「make」の検索結果

Write and harden reusable agent-loop specification documents for biomechanics, data science, and vailá coding work. Use when the user says `/preto-loop`, asks to write/create/forge/specify/document an agent loop, turn an iterative vailá task into an autonomous loop, make an overnight loop, or design a biomechanics, data-pipeline, markerless-tracking, testing, refactoring, or performance loop. Include external verification, scientific validity, GUI/CLI parity, reproducibility, memory, guardrails, and named terminal states. Do not use merely to repeat a fixed scheduled prompt, execute an existing loop, or create unrelated documents.

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Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.

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Always use this skill before claiming any work is done, fixed, passing, or complete — even if it seems obvious. Also use when receiving code review feedback from any source (human or automated), when finishing a task or major feature, before committing or creating a PR, or when about to express satisfaction with work. Covers three practices: receiving feedback with technical rigor (no performative agreement), triggering code review via /code-review command or cook/fix pipelines, and verification gates (run the command, read the output, then make the claim). Never skip — the cost of false completion claims is higher than the cost of verifying. References: code-review-reception.md, requesting-code-review.md, verification-before-completion.md.

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Authoring and managing Agentforce agent definitions using the declarative Agent Script DSL (.agent files) and associated metadata types, including the Agent Script language for the new Agentforce Builder (hybrid-reasoning -> logic vs | prompt instructions, @actions/@subagent/@variables references, subagents). Use when creating agents in source control, writing or debugging Agent Script, debugging agent metadata, or understanding the metadata lifecycle of GenAiPlugin/GenAiPlanner/BotVersion types. Triggers: 'how do I deploy an Agentforce agent using source control', 'convert an agent topic to a subagent', 'what metadata types make up an Agentforce agent', 'agent test run command failing in CI pipeline', 'GenAiPlugin vs GenAiPlanner metadata relationship', 'Agent Script logic vs prompt instructions'. NOT for Apex-based agent actions — use agentforce/custom-agent-actions-apex. NOT for clicking the agent together in the Builder UI — use agentforce/agentforce-agent-creation.

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Designing or reviewing Agentforce actions: Flow actions, Apex invocable actions, prompt-template actions, action naming, input and output contracts, confirmation requirements, and safe error behavior. Triggers: 'agent actions', 'build an agent that can look up an order', 'make the agent able to check order status', 'give the agent a capability', 'agent that can retrieve a record', 'flow action for agent', 'agent invocable action', 'action schema design'. NOT for writing the Apex class itself — use agentforce/custom-agent-actions-apex. NOT for the reason_code error envelope that stops an agent retry loop — use agentforce/agent-action-error-handling.

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Use when designing or configuring public pages on an Experience Cloud site — guest user profile setup, page-level access settings in Experience Builder, object/field visibility for unauthenticated visitors, and explicit sharing rules that expose data on public pages. Triggers: 'configure public pages Experience Cloud', 'guest user profile setup', 'unauthenticated site access', 'public community page visibility', 'make page visible without login'. NOT for authenticated user features (use admin/experience-cloud-member-management). NOT for security hardening or remediation of guest user exposure (use security/guest-user-security). Also covers the deployable shape: pageAccess on the route file, the guest Profile's objectPermissions and fieldPermissions, sharingGuestRules, siteGuestRecordDefaultOwner on CustomSite, and the Network guest flags.

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Prevents overengineering when designing, implementing, refactoring, or reviewing software. Use when the user asks to implement a feature, add an abstraction, refactor code, review a design, simplify existing code, or make an architectural decision. Also triggers when the user asks if code is too complex, whether to abstract something, or how to structure something. Do not use for deployment, infrastructure configuration, or debugging runtime errors unrelated to code structure.

