「output」の検索結果

Creates an SVG weather card showing the current temperature and writes it to orchestration-workflow/weather.svg and orchestration-workflow/output.md

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。

Assemble the final `.ppmplugin` binary bundle for a PAM native extension and verify its contents. First **reconciles** the manifest's declared `entrypoints` against the binaries actually staged — if the manifest declares a platform with no built binary it gates (build it / ship without it / stop) rather than shipping a broken bundle. Then re-runs the plugin's upload-compatibility checks on the reconciled manifest, zips the manifest plus whichever of `android/<PascalName>Plugin.dex` and `ios/<PascalName>Plugin.framework/` are present into `ppmplugin/<name>.ppmplugin`, and verifies the archive layout with `jar tf` (exactly the manifest + the shipped binaries — nothing missing, nothing extra). Output: a statically verified `.ppmplugin` file on disk. Prereqs: `jar` (JDK). Run after /generate-ppmplugin-manifest and the build skill(s).

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。

Integrates Power Pages generative-AI summarization APIs (PREVIEW) into a Single Page Application (SPA) site — the Search Summary API and the Data Summarization API — on any record-detail or list page. Generates per-target service code (CSRF-handled) and AI site settings; delegates Web API settings, table permissions, and web roles to `/integrate-webapi` and `/create-webroles`. Use whenever a user wants AI/Copilot output that condenses Dataverse content on a Power Pages site — an AI summary, AI-generated overview or "key insights" across a record or list, a search-results summary, a case/incident summary, or recommendation-chip refinement — even when phrased as "AI-generated paragraph", "insights", or "overview". Do NOT use for: generative pages in model-driven apps (use the model-apps `genpage` skill), Copilot Studio agents/chatbots, summarizing documents or PDFs, Power BI dashboards, plain keyword search with no AI summary, or plain Dataverse CRUD (use `/integrate-webapi`).

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。

Diagnose and fix failures in a built third-party `.ppmplugin` control: crashes, silent no-ops, PCF error outputs, or incorrect behavior. Uses the reported symptom, `shared/error-codes.md`, and file-level evidence to trace the manifest, Android/iOS modules, PCF dispatch, and build configuration. Produces a ranked diagnosis, asks for approval, then applies a surgical fix while keeping the committed manifest and affected contracts synchronized. Re-validates manifest changes through /generate-ppmplugin-manifest.

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 the user has finished building a mobile app, started Metro with `npm run dev`, and wants the running app monitored for runtime errors AND silent failures (empty lists, blank screens, swallowed network errors) and fixed autonomously. Accepts a free-text symptom (e.g., `/debug-app "todos not appearing on home screen"`) to drive persisted-log diagnostics — injects temporary console.log statements at data-path boundaries, reads the sanitized `.powernative/metro-logs/` log, and cleans up logs after the root cause is fixed. Supports port/platform filtering, configurable clean-cycle and timeout limits, and watch-only `--no-fix` mode. Otherwise polls with a durable byte cursor, fixes inline or routes appropriately, verifies each fix from new output, and exits after the configured clean checks (default 3). Foreground loop — blocks the conversation while running. Run only after the app is loaded.

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。

Manufacturing and fabrication workflow for KiCAD projects via MCP tools. Triggers on: "send to fab", "order boards", "gerbers", "JLCPCB", "manufacturing", "export for production", "pick and place", "assembly files", "generate fabrication outputs", "BOM for fab", "production files", "fab house".

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。

Production-ready scripts for Android app testing, building, and automation. Provides semantic UI navigation, build automation, log monitoring, and emulator lifecycle management. Optimized for AI agents with minimal token output.

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 writing test fixtures for @copilotkit/aimock — mock LLM responses, tool call sequences, error injection, multi-turn agent loops, embeddings, structured output, sequential responses, or debugging fixture mismatches

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。

The Jobs-to-be-Done framework as applied product methodology. Job statements, struggling moments, hire and fire criteria, the difference between feature-thinking and job-thinking. Honest about where JTBD adds clarity (discovery, prioritization, positioning) and where it becomes performative ritual (job-statement workshops that do not drive decisions, persona-theater disguised as JTBD). Triggers on jobs-to-be-done, JTBD, job statements, struggling moments, hire criteria, fire criteria, switch triggers, functional emotional social jobs, outcome-driven innovation. Also triggers when a team is over-relying on feature-request lists or persona archetypes that do not drive product decisions, when a positioning conversation needs the framing JTBD provides, or when discovery is producing outputs that do not connect to product strategy.

