「scribe」の検索結果

Classify a proposed code change as Leaf Node or Core Code to decide how much AI usage and review rigor is appropriate. Use this skill whenever the user asks "is this leaf or core", "what kind of change is this", "should I vibe code this", "can AI write this", "how rigorous should the review be", or before starting any non-trivial change. Also useful as a sub-step inside other workflows (planning, PR prep, code review) when classification matters. Asks 6 diagnostic questions about propagation range, change frequency, tech-debt tolerance, examples, failure cost, and review intensity, then outputs a clear classification with the recommended approach. Trigger even when the user describes a change without explicitly asking for classification — the answer changes how they should proceed.

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The measurement surface for ALL Pulp DSP and audio-pipeline work — read it BEFORE writing or gating DSP, not only when something already sounds wrong. Covers the C++ harness (signal generators, metrics, assertions, RenderScenario, contracts), the offline Audio Doctor (magnitude/frequency response, THD/THD+N, phase/group delay), and their Python sibling the Audio Quality Lab (tools/audio/quality-lab — null residual + alignment, LTAS log-spectral distance, spectral flux/centroid, HNR, Theil-Sen drift slope, Kaiser-sinc resampling, license-guarded corpus, regression-net ratchet). TRIGGER on AUTHORING work — "build/design an oscillator/filter/synth/effect", "add a DSP module", "what should the acceptance gate be", "how do I measure aliasing / anti-aliasing / alias floor", "null against a reference", "is this DSP correct", "choose a tolerance", "golden/regression corpus for audio", "measure drift or jitter", "A/B two renders" — AND on DEBUGGING work — "is there sound / no audio / I hear nothing", "does this filter/compressor/synth/delay produce the right signal", "prove the DSP / prove the contract", "measure the frequency response", "what's the THD / is it distorting", "what's the group delay / phase response / measured latency", "magnitude response curve", "render a test tone and assert", "audio regression", "64-frame works but 128 is silent", "sample-rate change pitch-shifted it", "describe what's in this buffer", "audio doctor", "compare before/after a DSP refactor". Reach for this BEFORE hand-rolling any FFT, null test, alias measurement, pitch tracker, or golden-render script — most of it already exists in one of the two lanes. Test/tool layer over HeadlessHost — deterministic, no audio device, no speakers. Off the realtime thread entirely.

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LV2 format adapter for Pulp — the Turtle manifest the build emits by asking the module to describe itself, port indices as a saved-session wire format with one shared layout, host transport arriving as a time:Position atom on the MIDI port, the optional buf-size feature that is a hint and not a guarantee, state:interface versus control ports, and the real-time rules run() has to keep.

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Traces and documents signal paths, bus/aux architecture, and sidechain connections in audio systems. Surfaces hidden coupling between audio components. Use when the user asks to trace a signal chain, explain audio routing, understand an audio graph, locate sidechain sources, or describe how audio flows through a plugin or engine. Trigger on phrases like "trace this signal chain", "explain this audio routing", "what calls what in this audio graph", "where does the sidechain come from", "how does audio flow through this plugin".

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Systematic checklist for diagnosing audio artifacts. Use when the user describes a sound quality problem — clicks, pops, crackling, silence, DC offset, aliasing, phase issues, or latency problems. Trigger on phrases like "why do I hear clicks?", "my output has DC offset", "there's aliasing in my oscillator", "phase is wrong in mono", "dropout when CPU spikes". Pairs with audio-dsp-review (realtime safety) and audio-numerics-review (numeric correctness) — use those to fix once the cause is found.

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Before designing, training, or auditing ANY model that replicates human-annotated labels, audit the annotation protocol's INPUT — the exact document/evidence the human labelers consulted — and give the model that same input. Use when: (1) designing a classifier/LLM extractor whose target is a hand-coded label set, (2) a label-replication model shows low recall concentrated in a label subset and the diagnosis on offer is "the label's information is not in the features", (3) reviewers propose construct splits (e.g. "designation vs record-evident"), adjudication sittings, or per-domain stop rules to explain residual disagreement with gold, (4) validating an extraction pipeline against labels transcribed from a source document. Symptom of the underlying failure: elaborate theory accumulates to explain why gold is "partially unpredictable" when the model was simply never shown the document the annotators read.

