「its」の検索結果

Run the Anabasis v2 improvement loop, the Super Loop: find the one link that holds the climb, choose one change against it, prove its path, put a prediction on record, launch, watch, read the log, decide the next move. Use when the operator asks to keep a campaign going, to run a pass of the loop, what to launch next, why a campaign is not climbing, or what a finished round means for the next one. Owns the choice of experiment and the reading of its evidence; the operator owns promotion, a freeze, a stop, spend and the solve's condition.

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Determine the conceptual proximity of a topic -- its parent topic, its most relevant sibling topics, and its most relevant child topics -- optionally grounded in Internet/Web facts and optionally navigable in an interactive loop. Use when the user wants to explore the conceptual neighborhood of a topic, or mentions "proximity" or "related topics".

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Write the postmortem for an incident, in its incident channel, once it is mitigated or resolved. Use on "write up this incident", "postmortem", "incident summary", "what happened here for people who weren't around", "draft the retro", or when the oncall memory says incidents of this severity get one. Reads the incident channel (and the alert thread it came from), the investigation findings and the data behind them, and writes a one-screen, zero-context write-up: what happened, impact with numbers, detection, timeline with durations, why it happened, what fixed it, follow-ups with proposed owners, and one before/during/after chart. Posted and pinned in the incident channel as its final pinned post, with edit requests updating that one pinned post in place — unless the person or the team's conventions say write-ups live elsewhere, in which case it is written there and only a link is posted, nothing pinned. A person edits and publishes it; never assigns blame.

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Use when cutting a release, writing a CHANGELOG entry, or summarizing what changed since a tag — when the repo's commits follow (or mostly follow) Conventional Commits and a mechanically-accurate section breakdown beats a model's reading of the diff.

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Turn a KOL roster + subreddit brand-fit analysis into a deployable creator network. Splits creators into KOL (authority) and KOC (grassroots) layers, matches each to a main + secondary subreddits by real gear/shooting-type ∩ community fit, and emits an account×subreddit deployment_matrix (with a ≤3-per-sub ceiling + no-cross-interaction rule) plus per-creator persona_cards. Route A disclosed-compliance baked into every card (FTC disclosure required on any material connection). Consumes reddit-kol-finder's kol_roster.json natively. READ-ONLY, deterministic, no LLM key needed.

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Use on any core for first-run planning intake — Phase 0 runs the vendored BMAD-METHOD planning shelf, shared by every core, and Phase 1 (mining `04-prd.md` into intent records plus the Add-ons/sync-and-remote-entities decision) is full-stack-app's and pwa-app's shared procedure — identical mechanics, a different decision at step 5/8. Phase 0 also defines compressed intake, the path a user's explicit "just build it" choice takes on full-stack-app, pwa-app, authored, and copywriting cores: one batched round of questions in place of the shelf, writing a thinned archive at the same paths so Phase 1 (or, on copywriting, that core's own mining step), `ux-planner`, and the Re-entry pass all keep their documented source. Also use for the Re-entry pass, which mines new scope into additional intents without re-running the shelf, on any core with a module axis to add an intent to (full-stack-app, pwa-app, authored) — landing-page has none, so its own new-scope path runs through `hedgehog-landing-loop`'s Correction Protocol instead. Invoked by the `planner` agent, which decides the path; don't run standalone. landing-page runs this skill's Phase 0 on first run, then mines the same archive through `hedgehog-landing-loop`'s own planning-intake section, that core's counterpart to this skill's Phase 1. copywriting runs this skill's Phase 0 the same way (full or compressed), then mines the same archive through `hedgehog-copywriting-loop`'s own planning-intake section into a what/audience/register brief — no module axis, so its own new-scope path runs through that loop's Correction Protocol rather than the Re-entry pass below. An authored core runs this skill's Phase 0, then `hedgehog-core-design`, then this skill's Phase 1 mining against the designed layer sequence. A brownfield adoption (`hedgehog-adopt`) never runs this skill's shelf at all — the drivers BMAD elicits are already settled facts of a repo that already exists.

