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gaasher/agent-loop-skills

25 skills · 8 total installs

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$npx skills add gaasher/agent-loop-skills
SkillInstalls
purple-teamUse when the user wants to automatically harden a guardrail, classifier, content filter, prompt, or API they own by running attack and defense together as a…8alpha-evolveUse when the user wants to evolve an ML model/program through population-based search rather than a single sequential refine loop — a generational evolution…—anomaly-investigationUse when the user has a known, already-observed anomaly in their data — a metric spike or drop, an outlier, an unexpected number — and wants its root cause…—blue-teamUse when the user has concrete failing cases in code or a guardrail/classifier/filter/prompt/API they own — a red-team failure catalogue OR a CI/CD…—claim-verifyUse when the user has a results draft or a set of data-backed claims and wants each one adversarially verified against the underlying dataset before publishing…—data-analysisUse when the user wants an iterative, self-checking exploratory analysis of a dataset — surfacing findings that are each verified by re-running the…—dueling-autoresearchUse when the user wants two approaches raced head-to-head on a single shared metric — e.g.—exploratory-autoresearchUse when the user wants an autonomous ML research loop that explores the space broadly rather than hill-climbing one approach.—hypothesis-genUse when the user wants to generate and literature-vet a pool of novel, testable research hypotheses for a question or domain.—karpathyUse when the user wants the LLM to do its own ML research: a fully-autonomous loop that hacks the training code, runs it, and keeps changes that lower a single…—literature-searchUse when a loop needs scholarly literature — paper discovery, novelty checks, full-text snippet search, citation-graph traversal, single-paper reads, or…—literature-surveyUse when the user wants a structured, saturating literature survey on a question — not a one-shot summary, but an evidence/contradiction matrix (sources ×…—ml-autoresearchUse when the user wants an autonomous ML research loop that does more than blindly try changes.—optimize-loopUse when the user wants to iteratively improve an artifact under a hard correctness bound while minimizing a measured cost — refactoring a code module to cut…—plan-loopUse when the user has a coding or engineering prompt and wants it refined into a detailed, executable plan before any code is written — the planning stage of a…—power-analysisUse when the user is planning a two-arm comparison (an A/B test, a simple RCT, a behavioral study, or a two-model/two-config evaluation) and needs to size it…—prompt-optimizeUse when the user has a prompt that feeds a system they can already score, and wants that prompt automatically improved to raise the score against their own…—red-teamUse when the user wants to adversarially stress-test a guardrail, classifier, prompt, or API they own or are authorized to test, to surface the distinct ways…—research-proposalUse when the user has a research proposal (problem + proposed methodology + planned experiments) and wants it iteratively strengthened until it clears a…—research-questionUse when the user has a vague topic or area of interest and wants it sharpened into a few strong, novel, feasible research questions.—scientific-figureUse when the user has scientific data (or a prompt alluding to scientific data) and wants a publication-quality figure made from it.—scientific-writerUse when the user has a scientific draft (with its dataset, figures, and optional analysis code) and wants it iteratively revised until it clears a quality…—swe-loopUse when the user has a coding prompt — a feature, bug fix, or refactor — and wants it implemented end to end by a self-checking software loop, not a single…—tabular-cleanupUse when the user has a messy tabular data dump (CSV/TSV/parquet/Excel/JSON) and wants it iteratively cleaned to an inferred data contract — a checklist of…—tournament-autoresearchUse when the user wants an autonomous ML research loop that pressure-tests competing ideas before spending compute — several research subagents each propose…—