「ema」の検索結果

Use when the user needs to write, rewrite, review, or critique commercial copy meant to drive a reader toward action — landing pages, hero sections, headlines, email (cold outreach, nurture, promo, launch), CTAs, microcopy, product descriptions, value propositions, ads, or taglines. Also for copy audits, clarity checks, conversion reviews, or choosing a framework (AIDA, PAS, BAB, FAB, 4U's). Applies even when the user just says "write me an email" or "review this page." Not for channel/budget strategy (use channel-expert) or pricing structure (use pricing).

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FastAPI web framework conventions: APIRouter with prefix/tags/dependencies, Pydantic v2 schemas (BaseModel, model_config, field_validator, model_validator), dependency injection with Depends, async SQLAlchemy session yielding, OAuth2PasswordBearer + JWT auth, lifespan context manager, pydantic-settings configuration, OpenAPI customization, and HTTPException error handling. Activated automatically by fastapi-plugin/stack.md. Use this skill to: - Structure FastAPI apps with per-feature APIRouter modules and a central app factory. - Write Pydantic v2 request and response schemas with proper validators. - Build a reusable Depends-based dependency chain for DB session, auth, and pagination. - Implement JWT-based authentication with get_current_user dependency. - Configure the app from environment variables via pydantic-settings. Do NOT use this skill for: - SQLAlchemy ORM model configuration and Alembic migrations — see fastapi-plugin:sqlalchemy-patterns. - Python language idioms — see python-foundation:python-conventions. - Testing patterns — see python-foundation:pytest-testing.

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Generates a complete, professional client onboarding package for AI consultants, AI auditors, and solopreneurs working in the AI space (AI strategy, automation, AI readiness audits, implementation, training, etc.). Use this skill whenever a user asks to onboard a new client, set up a client folder, write a welcome email, generate a discovery questionnaire, draft a service agreement, or create a project brief — especially in an AI consulting context. Also trigger when the user says things like "I have a new client", "prepare onboarding docs", "create a client package", or "set up a new project". Produces four ready-to-use deliverables: intake questionnaire, welcome email, service agreement, and project brief.

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Use when a project context-schema differs from the installed entry format. Not for remote, publish, deploy, or irreversible changes.

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Maintain schema-governance contracts and related Odylith registry truth.

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。

Fix Elixir/Erlang AST processing bugs in Grafema beam-analyzer. Use when: (1) Elixir parser returns MODULE node but 0 functions/calls — body nesting issue, (2) Erlang parser crashes with "cannot convert list to string" on OTP 26+ — location format changed from integer to keyword list, (3) pipe operator |> creates spurious CALL nodes instead of desugared function calls — clause ordering bug, (4) multi-module .ex files return only the first module — missing __block__ handler, (5) installing Erlang/Elixir on macOS with outdated Xcode/Clang.

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Extract knowledge (decisions, facts, session metadata) from the current Claude Code session into the Grafema Knowledge Base. Run after completing a task or at any point when substantive knowledge was produced. Follows runbook _ai/runbooks/02-claude-sessions.md.

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Fix nodes silently disappearing from RFDB when an enricher or post-resolution pass writes new nodes via BatchHandle. Use when: (1) writing a TypeScript enricher that should ADD nodes/edges to existing files, (2) after calling `client.createBatch()` + `batch.addNode({file: 'X', ...})` + `batch.commit()` the original nodes in file X have vanished, (3) tests that load a graph fixture, run an enricher, then query original nodes get empty results, (4) a verification step shows expected nodes pre-enrichment but 0 post-enrichment. Root cause: `BatchHandle.commit()` invokes RFDB's `commit_batch` which AUTO-POPULATES `changed_files` from each added node's `file` field, then the server DELETES all existing nodes whose `file` matches before inserting new ones — file-level upsert semantics. This is correct for the JS/Haskell analyzers (which fully re-emit a file's contents) but catastrophic for enrichers that only ADD to existing files.

