`repo_path` + specific command	minimal-reproducible-run	1 (explicit)	Verify env → execute → record
No `repo_path`	—	3 (no input)	Ask path, or auto-detect entry files

Scenario	Recommended
Just auditing/reproducing evidence	This skill (standalone)
Writing results into paper prose	academic-paper-writer orchestrator
Draft results need verification	This skill → academic-reviser