「auditing」の検索結果

Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.

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Review a written plan or design doc through a designer's lens before implementation - seven passes over information architecture, interaction states, emotional arc, AI-slop risk, design-system alignment, responsive and accessibility coverage, and unresolved decisions. Each dimension is rated 0-10 with an explicit statement of what would make it a 10, then the plan is edited to get there. Use when a plan has a UI surface and you want the design gaps closed before code is written. Not for auditing a live site.

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Design leakage-safe machine learning experiments that mirror real deployment and support fair model comparisons. Use when defining prediction timing, feature eligibility, train-validation-test splits, baselines, metrics, or controlled model iterations; not for auditing whether raw labels are trustworthy.

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Audit datasets, joins, labels, and ground truth before analysis or modeling. Use when data meaning, row grain, time semantics, source-of-truth reliability, or label construction may invalidate conclusions; not for general model evaluation after the evidence base is already trusted.

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Finalize code changes for production readiness by removing duplicate logic, auditing hardcoded values, verifying branch/worktree intent, verifying build integrity, structuring clean commits with Conventional Commits format, and forcing a post-publish branch/worktree cleanup decision.

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Use when reviewing, auditing, or optimizing skills — validates against the 7 Skill Killers checklist and produces fix recommendations.

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Use when ranking competing initiatives for a roadmap, breaking a tie between two features, or auditing a backlog for hidden low-value work via Reach × Impact × Confidence ÷ Effort.

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Use when designing or auditing a sales pipeline — stage exit criteria, per-cell conversion, coverage reasoning, leak detection. Triggers on 'tighten our pipeline', 'where is the leak'.

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Use when decomposing a company objective into team OKRs, auditing a draft OKR tree, or stress-testing an existing one for measurability and laddering.

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Use when defining or auditing the activation event — aha-moment selection, retention correlation, falsifiable definition. Triggers on 'what is our aha moment', 'redefine activation'.

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Apply the Opquast Digital Quality Framework (245 rules, 14 categories) when building, reviewing, or auditing websites and web applications. Use for web development quality assurance, accessibility compliance, security hardening, privacy implementation, e-commerce best practices, and holistic digital quality checks.

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[Architecture] Use when auditing the ENTIRE project architecture and production readiness in one pass — bundles architecture-review + architecture-scalability-review + production-readiness-review at project or diff scope, then synthesizes one consolidated Architecture Health Report.

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Scaffold and formally review a new Agent Skill in this marketplace repo. Covers valid SKILL.md generation, directory layout, registry entries, and spec auditing. Use when adding a skill, validating frontmatter, or checking marketplace readiness before a PR.

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Requires durable citations when authoring or researching Agent Skills—maintain references/sources.md per skill, link external research, and record provenance in PRs. Use when creating skills, updating SKILL.md, doing web research for skills, or auditing missing sources.

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Manage agent-skill lifecycles across local, global, project, Skill Hub, skills.sh, GitHub, plugin-cache, and system roots. Use when searching, recommending, installing, updating, upgrading, syncing, merging, auditing, deduplicating, cleaning, packaging, publishing, or validating skills; choosing project versus global scope; verifying upstream source, stars, or installs; or working with skill-upgrade, check_upstreams.ps1, sync-pull/push, junctions, skills-lock.json, or skill-upstreams.json. Do not use for ordinary software-package upgrades or non-skill file cleanup.

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Use when writing, moving, reviewing, or auditing documentation in the deepseek-harness repo — choosing hierarchy and detail, separating tutorials from references, checking tutorial progression, trimming doc slop, responding to a verify-doc-budgets failure, or requests like "improve the docs", "audit the docs", "where should this be documented", or "this doc is too long".

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Use when adding, auditing, pruning, archiving, restoring, or reviewing Agent Notes in deepseek-harness; checks every new note for superseded active records, classifies implemented notes by future decision value, deletes rejected notes that no longer prevent a tempting fallacy, and applies the frozen archived/{kind} triplet and manifest rules.

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Use when auditing or fixing prose that reads like a leaked reasoning transcript — dead design-session citations such as (decision N), audit item codes, or §N of uncommitted drafts; change narration such as "used to", "no longer", "this cut"; stack or review vantage ("a later PR in this stack", "rejected in review"); reviewer-addressed justifications; control-flow narration; or hedged planning residue in comments, JSDoc, docs, or Agent Notes.

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Use when writing, reviewing, restoring, trimming, or auditing prose in the deepseek-harness repo, including deciding where documentation or comments are required across Markdown, JSDoc, code and test comments, prompts, descriptions, diagnostics, and CLI or UI strings.

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Protected Health Information (PHI) and Personally Identifiable Information (PII) compliance patterns for healthcare applications. Covers data classification, access control, audit trails, encryption, and common leak vectors. Use when code touches PHI or PII in a healthcare system, or when auditing access control, audit trails, or leak vectors.

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All animation knowledge for HyperFrames — atomic motion rules, multi-phase scene blueprints, scene transitions, broader motion-design techniques, AND the seven runtime adapters (GSAP default, plus Lottie, Three.js, Anime.js, CSS keyframes, Web Animations API, TypeGPU). Use for any motion or animation task: pick 2-4 rules and compose, or load a blueprint, or look up runtime-specific API (e.g. GSAP eases / Lottie player / Three.js mixer). Also covers auditing an existing composition's choreography (animation map) and 24 named text-animation effects. HyperFrames-native: single paused timeline, seek-safe, deterministic.

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Manage Agent Skills across Codex, Claude Code, local/global/project roots, Skill Hubs, GitHub, skills.sh, and managed plugin caches. Use when searching, installing, updating, upgrading, syncing, merging, auditing, deduplicating, cleaning, packaging, publishing, validating, resolving upstream sources, choosing runtime or scope, or working with skill-upgrade, check_upstreams.ps1, Claude Code plugins, skills-lock.json, or skill-upstreams.json. Do not use for ordinary software-package upgrades or non-skill file cleanup.

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Durable categorized record-keeping for any predicate-enabled walk. Trigger when: - Classifying a step's output for recording (decision, finding, debt, feedback). - Promoting a scratch artifact to the ledger, to repo/docs, or to a category home (.ledger/tech-debt/, .ledger/process-feedback/). - Auditing whether a draft is structurally ready for its destination. - Running a zero-context sensibility read before committing to promotion. - Recording a known limitation as a tech-debt entry (not prose in the log). - Recording a friction, miss, improvement, or process amendment. - Prompt contains: /record, record-keeping, promote, ledger note, zettelkasten, scratch-to-ledger, zero-context read, over-strip, classification trigger, tech-debt, process-feedback, amendment.

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Normative sufficiency conditions for Initial Boundary Conditions (IBCs) and the SOP for the cheap-tier boundary refinement loop (/boundary). Trigger when: - Crafting, auditing, or refining a prompt/IBC destined for an expensive (architect-class) model or an autonomous worker dispatch. - Evaluating whether a task frame is sufficient to bound an agent walk. - Prompt contains: /boundary, IBC, initial boundary condition, boundary contract, sufficiency conditions, worker prompt, prompt refinement.

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。