「what」の検索結果

Build and maintain a persistent, LLM-maintained markdown wiki following Andrej Karpathy's LLM Wiki pattern — the agent incrementally compiles raw sources into an interlinked knowledge base instead of re-deriving answers from scratch. Use this whenever the user wants to ingest a source (an article, paper, transcript, chapter, meeting notes), file knowledge or conversation findings into the wiki, query the accumulated knowledge base, lint or health-check the wiki, or mentions "the wiki", "knowledge base", "ingest this", "file this", "what do we know about X", or accumulating notes on a topic over time — even if they don't say "LLM Wiki" explicitly.

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。

Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.

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 **Commitment Tracker** skill extracts and makes explicit the **ontological commitments** that agents make implicitly through their code and behavior. It enables detection and resolution of silent incompatibilities between systems that use different underlying assumptions about what exists and ho

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。

Complement to alice-emacs-mods. Covers what alice does not — ghostel mastery, multi-daemon orchestration, cross-session coordination, debug/recovery harness, REPL-as-dynamical-citizen, QRTP distribution, strobe internals, and the hard-won lessons from spawning and debugging live REPLs under the server daemon. Read alongside alice-emacs-mods; together they tile the total Emacs-mod space on this machine.

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。

Performs initial binary triage by surveying memory layout, strings, imports/exports, and functions to quickly understand what a binary does and identify suspicious behavior. Use when first examining a binary, when user asks to triage/survey/analyze a program, or wants an overview before deeper reverse engineering.

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。

Unified messaging via Beeper Desktop MCP. Search chats, send messages, manage conversations across all networks (iMessage, WhatsApp, Signal, Telegram, Discord, Slack, etc.)

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 this skill when the user wants to discover, define, or refine their product's aesthetic identity. Triggers on "what should this feel like?", "help me figure out the vibe", "something feels off visually", "I want it to feel like [X]", "define the visual language", or when a project has no established design direction. This is the art director skill - it helps users articulate something they can feel but can't name. Also handles quick cohesion checks when the orchestrator needs one during cycle planning.

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。

This skill should be used when validate-chunk reports test failures specifically, when the user says "tests are failing", "figure out what's wrong with the tests", "fix the failing tests", or when test assertions don't match expected output after chunk implementation. Triages whether the test or the implementation is wrong and fixes the correct one.

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。

This skill should be used when the user asks to "brainstorm", "explore options", "get creative", "what if we...", or selects "Let's get creative" during story or cycle creation. NOT for a bare vague feature idea where generating options would mean inventing the premise first - that routes to /craft:riff (riff first, options after). Generates 3-4 creative options with trade-offs, visual direction for UI stories, and wireframes.

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。

A live visual Kanban board and continuity layer for long-running agentic tasks. Nobody wants to read a markdown plan or stare at raw HTML while an agent grinds for an hour, so Plandeck turns the plan into a board that organizes itself. Use it when a task is multi-step, long-running, or needs visual planning. Break the work into cards, declare which card depends on which, and Plandeck computes the critical path, auto-promotes cards to Ready as their dependencies clear, rolls up story-point estimates into an honest percent complete, and names the one next action. Plans, observed transitions, and last-known-good snapshots stay as plain files on disk, so they survive /clear and context resets. After a reset, run plandeck next to recover the single next move and its recent history. If the plan stops parsing, run plandeck doctor before using git. Renders a live board in the browser over SSE. Triggers on plan a project, break down a task, kanban board, task board, visual plan, long-running agent, agentic task, track dependencies, critical path, story-point estimates, what is next, mission journal, recover plan, plandeck.

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。

Sync a skill's content against the upstream library it covers — check whether the API descriptions, version references, and SOURCE: citations inside SKILL.md and its reference files still reflect what the library actually does today. Use when a library has released updates that may have changed the APIs the skill covers, when a skill references an old library version, when asked to sync, refresh, update, or check a skill against upstream docs, when the skill's content may have drifted from current library behavior, or when SOURCE: citations are stale. Accepts a SKILL.md path, skill directory, or plugin directory.

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。

Query and invoke tools on MCP servers using fastmcp list and fastmcp call. Use when you need to discover what tools a server offers, call tools, or integrate MCP servers into workflows.

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。

Quantitative cost measurement for technical research — token injection costs, payload sizes, context window consumption, and file-level counts from actual repo files. Use when a technical-researcher orchestrator needs the cost dimension of adding or changing something: how many tokens will it inject, how big are the artifacts, what is the context window impact? This is NOT blast-radius analysis (which files break) — it covers size, tokens, and performance cost only.

