「fact」の検索結果

Generate an actionable, dependency-ordered tasks.md for the feature based on available design artifacts.

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。

Convert existing tasks into actionable, dependency-ordered GitHub issues for the feature based on available design artifacts.

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。

Stress-tests a fuzzy or vague feature idea before any PRD, spec, or ticket is written. TRIGGER when: the user has a fuzzy feature idea — one or two paragraphs, vague on users / scope / success — and wants to harden it, or says "grill / stress-test / pressure-test this idea." DO NOT TRIGGER when: the idea is already turned into a spec or PRD; bug fixes or refactors; the idea is hardened and you are ready to write the PRD → creating-prd.

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。

Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.

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。

PCBWay PCB fabrication and assembly — turnkey/consigned assembly, design rules, ordering workflow. Alternative to JLCPCB for manufacturing. Use with KiCad. Use this skill when the user mentions PCBWay, needs turnkey assembly (PCBWay sources parts by MPN), has parts not available on LCSC, needs assembled boards with non-LCSC components, wants to compare PCBWay vs JLCPCB, or needs assembly with parts sourced globally rather than from LCSC only. For gerber/CPL export, stencil ordering, and BOM management, see the `bom` skill.

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Manage an electronics bill of materials across distributors and fabricators: part selection, stock, pricing, alternates, ordering, KiCad properties, and BOM/CPL export. Use for distributor-neutral sourcing, cost comparison, order preparation, or requests such as "what parts do I need" and "export for JLCPCB". Do not take over schematic analysis or a complete new-design workflow unless the requested task is specifically its sourcing/manufacturing stage.

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。

Create, import, analyze, resume, or revise an end-to-end Circuit Weaver electronic design from requirements through validated functional KiCad schematics, placement review, and a truthful manufacturing handoff. Use for new designs and for existing KiCad/PCB/Gerber projects that need durable state. Use kicad for one-off file inspection, bom for standalone sourcing, and design-wizard only when the user explicitly requests the slower questionnaire.

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 Circuit Weaver's exhaustive placement proposal and apply approved SVG coordinates to a real electrically annotated KiCad PCB. Use after schematic generation for placement optimization, official-reference review, interactive SVG editing, strict reference reconciliation, and PCB placement handoff. Do not treat review artifacts as fabrication data.

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Orchestrate work as a cyclic directed graph of subagent-executed nodes with transition criteria on edges, budgeted cycles, and per-node gates (runtime verification, metric, or artifact). Use when the user says "workgraph", "run this as a graph", "graph this work", or when a goal has parallel branches, feedback loops, or mixed gate types that a linear loop cannot express. Every node is sized to a 64k context budget, so small goals run as a two-node do/verify graph and large goals scale out without caps. For clock-driven or metric-driven single loops, timeboxed-iterating and autoresearch remain lighter.

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。

Create custom modules for [Harbor Boost](https://github.com/av/harbor/tree/main/boost), an optimizing LLM proxy. Use when building Python modules that intercept/transform LLM chat completions—reasoning chains, prompt injection, structured outputs, artifacts, or custom workflows. Triggers on requests to create Boost modules, extend LLM behavior via proxy, or implement chat completion middleware.

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Run work as an explicit event-driven state machine executed by subagents. The orchestrator is the runtime from the canonical loop — `state, effects = init(machine); execute(effects); while state is active: event = nextEvent(); state, effects = transition(machine, state, event); execute(effects); return state.output`. All routing judgment is authored ONCE, at plan time, into a machine file (states, event alphabet, transition table, budgets, final states); at runtime the orchestrator does pure table lookups and dispatches effects — it never decides, never authors, never ingests artifacts. Subagent/sync protocol is the timeboxed-iterating one: role prompts scaffolded once to disk and dispatched BY PATH, an initialiser preamble every subagent reads first, a self-populating cheatsheet, per-unit files, tiny structured returns, independent measurement gate. Use when the user says "workmachine", "run this as a state machine", "state-machine this", or when a goal has a small number of clearly named phases with explicit outcomes (built / passed / failed / blocked) and you want the routing to be auditable rather than judged on the fly. For clock-driven loops use timeboxed-iterating; for wide graphs with judged edge criteria use workgraph.

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How to use the coding agents installed on this machine (claude, codex, droid, grok, vktr, hermes, opencode, copilot, pi) as plain sub-agents in orchestrated workflows: one headless invocation, one prompt in, one result out. Deliberately ignores each CLI's own orchestration features (droid --mission, codex multi_agent, hermes delegation/moa/kanban, grok --agents, opencode personas). The orchestrator is whatever session is running the skill; the CLIs are interchangeable workers. Use when the user asks "which agent should run this", "fan out workers", "run X headless", or when a lifeos skill (overnight, timeboxed-iterating, workgraph, gauntlet, bughunt, dark-factory) needs to launch an agent CLI, or when a worker needs company context it should ask Viktor for (vktr).

