「surface」の検索結果

Semantic Python code queries via a stdio LSP client driving pyright-langserver. Provides binding-resolved go-to-definition, find-references, hover types, type diagnostics, file symbol outlines, and project-wide symbol search — name resolution and type inference that tree-sitter and ripgrep cannot do. Use when you need to follow an import to a definition, find all real uses of a symbol (excluding same-named-but-unrelated ones), get an inferred type, surface type errors, outline a file, or search symbols across a project. Triggers on "go to definition", "find references", "what type is", "resolve this symbol", "symbol outline", "find symbol in project", "pyright", "type-check this file".

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。

Draws images, PDF/SVG vector files and animation frames with pycairo, and supplies what cairo lacks: shaped text for Arabic, Indic and other scripts, text along curves, blur/glow/drop shadows, path booleans, stroke-to-outline, and Gouraud-shaded 3D. Use when writing pycairo or cairo drawing code, generative art, custom diagrams or posters rendered in Python, or when cairo output needs non-Latin text, soft effects, merged shapes or shaded surfaces.

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。

Periodic multi-reviewer sweep of the whole codebase — surfaces a triaged checkpoint report.

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。

Stop everything and surface a rule conflict — persona vs. docs vs. code. Present both sides and the conflict-hierarchy level; the user resolves. No silent reconciliation.

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。

Route HugeGraph MCP regression testing tasks to the current public tool surface, including inspection, read-only queries, Gremlin generation, extraction, controlled import, schema validate/dry-run, safety guards, and admin-gated tool checks.

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 an agent or harness needs to drive the full tiny.place network from the command line — register an @handle identity, search the open directory, read/post to channels and broadcasts, send and acknowledge encrypted messages, manage inbox items, fund and win bounties (contest-style work), read reputation, fetch pricing, manage approved signers, settle/verify x402 payments and subscriptions, and read the ledger. Wraps the flagship TypeScript SDK CLI (`tinyplace`), which carries the complete API surface.

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。

FLOW framework integration — evidence-led SEO using the Find → Leverage → Optimize → Win loop. Surfaces stage-specific AI prompts from the FLOW knowledge base (41 prompts, CC BY 4.0). Use when user says "FLOW", "FLOW framework", "seo flow", "evidence-led SEO", "find leverage optimize win", or wants stage-specific SEO prompts.

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。

Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.

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。

Blog strategy development including topic cluster architecture with hub-and-spoke design, audience mapping, competitive landscape analysis, AI citation surface strategy across ChatGPT/Perplexity/AI Overviews, distribution channel planning (YouTube, Reddit, review platforms for GEO), content scoring targets, measurement framework, and content differentiation through original research and first-hand experience. Use when user says "blog strategy", "content strategy", "blog positioning", "what should I blog about", "blog topics", "content pillars", "blog ideation".

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。

When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' or 'optimize for Claude/Gemini.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema.

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。

Counts and compares blog posts across a target and competitors, audits content freshness via sitemap lastmod dates, and maps competitor organic keywords (US, non-branded, informational) against the target to surface ranking gaps. Use when asked to compare blog counts, content volume, publishing cadence, content freshness, keyword mapping, keyword gap analysis, or competitor keyword reports — e.g. "how many blog posts does X have vs Y", "how fresh is content on X", "where does [target] rank for [competitor] keywords", "keyword gap between X and Y". Works from company names alone. Always use for blog comparison, freshness audits, and keyword mapping tasks.

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 assessing the architectural health of a codebase — before a major refactor, when onboarding to an unfamiliar repo, after rapid growth, when planning a redesign, or to surface structural strengths and risks before they become expensive. Not for fixing what it finds, and not for reviewing a branch diff.

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。

Open Analytics' design language, extracted from the shipped product: an ink-derived neutral system, squircle surface anatomy, one small spring vocabulary, pixel-matched skeletons, and a plain-spoken copy voice, with type-checked component recipes. Use this whenever you build or restyle a dashboard, SaaS app, analytics UI, settings screen, onboarding flow, or marketing/landing page that should feel calm, dense and native, and whenever the user mentions Open Analytics' look, 'clean SaaS design', cards, dropdowns, tab bars, empty states, skeletons, or UI animation quality, even if they never say the words 'design system'.

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。

Suede-owned operations-assessment discipline that maps how work actually happens before anyone designs a system: floor-level interviews with the people who do the work, an inventory of every silo including spreadsheets and inboxes used as databases, friction quantified in the requester's own numbers, opportunities ranked by annual value against build complexity, and adoption watched for the thirty days after launch. Use when nobody can answer what to automate, when an operation needs auditing before a build, when tribal-knowledge and key-person risk has to surface, or when a shipped system is quietly being routed around. NOT FOR: deciding what to build and in what order once the map exists (use suede-ops-architecture); researching external customers rather than internal operators (use suede-customer-research); lead lifecycle, scoring, and CRM routing rules (use suede-revops); product instrumentation and dashboards (use suede-analytics); getting a new user to first value (use suede-onboarding).

