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概要と使いどころ
Execute and verify Apache OpenDAL release-manager work, including weekly ATR candidates, RC tagging, required GitHub Actions checks, ASF SVN dist uploads, Nexus staging close/release, vote discussions, language package readiness, GitHub release, announcements, and release postmortems.
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。
Teaches agents to reply to PR review comment threads after fixing issues, making resolutions traceable
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。
Detect and set up account-locked gh aliases for multi-account GitHub. The AI reads this skill, detects accounts, asks the user which is personal/work, and runs the setup automatically.
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。
How to coordinate with squads on different machines using git as transport
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。
Categorized catalog of common Squad operations. Coordinator reads this file and presents it as an interactive menu when the user asks for available commands or help.
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。
Selecting WHO handles work is the Routing table; selecting HOW they handle it (Direct, Lightweight, Standard, Full) is Response Mode. This skill contains the complete decision table, exemplar prompts for each mode, the Lightweight spawn template, and the upgrade rules. Squad coordinator loads this on demand once routing has identified the agent — to pick the right ceremony level for the task.
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。
The complete file-by-file source-of-truth hierarchy for Squad: which files are authoritative, which are derived/append-only, who may write each one, who may read each one, and the precedence rules when they conflict. Squad coordinator loads this on demand when it needs to resolve a write conflict, decide where a piece of state belongs, or answer a 'who owns this file' question.
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。
The scheduled model sweep. Reads the team's models channel for hints, discovers new LLM models, adds them to ml_model_list.py, runs the paid tests, marks dead provider entries deprecated, opens PRs under the team's rules, announces them in Slack, and checks whether remote_config needs a publish PR. Use when asked to run the model sweep by hand, to add or deprecate models unattended, or to change how the daily sweep behaves.
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。
Kiln's code conventions and per-area gotchas, plus a diff gate that enforces the mechanical ones. Invoke before writing or changing any Python, TypeScript or Svelte code in the Kiln repo (libs/core, libs/server, app/desktop, app/web_ui), and when reviewing such a change. Covers comments, startup and entry points, globals and module state, config reads, module layering, library-vs-app rules and async I/O.
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。
Microsoft 365 / Entra ID red-team attack chain — current 2026 reality. AADSTS code reference, user enumeration vectors (with hardening status), Smart Lockout math, Conditional Access bypass options, ROPC + SAML SSO browser flow, Burp/Playwright templates. Built from authorized red-team work where ROPC spray surfaced pre-existing lockouts and CA-blocked credentials, plus real-time external attacker activity correlation. Use for any M365/Entra credential attack, password spray, user enumeration, CA-bypass exploration, or active-attacker-detection scenario.
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。
Hunt LLM/AI feature bugs — prompt injection, indirect injection, exfiltration via tool-use/markdown, ASCII smuggling, agentic AI security (OWASP Agentic Apps 2026, ASI01-ASI10). Patterns: direct injection ('ignore previous instructions'), indirect injection via documents/web pages/email the model reads, ASCII smuggling (Unicode Tags block U+E0000-U+E007F, invisible to humans, decoded by the model), tool-use exfiltration (model has fetch/browse tool, attacker injects OOB URL, model exfils chat history/secrets), markdown-image zero-click exfil, system-prompt extraction, IDOR-via-AI (cross-tenant data). Targets: chatbots, RAG, summarizers, agentic copilots, MCP tools. Detection: any LLM-backed endpoint, doc upload triggering AI processing, autonomous agent with tools. Validate: OOB/Collaborator callback for exfil, verbatim-reproducible system-prompt leak (run twice), verifiable cross-tenant leak or RCE. Confabulation is NOT a finding. Use when hunting AI features, chatbots, RAG, agentic systems, MCP.
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。
Skill-set loader for /hunt orchestrator. Fingerprints the target, picks the right platform attack skills, and loads the Red Team or WAPT skill set. Use when /hunt has just received a mode answer (redteam or wapt + blackbox|greybox) and needs to load the appropriate skills and print the taxonomy. Not for direct user invocation.
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。
Internal — invoked headlessly by the peon eval server; humans should run `peon eval <pack>` instead. Execute one PeonPing reroll job — invoked headlessly by the peon eval server as: "Use the peon-ping-remix skill to execute the reroll job at <path>". Reads the job JSON (scope, category, index, caption), rewrites the affected sound prompt(s) to honor the caption, re-renders via scripts/pack-render.py, and logs the change to eval-log.json.
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。
Use when English text must be parsed without a human to resolve ambiguity — tool descriptions, error messages, inter-agent instructions, system prompts, status reports — and misreading has a real cost, or when text reads as dense, hedged, or easy to misparse. Triggers: disambiguate, STE100 rewrite, apply Simplified Technical English, plain-language rewrite, controlled-language rewrite, rewrite so an agent cannot misread this. Not for creative or marketing copy.
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。
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
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。
Remove AI tells from LinkedIn posts/comments: 2026 vocabulary density, reveal bridges, staccato fragments, stacked triads, performed sincerity. Tiered rewriter plus `--mode audit` LinkedIn post auditor and `--mode profile` voice builder. Not for drafting from scratch (use linkedin-post-writer) or beating AI detectors. Keywords: humanize, de-AI, post audit, post auditor, audit before posting.
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。
Draft a reply to one LinkedIn comment from its URL, or sweep a whole thread from just the post URL and draft a reply to every comment worth answering, in one batch. Use for replying to a comment, following an author reply, or clearing all comments on a post. Resolves the correct parentComment (LinkedIn flattens threads to 2 levels), filters low-value comments before a sweep, and posts via Publora on approval. Not for top-level comments (use linkedin-comment-drafter).
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。
Analyzes frequency data across your Meta campaigns, identifies where you're overserving ads to the same people, and recommends frequency caps by campaign objective. Tells you the point where additional impressions stop driving conversions and start burning money. Platform: Meta.
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。
Scans your Google and Meta accounts for money being spent on search terms, placements, audiences, and ads that produce zero or near-zero conversions. Delivers clean exclusion lists you can upload directly. Platform: Google and Meta.
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。
Transform one long-form piece into multiple platform-specific content derivatives including LinkedIn posts, tweet threads, email snippets, ad hooks, and video scripts while maintaining voice consistency. Use when given a blog post, article, or pillar content to atomize across channels. Platform: Google and Meta.
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。
Compares your Meta ad sets and identifies where audiences overlap significantly, causing your ads to compete against each other in the same auctions. Tells you exactly which ad sets are cannibalizing each other and how much it's costing you in inflated CPMs. Platform: Meta.
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。
Breaks down Quality Score components for your Google Ads keywords — expected CTR, ad relevance, and landing page experience — and tells you exactly which component is dragging each keyword down, with specific fixes ranked by potential CPC impact. Platform: Google.
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。
Monitors your ads for early signs of fatigue before performance fully collapses. Tracks frequency buildup, CTR decay, CPM increases, and engagement drops across all active creatives and tells you which ones need rotation now vs next week. Platform: Meta.
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。
Analyzes your top performing ads, identifies what's working in the hooks, CTAs, messaging angles, and formats, then generates new variants that follow the same winning patterns while introducing enough variation to test meaningfully. Platform: Google and Meta.
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。