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 a finished piece from human-written fragments via an orchestrated two-loop pipeline - an assembly loop (assembler + cold reviewer) that sequences the fragments into a draft, then a polish loop (polisher + cold reviewer), then frequency analysis and a catalog-deslop pass with a regression gate. Two modes with opposite fidelity contracts - stitch mode preserves the author's exact wording, narrative mode preserves every idea but may rewrite freely. Use when the user says "mosaic", "assemble my fragments", "stitch these notes into a post", or provides a fragments file to turn into a finished piece. For writing from a topic with research, use article-factory; for prose from scratch, use the prose 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。

Run a task iteratively over a user-specified duration by dispatching subagents. The orchestrator stays strictly linear and time-checked, but each iteration fans out MULTIPLE subagents in parallel over independent units (and those subagents may fan out further). Shared state — a compact progress digest and a growing environment cheatsheet — lives on disk and is passed to every subagent BY REFERENCE, killing the per-subagent rediscovery tax. Every subagent first reads an initialiser preamble that points it at that shared state and makes it write findings back, so the cheatsheet populates itself; role prompts are produced ONCE on the filesystem by a single scaffold command and dispatched by path, never re-typed per dispatch. Subagents persist their results to disk and return only a tiny status, so the orchestrator's context stays small and lasts. The orchestrator classifies the goal as FINITE or OPEN-ENDED: finite lists may finish early; open-ended goals use the full duration, never idle, never manufacture busywork. Use when the user gives a task and a duration and wants it ground out iteratively by subagents over that time.

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。

Catalog-then-fix slop removal on an existing prose draft. Parallel catalog subagents inventory four slop categories (theatrics, overwrought register, corrective antithesis, dramatic short sentences), fix subagents repair only what a catalog names, mechanical lint + frequency analysis bracket the run, and a regression gate (lint delta, word count, cold meaning check) decides whether the result ships. Use when the user says "deslop this draft", "catalog deslop", "strip the AI patterns from this file", or as the final stage of the article-factory and mosaic-writing skills. For writing or redrafting prose from scratch, use the prose skill instead - this skill only repairs an existing draft in place.

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。

Firmware development for the 30-pin ESP32-WROOM-32 development board — the DOIT ESP32 DevKit V1 / ESP32 CH340 Type-C / NodeMCU-ESP32 30-pin form factor, 15 pins per side, CH340G or CP2102 USB-UART bridge, AMS1117 LDO, user LED on GPIO2. Use when working on a 30-pin ESP32 devkit (ESP32-D0WDQ6 / ESP32-D0WD-V3, ESP-WROOM-32 module): project setup, platformio.ini and sdkconfig for ESP-IDF or Arduino, pin mapping and which GPIOs are safe, strapping pins, ADC1 vs ADC2 with Wi-Fi, SPI speed and IO_MUX pins, I2C, deep sleep and RTC wake pins, flashing over the CH340 bridge, BOOT/EN recovery, brownouts, or debugging why something on the board does not 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。

Apply or audit the approved Quiet Signal core visual language when the user explicitly asks for Quiet Signal styling on a defined website, interface, poster, social graphic, report, presentation, or other design artifact. This skill supplies visual identity and rule checks; it does not plan content, invent platform requirements, or run a production pipeline.

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。

Compiles binary analysis findings into structured reports — correlates facts from triage, static, and dynamic phases, validates hypotheses against evidence, and produces traceable documentation. Use when ready to summarize findings, generate a report, document what a binary does, or prepare results for handoff or archival.

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。

Crystal and gemstone expert covering traditional associations, chakra systems, and metaphysical properties alongside geological facts

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Advanced matrix theory expert covering spectral theory, matrix factorizations, and numerical linear algebra

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。

Set up mobile CI/CD pipelines for Flutter, React Native, or native iOS/Android — GitHub Actions workflows for testing, code signing, TestFlight/Play Store distribution, build number management, Fastlane integration, and artifact retention

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Generate Excalidraw architecture diagrams (.excalidraw JSON files) from your codebase. Triggers: you need whiteboard-style sketches that read as a thinking artifact rather than a polished spec — ideal for design.

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Conduct a complete feature workflow in one skill — brainstorm, plan, TDD implementation, self-review, delivery summary — with hard gates between stages: no stage starts until the prior stage's artifact exists on disk (brainstorm note, plan doc, green tests per step)..

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Audit manufacturing predictive maintenance systems for OPC-UA/MQTT sensor data pipelines, time-series storage retention, ML model lifecycle (training-serving skew, drift detection, retraining triggers), MTBF/MTTF/MTTR reliability calculations, Weibull survival analysis.

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。