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Map a codebase into feature-grouped flowcharts, identify duplicated concerns across features, and propose a unified architecture. Use when asked to "find the ideal path," unify duplicated systems, or audit architecture before a refactor. Emits a proposed unified flowchart plus per-system /make-plan 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。

AI No-Code Automation Expert — Zapier, Make, n8n, workflow design, trigger/action, process automation สำหรับทุก business

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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.

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Configure and operate the Claude Code harness for large codebases. Builds CLAUDE.md hierarchies, scoped test/lint commands, file exclusions, codebase maps, hooks, skills, subagent strategies, and LSP/MCP wiring. Use when setting up Claude Code for a new repo, auditing an existing configuration, onboarding a team, or scaling from single-developer to org-wide deployment. Triggers on "set up Claude Code for this repo", "optimize my Claude Code config", "audit my CLAUDE.md", "make this codebase navigable", "configure hooks/skills/plugins".

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Household assistant for a whole family. Runs a morning brief, plans meals and builds grocery lists (hunting the best prices), looks ahead at the week's logistics, stays on top of the kids' school, watches prices on things the family wants, and helps book appointments and reservations. Use it for anything that keeps the family's day or week running. Trigger even on implicit asks - "what's on today", "what do the kids have this week", "what should we make for dinner", "add milk to the list", "when's the dentist", "did anything come from school", "remind me about the permission slip", "watch this jacket and tell me if it drops", "book us a table Friday".

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。

Saves learning notes from the current conversation. Classic mode makes concise notes, Mastery mode keeps detailed training 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。

Generate and edit images with Dreamfield's OpenAI-compatible gpt-image-2 image API. Use when the user asks Codex to create, test, or save an image from a text description, make wallpaper or illustration assets, perform image-to-image generation from reference images or clipboard images, use masks/inpainting, verify Dreamfield image generation, or troubleshoot image-generation responses such as empty data, b64_json, URL output, quota errors, or content policy errors.

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Aggregate friction log files across a time period to identify recurring patterns, classify each cluster by intervention type, produce a prioritized action plan with success criteria, and calculate convergence metrics. Complements `skmtc-retro` (which captures per-session signal) by acting as the system's actuator: turning accumulated observations into decisions. The primary output is a review document that makes the "is it getting better?" question answerable. Use this skill when the user asks to "review retros", "review friction", "run a retro review", "what's the pattern across sessions", "what should we fix next", or on a periodic cadence (monthly, pre-release). Also run after a cluster of sessions on the same feature area to surface systemic issues before they compound. Distinct from `skmtc-retro` — that skill captures per-session observations; this skill synthesizes them into decisions. Do not run this skill as a substitute for a per-session retro.

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Understand what SKMTC is, how its engine works, and the architectural invariants — for agents building or extending infrastructure *around* SKMTC rather than authoring generators or running the CLI. Covers the three-phase pipeline, the host/Worker boundary, cross-generator coordination, the manifest, the attribution / gen-maps (provenance) subsystem, the package graph, the dependency substrate, and the design decisions that make SKMTC behave unlike a typical codegen tool. Use this skill when the user asks "what is SKMTC", "how does the SKMTC engine work", "explain the SKMTC architecture", or is building platform infrastructure around SKMTC — a hosted generate API, a schema or generator registry, tracing or provenance tooling, a web app or SaaS that wraps the engine, or platform-level CI integration. This skill is the system mental model. It does NOT cover authoring generators (→ skmtc-generator), running CLI commands (→ skmtc-cli), or diagnosing broken runs (→ skmtc-debug).