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。

Suede Labs skill that lints a local music or media release folder and scores it for release readiness: missing files, weak or malformed metadata, artwork and stem problems, split gaps, rights blockers, and platform-delivery issues, produced by a bundled offline script as a scored markdown and JSON report. Use when a creator has one or more release folders of tracks, artwork, and stems and wants to know what is missing before distributing, delivering, or handing it off; when metadata quality or a delivery rejection is the question; or when a release-readiness score is asked for. Reports what is present, missing, or unknown; never upgrades unknown to confirmed and never means legal clearance. NOT FOR: organizing the evidence behind a rights or split gap the report surfaces (use suede-rights-audit); building the transfer package (use suede-rights-passport); a sync one-sheet (use suede-sync-packaging).

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。

Suede-owned measurement discipline for tracking plans, event and conversion instrumentation, UTM and campaign-parameter hygiene, and verification of what actually fires. Use when setting up, auditing, or repairing analytics across web, product, paid, and lifecycle surfaces. NOT FOR: experiment design or significance decisions (use suede-ab-testing), campaign optimization (use suede-ads), attribution models, model comparison, or cross-tool reconciliation (use suede-attribution), or revenue-process architecture (use suede-revops).

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。

Suede AI design skill for making an interface feel intentional instead of templated: design tokens, color strategy, OKLCH ramps, type scale, fluid type, visual hierarchy, dark mode, spacing, component laws, motion, and source-to-implementation visual QA. Use when asked to design, restyle, polish, or audit a screen; pick colors or fonts; define, fix, or document design tokens; build or repair a dark mode; review a component or a whole design system; or compare a mock, Figma frame, or reference screenshot against a rendered implementation. NOT FOR: a full design-plus-copy build, launch surface, or reference-to-target restyle (use johnny-suede-design); conversion and funnel architecture (use suede-site-alchemy); writing the words themselves (use suede-copy).

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。

Suede AI findings-only code review with full context: changed files, callers, contracts, and deploy surface. Covers TypeScript, React, Next.js, database, Swift/iOS, OWASP, accessibility, SEO, observability, commit hygiene, and deploy risk, ranked P0-P3 with file:line evidence and a fix path. Use when asked to review a diff, PR, branch, or commit range, find the bugs before merge, check a change for security or accessibility problems, or judge whether a change is safe to deploy. Emits findings and a ship gate, not a grade. NOT FOR: the A-F letter grade alone (use suede-code-grader); findings plus grade in one pass (use suede-code); making CI enforce the result on every merge (use suede-ci-gate); root-causing a live bug or failing test (a private Suede Labs companion, not in this pack).

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。

Suede-affiliated marketing deliberation that applies documented public frameworks through clearly labeled simulated advisors, surfaces disagreements, and synthesizes a decision. Use when the user wants multiple expert lenses on one bounded marketing question. NOT FOR: factual claims about a living person's private views, primary research (use suede-customer-research), or executing the selected tactic (route to the relevant public Suede skill).

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。

Suede AI blunt A-F ship grade for a code change across correctness, security and permissions, data and state, domain truth, UX and release behavior, tests and verification, and deploy readiness, with Instant-F triggers and evidence-based grade caps on auth, payment, migration, and public-API surfaces. Use when asked to grade this, give it a letter, is this an A, how ready is this to ship, or should this merge: when the caller wants the verdict without a findings list. NOT FOR: findings, evidence, and fix briefs (use suede-code-review, or suede-code for findings plus grade); enforcing the verdict in CI (use suede-ci-gate); eval coverage for AI behavior (use suede-ai-eval).

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。

Suede-affiliated AI search optimization discipline. Use when the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' 'optimize for Claude/Gemini,' 'llms.txt,' 'OKF,' 'Open Knowledge Format,' 'knowledge bundle,' or 'agent-readable site.' The durable job: make content structurally extractable, citable, and agent-readable so AI systems surface and cite it. NOT FOR: traditional technical SEO audit (use suede-seo-audit) or launch-appeal grading (use suede-visibility-grader).

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。

Brainstorms and debates approaches, then drives toward an actionable decision. Use whenever someone needs a thinking partner for a decision they're facing: 'discuss', 'debate', 'brainstorm', 'weigh options', 'tradeoffs', 'should I do X or Y', 'help me decide', 'I'm torn between', 'sanity check my thinking', or 'what do you think about'. The user must be asking for help reasoning through a choice — not asking to build, fix, evaluate, plan, or modify something (even if the topic involves this skill itself). Picks the right decision lens, surfaces tradeoffs and blind spots, pushes back when reasoning is genuinely weak, and never implements.

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。

Identify and challenge implicit assumptions in plans, proposals, and technical decisions. Use when strategic-cto-mentor needs to surface hidden assumptions and wishful thinking before they become costly mistakes.

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 verifying a running application end-to-end through its real interface — a web UI, a CLI, or a TUI — by writing and executing agent-run "scenario cards" against a freshly built instance with falsifiable assertions. Trigger on "test it end to end", "prove the UI actually works", "write/run a scenario", or after a change touches a user-facing surface that unit tests can't fully cover. Not for unit tests, pure code review, or API-only checks.

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。