「its」の検索結果

Use the moment a request is underspecified and you are about to act on an ASSUMED goal. Enumerate the candidate goals the request could mean, project the action or artifact each one implies, and check whether they diverge: if two or more plausible goals lead to materially different actions or artifacts, ask exactly ONE targeted clarifying question; otherwise proceed on the most-likely goal and state the assumption in one line. Clarification is an evidence-producing action, not a delay — but one question, never an interrogation. Distinct from gsd-spec-phase (GSD-phase-bound, emits a heavy SPEC.md) and intent-router (fetch strategy, not goal disambiguation). Backed by agent goal-state inference (arxiv 2606.16813v1). Triggers on acting under an assumed goal when the request admits more than one materially different reading.

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Master Rust async programming with Tokio, async traits, error handling, and concurrent patterns. Use when the task involves `async Rust`, `Tokio patterns`, `Rust concurrent programming`, `async traits`, or `Rust futures and streams`.

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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.

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Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.

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Audit agent lifecycle — validates agent execution capability against configuration. Accepts plugin path, runs 8 semantic audits (capability vs config alignment, skill loading correctness, inter-agent contracts, prompt contradictions, tool sufficiency, dead agents, scriptable patterns, pattern learning), writes reports to .plugin-creator/audits/. Use when auditing agent lifecycle, checking agent capabilities, verifying tool access, finding dead agents, validating agent contract alignment, or confirming agents can execute workflows.

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Use when executing a task — reads the task and its orchestrator response from the work ledger, loads task-level skills, and implements against acceptance criteria. A dispatch-owned attempt records divergences and the completion report, then closes; a direct invocation returns its task result and material divergence disposition without runner persistence or closure. Triggers on task execution within the implement-feature loop or when an agent picks up a specific task from a plan.

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One-line definitions of development-harness (dh) plugin terminology — RT-ICA, ARL, SAM, the S1-S7 pipeline stage names, Impact Radius — each with a pointer to its canonical source file. Use when a dh skill, agent, or workflow step references a term without defining it, before guessing what the term means from its observed outputs, or when asked what a dh concept or acronym stands for.

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Execute large-scale automated code transformations safely and idempotently. Use when renaming symbols across a codebase, migrating API call-sites, enforcing new patterns at scale, or applying structural edits to many files at once. Triggers on: 'codemod', 'mass rename', 'migrate all usages', 'transform codebase', 'apply pattern at scale', AST-based refactoring, or any task requiring consistent edits across 10 or more files.

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Generates and commits conventional-commits messages by analyzing staged git diffs — fast and fork-context safe. Use when the user asks to commit staged changes, needs a type-scope-description message generated from the current diff, or wants scope selection guidance and pre-commit hook handling.

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Turns raw captures (dictated braindumps in a deliverable's inbox/, or recent macwhspr dictation-log entries) into proposed planning-wiki changes, shown as one unified diff. Classifies each statement as a decision, evidence claim, question, task, or dropped item, traces it to its capture paragraph, tags unconfirmed names, numbers, and citations UNRESOLVED, and writes decisions only with the author's assent. Edits only the planning wiki, never source files. Use when asked to intake, absorb notes, or process the inbox, or after dictating notes from a talk, meeting, or reading session.

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Scaffolds or audits a social-science replication package and evaluates the manuscript and archived research objects against FAIR principles. Scaffold mode writes the folder structure, README, master.R, figure-table crosswalk, codebook, LICENSE placeholder, and .gitignore; audit mode grades the package against a pre-release checklist and audits data, code, materials, identifiers, licenses, access restrictions, and availability statements. Use when setting up or repairing a package, checking one before submission, auditing FAIR compliance, or drafting availability statements. Adapted from Yusaku Horiuchi’s replication-package-guide.

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[AUTO-INVOKE] MUST be invoked BEFORE creating git commits, PRs, or code reviews. Covers Conventional Commits, PR templates, review requirements, and AI-assisted development rules. Trigger: any task involving git commit, git push, PR creation, or code review.

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Complete DataForSEO API integration for SEO data and analysis. Use when the user asks for keyword research, search volume, SERP analysis, backlink audits, competitor analysis, rank tracking, domain authority, technical SEO audits, content monitoring, Google Trends, or any SEO-related data queries. Covers all DataForSEO APIs including SERP, Keywords Data, DataForSEO Labs, Backlinks, OnPage, Domain Analytics, Content Analysis, Business Data, Merchant, App Data, and AI Optimization APIs. Outputs CSV files.

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Works out a company's go-to-market motion (product-led, sales-led or hybrid) from its website and pricing, then maps the funnel stage by stage: a definition, strategy, leading inputs the team controls, lagging outputs with targets, cadence and owner for each stage, MQL, SQL and PQL criteria, post-sale stages, closed-lost re-entry paths and backward funnel maths from a revenue target. Triggers: "funnel strategy", "funnel stages", "pipeline stages", "PLG vs SLG", "lead qualification criteria", "map our sales process", "how do leads flow". Feeds /goals. Not for setting the target itself (use /goals).

