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概要と使いどころ
Maintain stewardship protocol continuity and tool/personality boundaries. Use when a repo agent needs steward-mode threshold checks, self-model update decisions, delegation hygiene, boundary violation review, or handoff-safe continuity context without overclaiming steward personality.
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Maintains repo-local action contracts and harness repositories where product CLI and MCP adapters stay thin over core libraries. Use when adopting or improving steward.yaml actions, capability-level adoption evidence, cold-start proof loops, probes, benchmarks, CLI/MCP/core parity, adapter refactors, packages/core boundaries, or sibling harness layout; use repo-quality-system-lifecycle first for general app/library/tool stewardship baselines.
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Establish or audit a structural quality contract for any agent-operated engineering repository: app, library, CLI/tool, plugin, harness, or meta repo. Use when a repo needs charter clarity, docs/decision ownership, type-native validation gates, evidence paths, safe action policy, cold-start legibility, maturity proof, repair-loop routing, consumer/producer owner-boundary routing, command surface evolution, evolutionary simplicity (see references/evolutionary-simplicity.md), or a repo ecology pass to decide what should be compressed, merged, removed, updated, created, retired, or moved to checks.
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Scaffold and formally review a new Agent Skill in this marketplace repo. Covers valid SKILL.md generation, directory layout, registry entries, and spec auditing. Use when adding a skill, validating frontmatter, or checking marketplace readiness before a PR.
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Steward public stories about any work — creation ethics, application ethics, and maintenance of the story plus its disclosures (generated, drafted, curated, authored). Use when writing a public article, origin story, talk, README narrative, or showcase about how work was made; when publishing ethics and decisions; or when asked who generated vs curated a text. Do not use for ADRs, FAQs, skill citations, or marketing hype.
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Design, implement, and integrate generalized validation harnesses across a producer-consumer boundary after a local harness contract exists. Use when refactoring custom validation CLIs/MCPs for large polyrepos, extending Steward across sibling repos, or deploying a local tool to a consumer project for dogfooding and testing; use mcp-harness-repo-maintainer first for initial steward.yaml adoption and cold-start proof.
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Use Lingzao creator-content tools for Xiaohongshu/XHS, Douyin, and WeChat official-account public content. Lingzao supports XHS SEO, Xiaohongshu account analysis, benchmark account discovery, viral note breakdown, keyword research, one-stop content packages from keyword/link/image/inspiration material, title and cover optimization, hand-drawn route-map cards, city food maps, travel itinerary maps, life checklist maps, workflow manual maps, creator content workflow, note search, creator search, profile lookup, recent posts, deep profile copy/subtitle analysis, note/article detail, post comments, article stats, related articles, short-video copy extraction, and prompt-based creator image generation.
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Manage Agent Skills across Codex, Claude Code, local/global/project roots, Skill Hubs, GitHub, skills.sh, and managed plugin caches. Use when searching, installing, updating, upgrading, syncing, merging, auditing, deduplicating, cleaning, packaging, publishing, validating, resolving upstream sources, choosing runtime or scope, or working with skill-upgrade, check_upstreams.ps1, Claude Code plugins, skills-lock.json, or skill-upstreams.json. Do not use for ordinary software-package upgrades or non-skill file cleanup.
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Find, build, evaluate, and improve systems using decision models. Use for bounded classification, routing, ranking, Choice/Score/Noul, decision-model composition, evaluation harnesses, prompt/program hill climbing, and Software 3.0 workflows across software, business, organizations, and life. Separate models, code, and human judgment. TypeSafe Jev is the default hosted exemplar. Not for straightforward arithmetic, prose rewriting, or provider setup alone.
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The LAW a council SEAT is bound by — deliberation protocol, pact obligations, governance, and decision-ledger recording — the discipline half of a seat. Trigger when: - Holding a seat on a bound council (architect, lead-maintainer, process-auditor, or a summoned guest). - Depositing an independent assessment, routing a decision, or recording assent or a finding. - Auditing whether the council honored the pact, the delegation table, or the barring lifecycle. - Prompt contains: /council, council seat, deliberation protocol, pact, delegation table, decision ledger, barring, merge-consent.
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Idiomatic programming style, patterns, and conventions for Rust development. Trigger when: - Writing, refactoring, reviewing, or debugging Rust code. - Files matching the pattern **/*.rs (including Cargo.toml, Cargo.lock) are in the workspace or referenced. - Tasks involve: cargo build, cargo clippy, cargo test, cargo check, rustc. - Prompt contains keywords: rust, cargo, clippy, borrow checker, lifetime, struct, enum, impl, Option, Result, match, unwrap, unsafe.
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SOP for structured documentation lifecycle. Trigger when: - Designing, writing, reviewing, or auditing large-scale documentation structures. - Navigating phases: Audit, Plan, Draft, Review, Verify. - Prompt contains: /doc, doc workflow, audit, draft, review, verify, documentation debt.