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Use when implementing new observable frontend behavior or fixing a behavior-changing bug where a failing test can describe the missing or incorrect behavior first. Apply to components, hooks/composables, utilities, API clients, route guards, or user workflows; pure behavior-preserving refactoring uses an already-green contract instead.

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Comprehensive social media operations for B2B SaaS brand building and engagement. Use this skill to develop LinkedIn strategy, decide whether to run a LinkedIn newsletter and how to scope it, capture consented registrations from LinkedIn Events, check LinkedIn Live eligibility, manage Twitter/X presence, create YouTube content, engage on Reddit communities, decide whether and how to answer on Quora, build community, develop influencer and creator partnerships, vet a creator before paying them, start or fix a B2B podcast, book podcast guests and guest appearances, judge whether a podcast is worth appearing on when you cannot audit its numbers, write show notes and transcripts, run social listening (what are people saying about us, share of voice, brand monitoring, validated sentiment, alert thresholds, routing signals to the right owner), and execute organic social campaigns. Also triggers on: LinkedIn, LinkedIn newsletter, LinkedIn Events, LinkedIn Live, event registration form, subscribe to our newsletter on LinkedIn, marketing consent checkbox, Notify Employees, Twitter/X, YouTube, Reddit, community, influencer, creator partnerships, influencer vetting, engagement rate, fake followers, engagement pods, FTC disclosure, sponsored post disclosure, media kit, social media strategy, organic social, employee advocacy, podcast, podcast strategy, podcast guesting, how do I know if this podcast has real listeners, the host says they get 50k downloads, is this podcast worth going on, podcast RSS feed research, IAB podcast measurement certification, Listen Score, Apple Podcasts reviews, show notes, audiogram, episode transcript, social media account access, who has admin on our LinkedIn page, the person who ran our social accounts left, locked out of our company account, social media offboarding, YouTube channel owner, Slack primary owner, social account MFA, social media approval workflow, pause all scheduled posts, social listening, what are people saying about us, brand monitoring, brand mentions, share of voice, social share of voice vs competitors, sentiment analysis, is our sentiment dashboard accurate, listening query, boolean query, mention alerts, spike alert, CrowdTangle replacement, Reddit API access, which platforms can our listening tool see, someone on Reddit asked for a tool like ours, comment mining, voice of customer from social.

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Client reporting, quality assurance, and financial operations management. Handles KPI frameworks, compliance audits, budget tracking, and launch checklists. Use when: managing client dashboards, ensuring brand compliance, conducting QA reviews, tracking marketing spend, ensuring GDPR/CAN-SPAM compliance, handling a request to delete someone's data across the marketing stack, deciding whether an AI voice or AI presenter has to be disclosed, proofreading deliverables. Also triggers on: client reporting, QA, quality assurance, brand compliance, marketing budget, financial tracking, legal compliance, GDPR, CAN-SPAM, proofreading, launch checklist, right to erasure, right to be forgotten, data deletion request, DSAR, someone asked us to delete their data, do we delete or suppress, suppression list, they unsubscribed and we emailed them again, we deleted them and they came back, restored a backup and re-emailed people, custom audience still has deleted contacts, California Delete Act, DROP, data broker deletion, enrichment records disappearing

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Use when a task needs the judgment of a Conservation Scientist — writing or reviewing a rangeland/forest conservation plan, calculating stocking rate or carrying capacity against a proposed grazing or timber plan, scoping a prescribed-fire prescription, resolving a multi-use land-allocation conflict on public or private land, or assessing range/forest condition trend from monitoring data.

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Use when a task needs the judgment of a computer programmer implementing to a given specification — translating a design/pseudocode/systems-analyst spec into working code in a specified language, flagging spec ambiguity before writing code, maintaining or modernizing an existing codebase against its original contract, or writing unit tests that prove the implementation matches the spec (not designing the system the spec describes).

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Verify that an application works correctly using `stably verify`. Use when an AI agent has made code changes and needs to validate the feature works in a real browser. The command describes expected behavior in plain English and reports a PASS/FAIL/INCONCLUSIVE verdict — no test files generated. Triggers on: "verify this works", "stably verify", "check if this works", "validate my changes", "verify my feature", "does this work", "check the app", "verify the feature".