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ALIGN for paper figures — draw a method-overview figure as an executable p5.js program that replays its own construction in named stages, exports SVG, and improves through pixel-only cross-model review whose gate is 'explain the method back from the figure alone, and is it worth looking at'. The method sets the relationships the figure must show, the chosen visual identity sets how its marks look, a composition source lends arrangements; the method may be the source's own (意临) or yours in its arrangement (风格迁移). Not for one-shot raster image generation.

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ALIGN for paper figures — draw a method-overview figure as an executable p5.js program that replays its own construction in named stages, exports SVG, and improves through pixel-only independent Codex subagent review whose gate is 'explain the method back from the figure alone, and is it worth looking at'. The method sets the relationships the figure must show, the chosen visual identity sets how its marks look, a composition source lends arrangements; the method may be the source's own (意临) or yours in its arrangement (风格迁移). Not for one-shot raster image generation.

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Report a problem with the open-pr plugin itself, or ask for a change, on its public issue tracker. Use when a run of one of its commands left something to say. Takes no URL.

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Audits and optimizes the five global Claude layers (User Preferences, Styles, Global Memory, Skills, MCP Connectors) using the Global Layer Scorecard (six dimensions, anchored 1-5 rubrics). Detects eight cross-layer failure modes and produces evolutionary recommendations (Promotion, Demotion, Codification, Skill Extraction). Use when user says "audit my global setup," "optimize my preferences," "review my Claude configuration," "check my cross-project setup," "are my preferences working," "clean up my global memory," or "what should be in my preferences vs my project." Also use when a user has 3+ Projects and wants to improve their shared foundation. Do NOT use for single-Project audits, Project Memory optimization, or full-stack audits (use rootnode-project-audit, rootnode-memory-optimization, or rootnode-full-stack-audit respectively, if available). Run on Opus 5 or Sonnet 5 at `high` effort (both defaults); depth reduces on legacy models.

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Restore legibility to an auto-generated graph diagram that has outgrown its canvas - rendering at single-digit percent scale with sub-pixel labels. Covers the levers that measurably reduce layout units (source-level label wrapping, invisible chain links so unconnected nodes stop spreading into one row, per-cluster splitting, layout direction picked by rendering both and measuring) and the rejected ones (raising the render font is a no-op because layout engines measure in text units; a topology heuristic for direction regressed 13 of 38 diagrams). Use when a generated Mermaid/Graphviz/DOT diagram is too small to read; not for hand-authoring a small diagram.

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Conduct a GxP audit of computerized systems and processes. Covers audit planning, opening meetings, evidence collection, finding classification (critical/major/minor), CAPA generation, closing meetings, report writing, and follow-up verification. Use for scheduled internal audits, supplier qualification audits, pre-inspection readiness assessments, for-cause audits triggered by deviations or data integrity concerns, or periodic compliance posture reviews of validated systems.

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Vue 3 SFC structure, Composition API + <script setup>, file naming, project layout, props/emits/slots typing, defineModel, composables, lifecycle, watchers, UI library detection. Vue 2 fallback notes. Use this skill to: - Structure a new SFC with `<script setup>`, template, scoped styles. - Type props/emits/slots correctly via macros. - Pick `ref` vs `reactive` (prefer `ref`). - Build composables that compose cleanly. - Apply lifecycle hooks correctly. - Detect UI library (Vuetify/Quasar/PrimeVue/Naive UI/Element Plus/shadcn-vue) and mirror its patterns. Do NOT use this skill for: - State management lib choice (see vue-state-management). - Routing (see vue-routing). - Forms (see vue-forms). - Testing (see vue-testing).

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Design and review autonomous or semi-autonomous agent loops — systems where an agent prompts itself, runs on a schedule or event, and iterates toward a goal without a human at the keyboard. Use this whenever the user wants to build, design, harden, or audit any kind of self-running agent, agentic workflow, control loop, background worker, cron/heartbeat/webhook-driven agent, "Ralph loop", auto-PR-fixer, monitoring agent, or any long-running task that should keep going on its own until done. Trigger this even when the user says "agentic workflow", "automation that runs itself", "an agent that keeps trying until X", or "make my agent stop running away / burning tokens" without using the word "loop". Also use it to review an existing loop's stopping conditions, guardrails, verification, and escalation paths.