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 starting a new feature, gathering requirements for an unfamiliar domain, refining a vague idea into actionable scope, or when a user request is ambiguous or underspecified. Conducts SAM Stage 1 discovery — structured requirements gathering through user discussion, asking WHO/WHAT/WHEN/WHY and never HOW. Produces the ARTIFACT:DISCOVERY document containing feature requirements, NFRs, goals, anti-goals, references, and resolved questions. Supports backlog item self-initialization via a

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 the plan_ref returned by add-new-feature is provided. Executes the SAM implementation loop — opens an attempt per ready task, dispatches each to a specialist agent in parallel, settles and judges what comes back, manages bookend tasks (T0 baseline capture and TN verification), and tracks concerns and contract violations per task. Drives task state through the work ledger via the SAM CLI.

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 determine which backlog backend a project is configured to use, and what to do with the answer. Use when about to call a backend-specific tool, choosing between a GitHub-only and a Beads-native operation, or reporting which store a result came from.

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。

Decompose substantive work into phases, dispatch each phase to a sub-agent, and adjudicate what comes back. Use whenever a request asks for implementation, investigation, a fix, a review, or any change to files — including small ones — and whenever you are about to read source or run a diagnostic yourself instead of handing it off. Also use when a report from a sub-agent needs judging, when a phase needs re-dispatching, or when a user names one instance of a pattern. Does not apply when your own prompt begins "Your ROLE_TYPE is sub-agent." — then follow references/sub-agent-contract.md instead.

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。

Onboard a repository to skillsaw — run the linter, triage the findings by rule, apply autofixes, manually fix what remains, set up CI, and create a baseline. Use when adopting skillsaw on a new or existing project.

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。

Decide what a papercut reel should be. Picks the topic, one familiar format, the audience level, the comment-keyword funnel and caption, studies competitor reels, and runs the post-publish autopsy. Use before any hook or script, or when reviewing how a posted reel did.

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。

Interviews a researcher in rounds until an idea, design, or draft has no unexamined decision — numbered questions, each with why it matters and a recommended answer, facts looked up rather than asked, and settled decisions written to a file. Stages are idea (topic or hunch to a falsifiable question and contribution claim), design (estimand, identification, sample and power, measurement, analysis plan, pre-registration, venue), and defend (reviewer objections to a finished design or draft). Use when the user says "grill me", asks to stress-test or poke holes in an idea, design, or plan, asks what they are assuming, or brings an idea that is not yet a design. --plan grills software or process plans.

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。

Runs several language models as independent coders on one labeling or discovery task and treats disagreement as data. Covers diverse panel assembly, independent voting, consensus rules, Cohen’s and Fleiss kappa, Krippendorff’s alpha, correlated-error limits on validity claims, human validation, and reporting. Use when the user asks about a council, panel, ensemble, or jury of models, how to combine model labels, or what kappa or alpha to report for model coders. Single-model codebook and validation work goes to text-classification, per-item confidence to llm-calibration-logprobs.

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。

Runs several language models as independent coders on the same labeling or discovery task and reads their disagreement as data — panel assembly for model diversity, keeping votes independent, consensus rules, agreement statistics (Cohen's and Fleiss kappa, Krippendorff's alpha), the correlated-errors caveat that stops agreement being mistaken for validity, human validation beyond the panel, and reporting. Use when the user asks about a council, panel, ensemble, or jury of models, asks how to combine several models' labels, or asks what kappa or alpha to report for model coders. Single-model codebook and validation work goes to text-classification, per-item confidence to llm-calibration-logprobs.

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。

This skill should be used when the user asks to "write a commit message", "create a commit", "format a commit", "what commit type to use", or when preparing changes for a git commit in StreamFlow. Provides commit message format, type conventions, and examples.

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。

This skill should be used when the user runs /dd or /ㅇㅇ to act on the current OS clipboard (text or image) without pasting it into chat. It captures the live clipboard into a local cache and uses only the manifest plus a short preview as context, so error logs and reference images do not bloat the conversation. Korean triggers: "/dd", "/ㅇㅇ", "클립보드 보내줘", "이거 분석해줘", "방금 캡처한 거", "이 레퍼런스로", "스크린샷 드롭". English triggers: "/dd", "drop clipboard", "use what I copied", "this screenshot", "this reference".

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。