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概要と使いどころ
一键发布 agent skill 到 GitHub，自动验证 SKILL.md、生成或检查更吸引人的 README、区分 skill name 与 GitHub repo name、创建或更新仓库、推送并通过 npx skills 真实安装验证。当用户说"发布这个skill"、"publish skill"、"把skill发到GitHub"、"分享这个skill"、"/publish-skill"时触发。支持发布当前目录或指定路径的 skill。
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。
Onboarding workflow for cross-library KB query in a consulting practice. Discovers existing user-scope library registrations, prompts for additions, validates each library, helps activate the relevant ones for the current project, runs a smoke test, and reports a clear "ready" or "issues to fix" verdict. Use --verify-only to skip prompting and just validate existing setup (sub-task 23 of
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。
Run all 5 decomposition validators (req-has-module, code-annotation-maps-to-module, visibility-rule-enforcement, anaemic-context-detection, granularity-match) on the project, reporting violations.
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。
Health-check the project knowledge base. Looks for contradictions between files, stale claims that newer sources have superseded, orphan files with no inbound cross-references, important concepts mentioned but lacking their own page, missing cross-references, and data gaps. Returns a structured report; does not auto-fix.
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。
Initialise a project for knowledge base use. Appends the [Knowledge Base] section to the project's CLAUDE.md, creates the library/ directory structure, optionally seeds with three example library files from the Agentic SDLC research, and reports next steps. Run once after installing sdlc-knowledge-base.
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。
Filter and summarise the cross-library KB audit log. Reports confidentiality events (attribution drops, synthesis aborts, dispatcher failures, no-evidence markers, cross-library promotions) over a date range, by event type, and by source handle.
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。
Check whether the knowledge base shelf-index is stale relative to the library files. Reports drifted entries without rebuilding. Designed to be invoked from environment validation or pre-push hooks as an opt-in check. Default mode is warning; strict mode fails with non-zero exit when any drift is detected.
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。
Rebuild the knowledge base shelf-index with hash-based change detection. Incremental by default — only re-extracts files whose content has changed since the last index. Use after ingesting new sources, after editing library files, or whenever the librarian agent reports a stale index.
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。
Check what's playing on WRHV 88.7 FM (Classical WMHT), fetch recent tracks, build playlist reports, search for pieces, and create or manage Spotify playlists from radio tracks. Triggers on 'Classical 887', 'WRHV', 'what's playing', 'classical radio', 'Hudson Valley radio', 'Spotify playlist from radio'.
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。
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".
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。
Analyze a repository's type system and generate type-safe DAG execution pipelines with GraphSentry-style certificate verification. This skill should be used when building LLM-driven workflows that need deterministic type safety, when composing typed operations into validated execution graphs, or when adding contract-checked pipeline orchestration to any codebase. Supports Python (Pydantic) and TypeScript (Zod).
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。
Final quality pass fixing alignment, spacing, consistency, interaction states, and micro-details before shipping. Executes changes (unlike design-audit and design-critique which are report-only). Triggers on polish, finishing touches, final pass, something looks off, pre-launch, good to great.
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。
Evaluate design from a UX perspective with Nielsen's heuristics scoring, anti-pattern detection, persona-based testing, and actionable feedback. Report-only. Triggers on critique, UX review, design feedback, how does this look, evaluate the design, component review.
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。
Install, customize, and compose shadcn/ui components with design-system awareness. Covers CLI v4, custom registries, Tailwind v4 OKLCH theming, components.json, presets, and monorepo setup. Pairs with minoan-frontend-design for creative direction. Triggers on shadcn, install component, shadcn theme, OKLCH colors, custom registry.
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。
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.
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。
Resolve merge and rebase conflicts with safe recovery strategies. Covers identifying conflict sources, reading conflict markers, choosing resolution strategies, and continuing or aborting operations safely. Use when a git merge, rebase, cherry-pick, or stash pop reports conflicts, when a git pull results in conflicting changes, or when you need to safely abort and restart a failed merge or rebase operation.
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。
Conduct a peer review of research methodology, experimental design, and manuscript quality. Covers methodology evaluation, statistical appropriateness, reproducibility assessment, bias identification, and constructive feedback. Use when reviewing a manuscript, preprint, or internal research report, evaluating a research proposal or study protocol, assessing evidence quality behind a claim, or reviewing a thesis chapter or dissertation section.
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。
Review a data analysis for quality, correctness, and reproducibility. Covers data quality assessment, assumption checking, model validation, data leakage detection, and reproducibility verification. Use when reviewing a colleague's analysis before publication, validating an ML pipeline before production deployment, auditing a report for regulatory or business decision-making, or performing a second-analyst review in a regulated environment.
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。
Close out a finished memex milestone slice by writing the handoff trail: update `docs/CONTINUE_HERE.md` §1 current-state and §3 next-slice, tick the `docs/ROADMAP.md` scoreboard (milestone header ✅ + version, `- [x]` items), confirm any new observation is logged (deferring to memex-observe), and propose the git tag plus a `MN Slice X:` commit subject. Use after you finish a milestone slice in the memex repo and before you commit/tag it, when handing the next slice to a fresh session, or whenever CONTINUE_HERE and ROADMAP have drifted behind what actually shipped.
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。
Implement comprehensive model drift monitoring using Evidently AI, statistical tests (PSI, KS), and custom metrics to detect data drift and concept drift in production ML systems. Set up automated alerting and reporting workflows to catch degradation before it impacts business metrics. Use when production models show unexplained performance degradation, when new data distributions differ from training data, when seasonal shifts affect input features, or when regulatory requirements mandate model monitoring.
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。
Run the local pre-commit gate for the memex repo before staging a commit: format check, clippy with warnings denied, and the workspace unit-test suite, mirroring memex's own CI. Use right before `commit-changes` on a memex working tree, after editing any Rust crate under `crates/`, or when reproducing a red CI run locally. Optionally runs the Postgres-gated integration suite when the `memex-pg` container is up and `.env` is sourced. This is a verification gate, NOT a replacement for memex CI — CI remains the authority; this catches failures earlier.
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。
Perform a Computer Systems Validation (CSV) assessment following GAMP 5 methodology. Covers user requirements, risk assessment, IQ/OQ/PQ planning, traceability matrix creation, and validation summary reporting. Use when a new computerized system is being introduced in a GxP environment, when an existing validated system is undergoing significant change, when periodic revalidation is required, or when a regulatory inspection demands a validation gap analysis.
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。
Implement cloud cost optimization strategies for Kubernetes workloads using tools like Kubecost for visibility, right-sizing recommendations, horizontal and vertical pod autoscaling, spot/preemptible instances, and resource quotas. Covers cost allocation, showback reporting, and continuous optimization practices. Use when cloud costs are growing without proportional business value, when resource requests are misaligned with actual usage, when manual scaling leads to over-provisioning, or when implementing showback and chargeback for internal cost accountability.
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。
Extract the conceptual essence of a repository as skills, agents, and teams — the project's roles, procedures, and coordination patterns expressed as agentskills.io-standard definitions. Reads an arbitrary codebase and produces generalized definitions that capture WHAT the project does and WHO operates it, without replicating HOW it does it. Use when onboarding to a new codebase and wanting to understand its conceptual architecture, when bootstrapping an agentic system from an existing project, when studying a project's organizational DNA for cross-pollination, or when creating a skill/agent/team library inspired by a reference implementation.
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。