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Synchronize existing READMEs with local Git code changes and every language edition. This skill should be used for update readme, sync readme, 更新 README, 更新项目文档, 同步多语言 README, README を更新して, README 업데이트해 줘, обнови README, or /readme-update. Ask for an exact project version or explicit unchanged choice before editing; inspect committed, staged, unstaged and untracked changes, weave each change into its natural position (never just the beginning or end), keep the flowchart current, and keep all language editions identical apart from the language.

Put a change on the one open stack of Anabasis v2 pull requests: find the real top, keep local work while moving to it, decide between appending and a new pull request, shape commits that each pass alone, run the checks CI runs (by hand where the runners do not), publish through the gating pre-push hook, write the body, repair your own children when a parent moves, and land a stack with `bun run land`. Use when asked to open, append to, stack, restack, rebase, hop to the latest head, sanitize or land a pull request, or when a push, a hook or a base refuses. v1's stack-hop and setup-pr in one.

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Launch and collect independent Codex sessions (gpt-6-luna at high, xhigh or max; gpt-6.1-sol at low to xhigh) for bounded parallel work, from Claude Code or from Codex: one manifest, one detached launcher, one report a session, a drain while it runs, and a retry of the sessions that ended without a report. Owns the Codex transport when another skill sets the questions, as whole-run-investigation does for its lanes. Use when the operator asks for Luna or Sol sessions, a swarm, many sessions, a reasoning effort, a Codex subagent from Claude Code, or a later collection of reports. Tell a request to launch from one to wait and collect.

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Hand a question about Anabasis v2 to an outside Oracle model as one task document and one zip. The Oracle reads GitHub; the zip carries what it cannot fetch: campaign logs and kept harnesses through `bun run runs zip`, a reader's output, predictions with how each resolved, patches for commits never pushed. Use when the operator asks to prepare an Oracle question, a report request, a problem statement or a second opinion on a run, a reading or a design, or to send the latest runs to an outside model. Produces local files; uploading is the operator's.

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Review changed Anabasis v2 code for reuse, simplification, efficiency and altitude, then apply the fixes. Quality only: it hunts no bugs, which /code-review does. Starts from what the repository already finds (the lint plugins, the whole-tree census, the not-slop ledger), measures before and after with reduce-complexity's scripts, and holds a pass to its budgets and to the rules no pass trades. Use as /simplify on your own diff before a commit, or when the operator asks whether code is simple enough, why something exists, to go one layer higher, or to remove something and find another way.

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Investigate one Anabasis v2 campaign from its log and turn what it shows into findings with one owner each. Answers whether a comparison's reading (step, no-step, not-scored) may be believed, whether a fail was the solver's or the exam's, whether the harness could know the exam, whether the tasks bracket the solver, whether the campaign is climbing, and where the hours and dollars went. Reads evidence; starts no solve, session or round, and changes no verdict.

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Post a sitrep (situation report) for a live incident, in its incident channel: a short fixed-layout update for people who haven't read the whole channel — the current picture and what moved since the previous update. Use on "sitrep", "status update", "where are we", "what's the latest", "catch me up", "summarize the incident so far", when asked to keep posting on a schedule ("post a sitrep every hour until resolved"), or when the oncall memory sets an update cadence for this severity and the incident owner asks Claude to keep it. Reads the channel, alert thread and findings posted, re-reads the one key signal, and writes: status line, TL;DR, impact, what changed since the last sitrep, what's in progress and who has it, what's needed, when the next update comes, one chart. Facts come only from what people said or Claude read first-hand; cause and recovery time are never guessed. Fits one phone screen. Not investigation (`incident-investigate`) or the write-up afterwards (`incident-postmortem`).

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Run SQL against Google BigQuery and browse its catalog — submit queries (sync or async), poll job status, page through results, list datasets/tables, and read table schemas. Use this whenever the user wants to query a BigQuery table, ask "what's in this dataset", check a BigQuery job's status, or mentions bigquery.googleapis.com or a `project.dataset.table` path. Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.

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The branded entry point to ServiceGraph — use whenever the user explicitly names **ServiceGraph** — "use ServiceGraph to…", "what datasets does ServiceGraph have", "search ServiceGraph for…", "look this up in ServiceGraph", "pull contacts from ServiceGraph for these domains", "how many credits do I have on ServiceGraph". ServiceGraph is a multi-dataset platform of metrics-enriched business data for founders — where to launch, who to email, who to hire. This skill explains how to drive the API (api.servicegraph.co / mcp.servicegraph.co) against ANY dataset — discover what datasets exist, discover a dataset's schema and filters, search free brief rows, and unlock contact + metric detail with credits. Dataset-agnostic by design — it discovers everything through the API and never assumes which datasets or fields exist. When the user describes an intent WITHOUT naming ServiceGraph (e.g. "find a PR agency in NY"), defer to the matching specific skill (find-pr-agency, find-marketing-agency, find-law-firm, …); this skill is for explicit ServiceGraph requests and for datasets no specific skill covers yet. Skip non-US firms, consumer/personal services, and individual freelancers.

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Show the manual page of an ASE skill, addressed by its full name, by any abbreviation of it, or by a description of its purpose, and list the entire skill catalog when no name is given. Use when the user wants the "manual", "man page", "manpage", or "help" of a particular ASE skill, or asks what a certain `ase-xxx-xxx` skill does.

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。