uchicago-dsi/ai-sci-skills
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reusable skills for AI scientists
概要
Reusable skills for AI-assisted scientific research. Coding agents lose context across sessions, trust results they shouldn't, and propose sweeps when a single diagnostic run would suffice. These skills encode recurring workflows and judgment calls so they don't have to be re-taught every session. Each skill is intentionally compact. The shared versions encode decision rules and workflows that generalize across projects, while cluster-specific, lab-specific, and repo-specific facts stay in local policy files. agentcomm gives several agents working on one problem a shared mailbox, so they can hand off, ask each other questions, and say when something is done without a person relaying it. It is most useful across harnesses. Claude Code can already message other Claude sessions directly, so two Claude agents need no help from this.
README
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ai-sci-skills
Reusable skills for AI-assisted scientific research.
Coding agents lose context across sessions, trust results they shouldn’t, and propose sweeps when a single diagnostic run would suffice. These skills encode recurring workflows and judgment calls so they don’t have to be re-taught every session.
Each skill is intentionally compact. The shared versions encode decision rules and workflows that generalize across projects, while cluster-specific, lab-specific, and repo-specific facts stay in local policy files.
Skills
| Skill | What it does |
|---|---|
slurm |
Submit, inspect, and debug Slurm jobs without mixing scheduler problems with runtime failures |
experiment-design |
Propose the smallest experiment that changes a decision |
training-audit |
Diagnose early validation decline and choose controlled optimization checks |
sensemaking |
Check whether a finding makes sense before trusting it |
skeptical-labmate |
Stress-test claims, baselines, and follow-up plans |
lab-notebook |
Keep records restartable and auditable |
quarto-presentations |
Create, render, check, and export Quarto reveal.js slide decks |
job-babysitting |
Classify job health and choose the next action |
mission-control |
Coordinate workers, reconcile steering, and intervene before directions become stale |
rut-breaker |
Detect low-yield loops and force a better reset move |
handoff |
Create restart-ready session handoffs |
bounded-auto-loop |
Run a short autonomous loop with a fixed budget and stop rule |
maintenance-pass |
Trim dead code, vestiges, and duplication without churn |
research-code-parsimony |
Reuse existing owners and cut over cleanly instead of growing code |
claude-code-worker |
Delegate isolated Claude Code tasks with resumable sessions and quota-aware recovery |
agentcomm |
Let agents coordinate with each other through a shared mailbox |
quota-saving-mode |
Cut the model requests spent on polling, waiting, and status chatter |
humanize |
Edit prose so it sounds like the author and reads plainly |
Agents talking to each other
agentcomm gives several agents working on one problem a shared mailbox, so
they can hand off, ask each other questions, and say when something is done
without a person relaying it.
It is most useful across harnesses. Claude Code can already message other Claude sessions directly, so two Claude agents need no help from this. A Claude agent and a Codex agent cannot see each other at all, and the mailbox is what lets them coordinate: a durable name each, a roster showing who is reading, and read state that tells a peer whether a question has actually been picked up.
quota-saving-mode uses it for the same reason, to deliver a wake-up when a
long job finishes rather than having an agent poll for it. That skill ships
bin/await-notify and bin/await-event for harnesses without built-in
推奨ツール
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インストール
npx skillfish add uchicago-dsi/ai-sci-skills