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Use when operating Volcengine TLS (日志服务) through volclog in agent or CI sessions and you need a contract-first workflow for runtime selector resolution, discover/describe/exec routing, App resource or Topic resolution, envelope reading, large-result delivery, and error recovery without guessing commands, fields, or shortcut flows. 当用户提到火山引擎日志服务 TLS、volclog、日志检索/分析/导入/导出、 日志项目或日志主题等操作时调用。

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Create and manage Volcengine cloud resources using the Volcengine CLI (`ve` command). Supports all Volcengine services including ECS, VPC, CLB, RDS, Redis, and more. Trigger this skill whenever the user asks to create, query, modify, or delete cloud resources on Volcengine, mentions the `ve` command, says "volcengine CLI", or describes infrastructure tasks such as "create an ECS instance", "set up a VPC", "list security groups", "allocate an EIP". Also trigger on Chinese prompts mentioning "火山引擎" or "火山" (e.g., "火山引擎上有哪些 ECS"、"查一下我火山的云服务器"、 "火山引擎创建一个 VPC"、"火山的 Redis 实例列一下"). Also trigger when the user encounters errors from `ve` commands and needs troubleshooting help. Also use for TOS bucket/object operations, tosutil (sometimes written tosutils), Ark CLI / arkcli model discovery, inference, generation, endpoints, fine-tuning, plans, or usage, and TLS (日志服务) / volclog log search, analysis, ingest, export, or LogCollector collection, through `ve tosutil`, `ve arkcli` and `ve volclog`.

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Propose a new OpenSpec change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation. Also use when the user says "openspec propose" or "opsx propose".

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Craft high-quality natural-language image prompts for any modern text-to-image or image-edit model that accepts flowing English. Trigger when the user wants help writing, rewriting, improving, or translating an English natural-language image prompt — including "write me an image prompt", "improve this image prompt", "describe this scene for an image model", or "convert these tags into a natural language prompt". Do NOT trigger for requests that are purely about dispatching to an image API, choosing samplers/schedulers, picking LoRAs, or setting up ControlNet — those belong to a runtime skill.

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Create a git commit with clear, conventional commit messages. You MUST read this when the user wants to commit staged changes, write a commit message, or finalize code changes with proper conventional commit format since it describes how to follow the user's specific requirements.

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Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.

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Read and manage the user's Klaviyo email and SMS marketing campaigns, newsletters, flows, subscriber lists, and audience segments. Use to compare campaign performance and revenue, find recent customers, plan audience targeting, and manage marketing content and subscriptions through Klaviyo's official MCP server.

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Work with the user's Gmail: search, read threads, draft, send, reply, forward, unsubscribe from mailing lists, manage labels, and open attachments.

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Write a clear pull request description. Use when the user says "write a PR description", "PR template", "pull request description", "how do I describe this change", "commit message for this", "document this change", "open a PR for", or is about to merge code and needs to communicate what changed and why - even if they don't explicitly say "PR description".

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Write recurring newsletter issues with a consistent format and POV using the Curiosity Gap (George Loewenstein) and David Perell's Online Writing framework. Different from one-off emails (use /content-writer or /email-nurture). Use when the user asks for a newsletter, weekly/monthly newsletter, "write this week's issue", recurring email, Substack issue, internal newsletter, or any periodic publication with subscribers. Reads brand voice and content library from knowledge/. For a nurture or lifecycle sequence, see email-nurture. For long-form thought leadership, see thought-leadership-writer. For the monthly plan, see social-calendar.

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Debug a bug or unexpected behavior systematically. Use when the user says "there's a bug", "this isn't working", "I'm getting an error", "help me debug", "why is this failing", "unexpected behavior", "test is failing", "something is broken", or describes behavior that doesn't match expectations - even if they don't say "debug".

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Assess whether your leadership behaviors amplify or diminish your team using Liz Wiseman's Multipliers framework. Use when a leader asks "am I a good manager", "why isn't my team performing at their potential", "I feel like I'm doing all the thinking for my team", "my team seems dependent on me", "I want to be a better leader", "how do I empower my people", or "my team is smart but underperforming". Also trigger when someone describes always having the best ideas in the room, team members not taking initiative, reports waiting for direction before acting, or a leader who feels exhausted from carrying the team. Diminisher patterns are often invisible to the leader exhibiting them.

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。