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Show one skill in full — its team record or Library folder, versions, installs, health, and its eval report when it is a team skill — as Markdown boards from the terum-skills CLI. Use when the user names a skill and asks what it is, who installed it, how it scored, or what its receipt says.

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Intake for an autonomous research run (Arbor). Use when the user wants to optimize a metric in a repo over many isolated experiments — 'optimize this benchmark', 'improve the model F1 overnight', 'beat the leaderboard'. Discovers the repo/eval/splits, measures the baseline, confirms a Research Contract, then emits a ready-to-send /auto-research command. Does NOT start the run itself.

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Use when handling external API rate limits (e.g., OpenAI 429s, HubSpot or Stripe rate limits), preventing duplicate work from rapid event bursts (debouncing user actions), spreading load over time, ensuring per-tenant fairness, processing events in batches, limiting concurrent runs of the same operation, or assigning priority to important runs. Covers Inngest flow control: concurrency limits with keys, throttling, rate limiting, debounce, priority, singleton, and event batching.

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Use when a task needs the judgment of a Compensation and Benefits Manager — designing or evaluating a pay structure/leveling system, benchmarking compensation against market, deciding on a benefits package tradeoff, or auditing for pay equity issues. Narrower and more specialized than the broader hr-people-manager role's compensation-adjacent heuristics.

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Use when a task needs the judgment of an Automotive Engineer — computing weight transfer and tire friction-circle limits for a braking-while-cornering maneuver to set brake-force distribution, sizing a powertrain and gear ratio against a 0-60 mph acceleration target while checking traction versus power limits, sizing a crumple zone's crush distance against FMVSS 208 occupant-deceleration limits, or checking a powertrain-mount or driveline natural frequency against engine firing-order excitation for NVH isolation. Distinct from an automotive-service-technician (diagnoses and repairs a vehicle already designed) — this role owns the system-level design decisions (structure, powertrain sizing, suspension geometry, restraint/crash structure, NVH) that produce the vehicle the technician later services.

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Update an OpenSpec change by revising its existing planning artifacts and keeping them coherent with one another. Use when the user wants to revise a change's plan, fold new decisions into it, or reconcile its artifacts after an edit. Also use when the user says "openspec update change" or "opsx update". If the user means the openspec update CLI command, which refreshes generated files, run that command instead. Never edits code.

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Run a source-grounded paid-advertising audit for one or more of Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, and X. Use for full ad checks, account health reviews, paid-media diagnostics, partial audits after authentication or worker failure, missing-platform weighting, beta-feature eligibility and scoring, spend audits, tracking audits, or prioritized opportunities and risks.

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Use when setting up, configuring, or troubleshooting Marketing Cloud Journey Builder — including entry sources, activities, decision splits, wait activities, goals, exit criteria, journey versions, test mode, or journey analytics. Triggers: 'journey builder setup', 'entry source configuration', 'decision split not routing', 'exit criteria not removing contacts', 'goal not tracking conversion', 'journey version publishing', 'journey re-entry settings', 'wait activity date field'. NOT for coding a custom activity or entry source — use apex/marketing-cloud-custom-activities. NOT for business units and sender profiles — use admin/marketing-cloud-engagement-setup.

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Enrich customer/lead profiles with business data using [LeadIQ](https://composio.dev/toolkits/leadiq), [RocketReach](https://composio.dev/toolkits/rocket-reach), or [Clearout](https://composio.dev/toolkits/clearout)

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Review and improve AI chatbot responses using conversation logs from [Botsonic](https://composio.dev/toolkits/botsonic), [Docsbot](https://composio.dev/toolkits/docsbot-ai), or [Landbot](https://composio.dev/toolkits/landbot)

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。