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。

OKR design as actually shipped, not as conference-talk theory. Outcome statements that drive decisions, key results that measure the right thing, scoring discipline, mid-quarter recalibration, and the difference between sandbagged OKRs (always 100%) and aspirational OKRs (always 30%) and stretch OKRs (genuine ambition with quarterly accountability). Triggers on OKR design, OKR setting, key result design, OKR scoring, mid-quarter recalibration, OKR cascading, outcomes vs outputs, quarterly planning, goal setting. Also triggers when a team's OKRs are always hit and producing no learning, when OKRs are demoralizing because they were set as fantasy, or when the team uses OKR vocabulary but the practice has decayed.

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。

Walk the user through four directional axes (tone register, aesthetic philosophy, audience relationship, sensory ambition) and produce a structured aesthetic brief that downstream content, copy, design, and art-direction skills consume as required input. The aesthetic depth layer, distinct from `creative-brief` (operational kickoff: scope, audience, deliverables, constraints). Use when a project needs aesthetic coherence across many small decisions and the user has only a vague feeling, or when multiple downstream aesthetic-producing skills need a shared brief. Triggers on creative direction, aesthetic direction, set the aesthetic, define the visual direction, what's the vibe, what's the tone, the four axes. Does NOT fire for a general kickoff brief (use `creative-brief`), tactical single-piece work, already-documented direction, purely functional output, or locked production-stage work.

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。

A Yahoo Finance (yfinance) powered financial analysis tool. Get real-time quotes, generate technical indicator reports (RSI/MACD/Bollinger/VWAP/ATR), summarize fundamentals, and run a one-shot report that outputs a text summary.

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。

WeChat Official Account topic planning and content calendar management. Based on WeChat article search and trending analysis, generates differentiated topic recommendations and outputs structured content calendars. Activated when users mention "topic", "planning", "content calendar", "trending", or "what to write next week".

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。

Ultra-compressed communication mode (lite / full / ultra) that cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Use when the user requests "caveman mode", "less tokens", "be brief", or when output budget is tight.

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。

Validation-first design for Cavekit — every kit requirement must be automatically verifiable. Six-gate validation pipeline, phase gates, merge protocol, completion signals, acceptance criteria patterns. Use when designing acceptance criteria, wiring CI gates, or debugging why an agent is producing output that nobody can verify.

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。

Edit, validate, debug, publish, and inspect ReachAI Workflow drafts through the Workflow AI Coding REST API. Use when asked to create or modify a workflow graph, add/update/delete nodes or edges, validate GraphSpec, dry-run or debug-run a workflow, inspect trace/run output, check release readiness, publish a validated draft, or work on PAGE_ASSISTANT workflows from Cursor/Codex.

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Report-only QA — same browser-based testing as qa but documents bugs with screenshots and repro steps only, no code changes. Health score formula weighted across 8 categories. Outputs to .gstack/qa-reports/.

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。

YC Office Hours — product idea diagnostic before writing code. Two modes: Startup (6 forcing questions with rigorous pushback) and Builder (generative brainstorming). Outputs design doc. Includes landscape research, premise challenge, alternatives generation, visual wireframe sketching, and optional cross-model second opinion.

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Multi-AI second opinion via OpenAI Codex CLI. Three modes: Review (pass/fail gate), Challenge (adversarial edge-case finder), Consult (freeform with session continuity). Read-only with streaming output and thinking traces. Cross-model analysis when review has already run.

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Systematic root-cause debugging. Iron Law: no fixes without root cause investigation first. Four phases: Root Cause Investigation, Pattern Analysis (6 known patterns), Hypothesis Testing (3-strike rule), Implementation. Structured debug report output.

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。

Build a complete design system from scratch. Competitive research via web search and browse. SAFE/RISK breakdown of choices. Self-contained HTML preview page. Outputs DESIGN.md as project design source of 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。

Writes, refactors, and evaluates prompts for LLMs generating optimized templates, structured output schemas, evaluation rubrics, and test suites.

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。

Analyze prompts for clarity, structure, examples, and output reliability

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。

Review the agent's own recent outputs for quality and accuracy

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。