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Distributed machine learning, data mining, and iterative HPC with Exasol. Covers end-to-end ML pipelines (DISTRIBUTE BY + SET scripts + BucketFS), per-entity federated training with partial_fit and ctx.reset(), batch inference, map-reduce ensemble training, distributed ensemble and SON algorithm for frequent itemset mining (Apriori, FP-Growth, association rules, market-basket analysis), Lua execute script orchestration for iterative algorithms (k-means, SGD, gradient descent), scikit-learn model training, parallel hyperparameter search, per-entity forecasting, anomaly detection, model lifecycle in BucketFS (pickle/joblib/ONNX versioning), GPU acceleration via CUDA SLCs (PyTorch/TensorFlow/RAPIDS), and ML-specific performance tuning (skew, OOM, multi-pass chunking).
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Use this skill to process one to 99 local exact 2:1 equirectangular panorama images with Realsee Argus, producing depth maps, a merged GLB point cloud, camera poses, optional intrinsics, and a validated local output index. Trigger for Argus panorama reconstruction, Argus ZIP input, or explicit Argus start/status/collect lifecycle requests. Do not trigger for panorama editing or stitching, arbitrary-photo 3D generation, existing GLB inspection, or research-only questions.
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Set up, verify, and clean up Stripe test data end to end. Use when creating test customers, products, or subscriptions and you want a repeatable setup-then-teardown workflow, or when you need to remove leftover test customers and products with delete_stripe_test_customers, archive_stripe_test_products, and delete_stripe_test_products.
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Detect Golden Ticket attacks in Active Directory by analyzing Kerberos TGT anomalies including mismatched encryption types, impossible ticket lifetimes, non-existent accounts, and forged PAC signatures in domain controller event logs.
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Detect Kerberos Golden Ticket forgery by analyzing Windows Event ID 4769 for RC4 encryption downgrades (0x17), abnormal ticket lifetimes, and krbtgt account anomalies in Splunk and Elastic SIEM
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Responds to malware infections across enterprise endpoints by identifying the malware family, determining infection vectors, assessing spread, and executing eradication procedures. Covers the full lifecycle from detection through containment, analysis, removal, and recovery. Activates for requests involving malware response, malware eradication, trojan removal, worm containment, malware triage, or infected endpoint remediation.
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Auditing Google Cloud Platform IAM permissions to identify overly permissive bindings, primitive role usage, service account key proliferation, and cross-project access risks using gcloud CLI, Policy Analyzer, and IAM Recommender.
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Track vendor support tickets and RMA cases across multiple vendors. Use when managing support ticket lifecycle, updating ticket status from vendor emails, generating status reports, or identifying tickets needing follow-up.
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End-of-life detection for runtimes (Node, Python, Java, Go, .NET) and key packages — surfaces past-EOL items, items reaching EOL within 90 days, and EOL base images for containers. Use when planning a runtime upgrade, auditing for unsupported versions, gating a deploy against EOL deps, or producing a remediation roadmap.
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Track build processing, find latest builds, and clean up old builds with asc. Use when managing build retention or waiting on processing.
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Knowledge base from the NIST/SEMATECH e-Handbook of Statistical Methods (NIST HB 151) — the practical statistics reference for engineering, metrology, and quality. Use for: exploratory data analysis and the four univariate assumptions (4-plot); measurement process characterization including bias/precision, calibration designs, gauge R&R, and ISO/GUM uncertainty budgets; production process characterization (stability vs. capability); process modeling and regression (LS/WLS/NLS/LOESS); design of experiments (screening, fractional/factorial, response-surface, Taguchi); statistical process control (Shewhart/CUSUM/EWMA charts, capability indices, acceptance sampling); product/process comparisons (hypothesis tests and confidence intervals for 1/2/3+ groups, ANOVA, multiple comparisons); and reliability (lifetime & repair-rate models, accelerated testing, reliability growth). Scope limits: this is applied frequentist statistics for measurement and quality — it does NOT reproduce the per-distribution formula galleries, worked case studies, datasets, plot images, or Dataplot/R code of the original web Handbook (those are described, not copied); it is thin on modern machine learning, Bayesian methods beyond conjugate reliability priors, time-series/forecasting, and Bayesian experimental design.
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Knowledge base synthesized from the Guide to the Systems Engineering Body of Knowledge (SEBoK) v2.14 by the BKCASE Project. Use for the established systems-engineering canon: SE fundamentals and foundations (systems science, systems thinking, the systems approach, modelling/MBSE), the life cycle (ISO/IEC/IEEE 15288/24748/24774 process, development & agile approaches, model selection/tailoring), technical management, concept definition, architecture/realization (the Vee), V&V, maintenance/sustainment, SE standards, and the application contexts (product, service, enterprise, systems-of-systems, healthcare), plus enabling SE (business/team/individual), related disciplines, quality attributes/specialty engineering, implementation examples, and emerging knowledge. Good for grounding background, vocabulary, and prior-art positions across all eight SEBoK Parts. SCOPE LIMITS: this pack is SEBoK v2.14 only (released 2026-05-18); it synthesizes and signposts rather than reproducing the source — it does not reproduce ISO/IEC/IEEE standard text, is a curated guide (not a complete textbook), and is thin on AI-integration depth (Part 8 is a staging area, not settled practice). LICENCE: content is CC BY-NC-SA 3.0 — non-commercial use only, attribution to the BKCASE Project required, share-alike obligations carry forward.
日本語の概要は準備中です。原文の説明を表示しています。