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。

Write, restructure, or review documentation — tutorials, how-to guides, reference pages, concept/explanation docs, API references, READMEs, changelogs, release notes, and troubleshooting guides. Distills documentation craft from Mintlify's guides (compiled from technical writers at Stripe, GitHub, Amplitude, and Anaconda), the Diátaxis framework (including the compass and per-type voice), the Google and Microsoft style guides, Every Page Is Page One, Write the Docs, and Docs for Developers: audience analysis, content-type selection, style and word-level rules, procedure writing, structure for humans and AI agents, code-example standards, page templates (templates.md), mechanical enforcement and llms.txt (mechanics.md), maintenance, and success metrics. Use this skill when the user asks to "write docs", "document this feature", "improve this page", "review these docs", "write a tutorial / how-to / reference page", "structure the docs", "write API documentation", "write a README / changelog", or when authoring any file under a `docs/` tree. For SKMTC docs specifically, this skill governs the *craft* (what makes the page good); the content split between skills, `llms.md`, and the docs tree is governed by `docs/skills/README.md`. Distinct from `skmtc-retro` (captures observations about work) and the `skmtc-*` operational skills (guide doing the work) — this skill guides writing *about* the work for readers.

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Render the GAME-DESIGN document (the GDD) into a human-readable form — read-only Markdown chapters under docs/design/ (index, systems, flows, content, economy, glossary), with facts resolved inline from GD-IDS.yaml and drafts flagged 🚧. Optional --web also renders an HTML site from the unikit-docs template (falls back to Markdown-only if the template is absent). Use to export or publish the design for people to read, e.g. "render the GDD", "export the game design to docs", "generate readable design docs", "publish the GDD", "make a design doc site". Read-only — it never edits the GDD or registry, only renders it. This renders the game DESIGN — for the project's CODE documentation (README, docs/*, modules, architecture) use /unikit-docs.

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Customize how a built-in unikit skill behaves in this specific project by writing workflow overrides into its skill-context file. These are per-skill workflow rules (e.g. "/unikit-review should also flag TODO comments", "/unikit-implement should run tests after each task"), not coding conventions. Use when the user wants to change, customize, or override how a particular unikit skill works in this project — "customize the review skill", "make /unikit-fix always add logging here", "the implement skill should do X differently", "add a skill rule for /unikit-commit". Use "validate" to find stale overrides against updated base skills. For a general coding convention (not tied to one skill) use /unikit-rules; to derive rules from past mistakes use /unikit-evolve.

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。

Record a finding about the configured engine MCP server into .unikit/MCP-RECHECK-NOTES.md — the project's log of what has to be re-checked here. Use right after a call reported success while changing nothing, ate an argument, or validated a broken state, e.g. "write this down", "record this MCP finding", "the server lied — note it", "add a recheck note", "trap this". Takes three forms of input: the finding in one line, a path to a plan file (harvests the "## MCP Findings" table of that plan and nothing else), or nothing at all — then it takes findings already in the session first, and offers to scan the tables of plans touched since the last audit. The table only, never the plan body. Writes in the one allowed genre — a check to perform; never a lifted gate, never a named workaround, never a claim about what the server can or cannot do. Makes zero MCP calls and needs no editor. To replay, retire, or upstream existing notes use /unikit-mcp-audit instead.

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。

Cuts a project release. Discovers the project's release procedure (Makefile target, RELEASING.md, CI workflow, etc.) and offers to capture it durably if missing. Always invokes /review-release as preflight, proposes a version bump from CHANGELOG, then presents an exact command plan for operator confirmation before executing step-by-step. Halts on first failure rather than attempting rollback.

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AI media generation CLI tool using Google's Imagen 4, Veo 3.1, and Gemini TTS. Use when the user wants to (1) generate images from text prompts, (2) edit existing images with AI, (3) explain image contents, (4) generate videos from text or images, (5) create narration/voice audio with character settings. Triggers on requests like "generate an image of...", "create a video...", "make a voice that says...", "edit this image to...", "describe this image".

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。

Audit and improve web accessibility following WCAG 2.2 guidelines. Use when asked to "improve accessibility", "a11y audit", "WCAG compliance", "screen reader support", "keyboard navigation", or "make accessible".

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Use when the user asks to make something faster, try many variants, run recursive optimization, benchmark latency/throughput/cost, or choose the best implementation by repeated measured tests.

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。