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Fix Playwright automation failures against code-server (VS Code in browser). Use when: (1) trust dialog blocks all clicks — "monaco-dialog-modal-block intercepts pointer events", (2) button:has-text() finds wrong buttons behind modal dialog, (3) keyboard shortcuts don't work — Meta vs Control inconsistency, (4) VS Code extension activity bar icon not found by aria-label, (5) panels show placeholder text despite extension being "Connected". Covers trust dialog dismissal, keyboard shortcut hybrid mode, extension panel selectors, and database connection verification for Grafema extension.

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Fires after fixing any non-trivial bug or regression. Asks: could the graph have caught this as a guarantee? Pairs with reflection-in-and-on-action — picks up after "earliest catchable signal" and asks the next question: was that signal expressible in graph? Triggers: (1) after any non-trivial bug fix is verified working, (2) after a regression report (something used to work, broke), (3) during step 6 (knowledge extraction) of the workflow, (4) when reflection-on-action surfaces a "would have been catchable" signal. Outcome is a triage decision (graph-reachable? rule expressible? rule sound?) and either a draft Linear issue + guarantee proposal, or a recorded "graph capability gap" note. Never auto-creates guarantees.

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Diagnose React + Three.js (or any browser canvas) frame stutter by capturing a CDP CPU profile via Playwright instead of guessing from `[perf]` console logs. Use when: (1) frame time is bad but `[perf]` instrumentation doesn't pinpoint the offender, (2) you've spent more than ~30 minutes "fixing" suspects without measuring, (3) hot paths involve animation systems, allocation bursts, or invisible scene-graph traversal, (4) you need self-time per function with line numbers, not aggregate "render slow". The `console.warn` pattern is good for monitoring; CDP is needed for diagnosis. Covers script template, sourcemap setup so minified function names are decoded, and interactive variant where the user drives the interaction and signals stop via `touch /tmp/<flag>`.

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Run automated QA checks on Grafema VS Code extension via Playwright + MCP cross-validation. Use when: (1) user says "/qa" to start or resume QA session, (2) user wants to validate extension panels against graph data, (3) user wants to re-check previously found bugs after a fix, (4) user wants to run a custom QA task. Requires Docker code-server running.

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Fix GraphSnapshot tests blocking CI on every feature PR. Use when: (1) every PR fails CI with "Snapshot mismatch" despite correct behavior, (2) fixing snapshots requires build → regen → commit → wait CI cycle per PR, (3) snapshot test in test/unit/*.test.js glob breaks on any intentional change, (4) pre-push hook runs pnpm build + snapshots:update on every push (2-3min overhead). Solution: move GraphSnapshot.test.js to test/unit/snapshots/ so it's excluded from the *.test.js glob. Run manually via pnpm snapshots:update when needed.

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Speed up Rust development iteration when `cargo build --release` takes 10+ minutes even for one-line edits. Use when: (1) every release rebuild takes minutes despite tiny edits, (2) Cargo.toml has `lto = "fat"` and/or `codegen-units = 1` in `[profile.release]`, (3) you want a production- shaped build for testing without paying the LTO cost on every iteration, (4) you suspect cargo is re-linking the whole binary instead of doing incremental work, (5) developing rfdb/grafema-orchestrator/large Rust binaries where full LTO is enabled for shipped builds. Adds a `fast` profile that inherits release but disables LTO, raises codegen-units, enables incremental compilation — first build still slow because it populates a fresh `target/fast/` dep cache, but every subsequent rebuild drops from ~13 min to ~13 s (≈60×).

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Fix scattered/torn regions in hex-grid simulated annealing layouts that use "competitive flood-fill" (one tile per region per outer iteration). Use when: (1) regions of >20 tiles end up dispersed instead of forming compact blobs, (2) maxDist/sqrt(N) dispersion ratio is 10×+ worse than the ideal compact blob, (3) tiles assigned to one region show up in multiple disconnected fragments across the layout, (4) the visualization has a "trypophobia ring" pattern at the perimeter where some regions spill into a perimeter spiral, (5) an overflow spiral fallback exists in the layout code and frequently kicks in for large regions, (6) bigger regions look worse than smaller ones (small regions stay compact, big ones shred). Root cause: interleaved competitive flood-fill (round-robin one tile at a time across all regions) lets large regions get boxed in by neighbors before they finish growing — the unfilled remainder is dumped into the overflow spiral at the perimeter, far from the seed. Fix: replace with sequential region-by-region BFS — process regions in size-descending order, fully claim each region's N contiguous tiles before moving to the next.

