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Python dependency management with Poetry and Rye -- lockfile-driven workflows, dependency groups, monorepo patterns, and migration paths. Covers pyproject.toml-centric packaging for projects not yet on uv.

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fast-check patterns for JS/TS — 6 canonical property categories with worked examples targeting agent-studio utilities (path normalization, safe-json, glob-to-regex, routing logic)

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Autonomous fixed-budget ML experiment loop — setup, iterative hypothesis testing, git-based keep/discard tracking, and indefinite autonomous execution. Implements the karpathy/autoresearch protocol.

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Decision matrix for selecting multi-agent topologies (Supervisor, Swarm, Hierarchical, Conductor) with token economics, failure modes, and escalation paths

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Structured workflow for upgrading Next.js applications across major versions. Use when migrating a Next.js project from one major version to another (e.g., 13 to 14, 14 to 15, 15 to 16). Covers codemod automation, breaking change detection, incremental migration paths, and post-upgrade validation.

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Documents the hook enforcement system, bypass mechanisms, and common failure patterns to help agents avoid getting stuck on protected path writes

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Create structured incident response runbooks with step-by-step procedures, escalation paths, and recovery actions. Use when building runbooks, responding to incidents, or establishing incident response procedures.

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Deeply analyzes Agent Studio framework structural health: catching phantom require() references, wrong module depth paths, missing skill/agent dependencies, bloated configurations, archived references in active code, stale catalog counts, and empty tool/skill directories.

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Structured debug log analysis for Claude Code sessions — auto-discovers most recent log, runs reducer, extracts error patterns, correlates with full log, produces observability report. Fills 5 identified gaps: hook error body capture, agent identity, file path tracking, stall correlation, success visibility.

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Register an external knowledge base library in the user-scope global registry at ~/.sdlc/global-libraries.json. Validates that the target path exists, contains a _shelf-index.md, and parses its format_version. Optional helper — hand-editing the JSON is also supported.

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File a librarian query result back into the library as a new page with provenance tracking. Karpathy's "good answers can be filed back into the wiki as new pages" insight made concrete. The library compounds from explorations, not just from external sources.

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Build a team Docker image from a manifest in .archon/teams/. Resolves plugin paths, generates Dockerfile with additive copy-only, makes plugins read-only, bakes team CLAUDE.md.

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Integrate a new source into the project knowledge base. Wraps the agent-knowledge-updater agent. Source can be a local file path, a URL, or pasted content. The updater reads the source, classifies it, identifies which existing library files it touches, makes surgical updates or creates new files, rebuilds the shelf-index, and appends to log.md.

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Queries the NCATS Translator ARAX production API for bounded, typed, provenance-rich one-hop and endpoint-pinned two-hop biomedical knowledge-graph relationships. Use for Biolink-constrained RTX-KG2 lookup, explicit selected-provider ARAX federation, separate entity normalization, qualifier-aware graph traversal, and inspection of TRAPI edge bindings, publications, and knowledge-source provenance. Do not use for inference, ranking, open-ended pathfinding, clinical guidance, or sensitive queries.

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Query the Precision Medicine Knowledge Graph (PrimeKG) for multiscale biological relationships across genes and proteins, drugs, diseases, phenotypes, pathways, biological processes, exposures and anatomy. Use this skill to search entities by name, pull direct neighbours and their evidence types, summarise the local network around a disease, and find direct or two-hop drug-disease connections for repurposing hypotheses. Also trigger on PrimeKG, kg.csv, Harvard Dataverse knowledge graph, disease_protein, drug_protein, indication and contraindication edges, or network pharmacology over a biomedical knowledge graph.

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Scrape pages locally with anti-bot bypass, TLS impersonation, and adaptive element tracking — no API keys, no cloud. Handles Cloudflare protection, CSS/XPath element extraction, and survives site redesigns. Complements firecrawl (cloud) with 100% local execution. Triggers on Cloudflare bypass, anti-bot scraping, stealth fetch, local scraping, Scrapling.

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Scaffold and run Karpathy-style autoresearch loops in any git repo. This skill should be used when setting up autonomous code improvement, generating adversarial eval harnesses, running hypothesis-implement-eval-keep/discard loops, or checking autoresearch progress. Triggers on "autoresearch", "autonomous improvement", "eval loop", "hypothesis loop", "self-improvement loop".

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Create text effects impossible with CSS alone — kinetic typography, flowing text around animated obstacles, calligrams, shrinkwrap chat bubbles, typographic ASCII art, glyph path animation, variable font waves, glyph morphing, illuminated manuscripts. Single-file HTML output, zero build step. Powered by @chenglou/pretext + opentype.js. Triggers on text effects, kinetic typography, text animation, calligram, glyph art, typography art.

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Redact a network/MITM capture directory — JSONL, JSON, logs, HAR-style dumps — in place before it can be referenced publicly, scrubbing credential tokens, API keys, service ids, UUIDs, emails, home paths, usernames, and device or session hashes while preserving token-class prefixes for analysis and leaving public identifiers untouched. Covers class-preserving substitution, an idempotent re-runnable pass, distinguishing a secret from a public id, and verifying the scrubbed capture through the redaction gate. Use when a wire capture from a sanctioned probe must enter notes, a guide, or a public repo without leaking the session that produced it.

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Design a generative recipe DSL so agents emit small validated JSON documents and ONE audited interpreter renders them all — data, not code. Covers the N-artifacts threshold for choosing a DSL over bespoke code, designing roles as style slots so a single recipe renders unchanged in every output style, the validator gate (compile + bounds + real render in all styles, plus a --fast mode for corpus-wide sweeps), hand-authored seed recipes, and the emergent conventions that keep a corpus of hundreds consistent without per-item steering. Use when many similar artifacts (icons, status badges, diagram nodes, test fixtures) must be generated by agents, when per-item bespoke code is multiplying unreviewable code paths, or when a whole corpus must be re-rendered cheaply into new styles.

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Systematically interpret mass spectra to determine molecular formula, identify fragmentation pathways, and propose molecular structures. Covers ionization method assessment, molecular ion identification, isotope pattern analysis, common fragmentation losses, and purity evaluation.

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Guide a person through structured learning of a new topic, technology, or skill. AI acts as learning coach — assessing current knowledge, designing a learning path, walking through material, testing understanding, adapting difficulty, and planning review sessions for retention. Use when a person wants to learn a new technology and does not know where to start, when someone feels overwhelmed by documentation, when a person keeps forgetting material and needs spaced repetition, or when transitioning between domains and needing a gap analysis.

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Fit hidden Markov models using the Baum-Welch (EM) algorithm with model selection, Viterbi decoding for state sequences, and forward-backward probabilities. Use when observations are generated by unobservable latent states, you need to segment a time series into latent regimes (market regimes, speech phonemes, biological sequences), compute sequence probabilities, decode the most likely hidden state path, or compare models with different numbers of hidden states.

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Coordinate safely with a peer interactive session sharing the same git worktree — check first whether a separate worktree removes the problem, then declare path and branch scope before the first edit, survive a contended index lock, and review the whole branch before opening a PR. Activate when starting work in a repository that may already be occupied, when a git command fails with `index.lock: File exists`, when `guard:snapshot` refuses because a snapshot already exists, or when a commit turns out to contain a file this session never edited. When one session leads and the other supports, divide the labour by shape and re-derive every reported number against a named revision before citing it. Distinct from subagent concurrency: a peer session cannot be bracketed, because no baseline exists from before its edits.

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