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Force `rust-embed` to re-embed assets from `$GRAFEMA_UI_DIST` (or any env-driven path) when cargo's incremental compilation skips the macro re-expansion. Use when: (1) you rebuilt the GUI bundle but the rust-server binary still serves the OLD bundle, (2) `cargo build --release` finishes in seconds (incremental hit) and `strings target/release/binary | grep <new-hash>` finds nothing, (3) any rust-embed pipeline where assets live outside the cargo source tree and are picked up via env var or symlink. Cargo only re-runs the proc macro when the rust file declaring `#[derive(RustEmbed)]` changes — env var changes alone don't trigger it.

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Build with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, load data, and develop applications with a serverless, distributed SQL database. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL and PostgreSQL-to-DSQL schema conversion, FK replacement code generation, OCC retry patterns, ORM migration (Django/Hibernate/Rails), DDL operations, query plan explainability, SQL compatibility validation, and bulk data loading. Triggers on phrases like: DSQL, Aurora DSQL, distributed SQL database, serverless PostgreSQL-compatible database, migrate to DSQL, DSQL query plan, DSQL EXPLAIN ANALYZE, DSQL ENUM, DSQL foreign key, DSQL OCC retry, DSQL multi-region, DSQL JSONB, DSQL GIN index, load into DSQL, load CSV into DSQL, bulk load DSQL, aurora-dsql-loader.

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Local SEO audit — "best [cuisine] near me" targeting, Google Business Profile optimization, NAP consistency, citation building, restaurant schema markup

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面向 Ascend PyTorch Profiler / msprof DB（如 ascend_pytorch_profiler*.db、msprof_*.db）的 SQL 分析技能。将自然语言问题（算子耗时、通信、下发、调度、schema/table 查询）转为安全可执行 SQL，并按需从官方文档提取表结构详情。

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Design the technical architecture for a NowStack Mobile app from .agents/plan/PRD.md, mapping the product onto the FIXED boilerplate stack (Convex schema + functions, Expo Router screens, Better Auth, Apple IAP/Stripe, R2), then save .agents/plan/ARCHITECTURE.md. Use for "design the architecture", "ns architecture", "plan the schema and screens", or as the second planning step after ns-prd and before ns-tasks. Not a blank-slate stack design — the stack is set; this maps features onto it.

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Plan safe Convex schema and data migrations. Use for widen-migrate-narrow rollouts, backfills, breaking field changes, table splits, or failed schema deploys.

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Редактирует русский текст по инфостилю Ильяхова. Убирает стоп-слова, штампы, канцеляризмы, голословные утверждения. Заменяет конкретикой: фактами, цифрами, пользой. Адаптирует строгость под контекст: UI, лендинги, email, статьи, саппорт. Вызывай, когда пользователь просит отредактировать, улучшить, вычистить или проверить русский текст. Also triggers on: edit Russian text, improve copy, review UX writing, fix marketing text, rewrite landing page, clean up email.

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Build applications and agents with Exa's API Platform: search, contents, answer, context, Agent API, monitors, websets, OpenAI-compatible endpoints, and exa-py / exa-js. Use when choosing Exa endpoints, writing Exa API calls, integrating semantic web search or research into products, or debugging Exa request shapes. Load references/ on demand for endpoint details.

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A senior marketing operator for any project. Orchestrates 76 marketing skills to build brands, generate content, and distribute across channels. Use this skill whenever the user wants to do marketing - brand voice, copy, SEO, email, social, launches, or anything marketing-related. Also triggers on 'help me market', 'write copy', 'launch strategy', 'brand voice', 'SEO', 'content', 'email sequence', 'social posts', 'landing page', 'grow', 'audience', 'competitors', 'what should I do next for marketing', 'I need more users', 'how do I get people to care', or any marketing request. When in doubt about which marketing skill to use, start here - even if the user's request is vague or doesn't explicitly mention marketing.

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。