1.1万 件 ・ 関連度順
概要と使いどころ
Epistemic logic for multi-agent perceptual systems — Kripke models, vision sets, public announcement as coordination primitive, and satisfiability-as-reconfiguration applied to agents with limited observability. From Charrier, Ouchet, Schwarzentruber's "Big Brother Logic" demonstration paper (ENS Rennes / IRISA).
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。
Design an agent's handling of obligations, prohibitions, permissions, and conflicts among norms and goals. Use when an autonomous agent must decide which norms apply and what to do when they conflict. NOT for simple fixed policy checks, ordinary BDI commitment design, or organizational metaphor.
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。
Verifies build output integrity after code changes. Runs builds, validates artifact structure, checks for regressions in bundle size, asset references, and static export completeness. The last line of defense before a bad deploy ships.
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Discipline an AI agent needs to work an issue/task tracker (Jira, Linear, GitHub Issues) as the shared source of truth: pull the right next item instead of inventing work, search before creating to avoid duplicates, write actionable items with checkable acceptance criteria, keep status transitions honest, and link work to items via branches/PRs/commits so progress is legible. Use when an agent picks up tracker work, files a new issue, updates status, or closes an item. NOT for authoring the PR itself (use agent-pr-authoring), roadmap-level planning and prioritization (use legible-roadmap-with-sidequests), or the mechanics of multiple agents coordinating on the same codebase (use multi-agent-coordination).
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Author a pull request an AI coding agent can actually get merged: a scoped, coherent diff; a Summary and Test Plan backed by real evidence; correct triage of required-and-blocking CI gates versus external/advisory checks (e.g. a Cloudflare Pages preview build); draft-while-WIP discipline; named fixup commits for real review findings; and a clean landing through a merge queue without force-pushing or bypassing branch protection. Use when opening, updating, triaging red CI on, or landing an agent-authored GitHub PR. NOT for this repo's internal release ceremony, actor embodiments, or contributor mirror-sync mechanics (use port-daddy-internal-dev), tracking backlog/issue lifecycle across a board (use agent-issue-tracker-workflow), or deciding what to build next / sequencing a roadmap (use legible-roadmap-with-sidequests).
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。
Expert-level idiomatic Rust API design — the patterns that make illegal states unrepresentable and abstractions zero-cost. Type-state programming (PhantomData state machines), newtype + sealed + extension traits, typestate builders, RAII guards & Drop ordering, the interior-mutability decision tree (Cell/RefCell/Mutex/RwLock/Atomic/OnceLock), enum-driven state machines, error architecture (thiserror vs anyhow), dyn vs generic dispatch & object safety, the impl Trait / GAT / RPITIT toolbox, and Deref-for-smart-pointers (and its abuse). Use when designing a Rust library's public API, encoding invariants in the type system, choosing a dispatch or error strategy, or reviewing Rust for idiom. NOT for borrow-checker firefighting / toolchain / test-runner workflow (use rust-development-workflow), NOT for pd-console GPUI rendering/layout/panes (use gpui-rust-console), NOT for app packaging/notarization (use rust-app-distribution).
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。
Design low-friction UX, interaction patterns, and comeback loops for AI coding assistant apps, agent consoles, background coding agents, and Port Daddy swarm/operator surfaces. Use when creating flows like prompt-to-diff, context attach, plan/apply/review, checkpoint rollback, background-agent dashboards, visual proof, or multi-agent invocation. NOT for generic landing pages, static dashboards, or implementation-only changes without product flow.
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。
Monitor a Coval run's progress with live updates. Use when user wants to check run status or wait for completion.
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End-to-end Coval adversarial / red-team testing workflow. Builds one adversarial test set (12 core attack vectors plus legitimate controls, each with an expected-behavior checklist), creates a persistent "Adversarial User" persona and a Composite Evaluation metric that scores each scenario against its own expected behaviors, launches a multi-iteration run against the agent (voice or chat), polls for completion, builds a per-scenario pass/fail scorecard, and creates a saved report grouped by Test Case. Use when a user wants to follow the Adversarial & Red-Team Testing cookbook (https://docs.coval.dev/guides/adversarial-red-team-testing) without doing each step by hand. Triggers: "adversarial test set", "red team my agent", "jailbreak / prompt-injection testing", "test my agent against bad actors".
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。
Image optimization analysis for SEO and performance. Checks alt text, file sizes, formats, responsive images, lazy loading, CLS prevention, image SERP rankings (via DataForSEO), and image file optimization (WebP/AVIF conversion, IPTC/XMP metadata injection). Use when user says "image optimization", "alt text", "image SEO", "image size", "image audit", "optimize images", "image metadata", "image SERP", "convert to webp", or "image file optimize".
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。
SEO drift monitoring: capture baselines of SEO-critical elements, detect changes, and track regressions over time. Git for SEO: baseline, diff, and track changes to your on-page SEO. Use when user says "SEO drift", "baseline", "track changes", "did anything break", "SEO regression", "compare SEO", "before and after", "monitor SEO changes", or "deployment check".
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Content quality and E-E-A-T analysis with AI citation readiness assessment. Use when user says "content quality", "E-E-A-T", "content analysis", "readability check", "thin content", or "content audit".
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。
Live SEO data via DataForSEO MCP server: SERP analysis, keyword research (volume, difficulty, intent, trends), backlink profiles, on-page analysis, competitor and content analysis, business listings, AI visibility (LLM mention tracking), and domain analytics. Requires DataForSEO extension installed. Use when user says "dataforseo", "live SERP", "keyword volume", "backlink data", "AI visibility check", or "real search data".
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 standing order for local git state in every AI Matrx repo — zero worktrees, zero local branches, zero dirty files, zero open PRs, everything merged to origin/main, and no code ever lost. Use when you find a worktree, a local branch, a stale checkout, an unpushed commit, or a dirty tree in any repo under /Users/armanisadeghi/code, when asked to "clean up", "unify", "merge everything", or when you are tempted to create a worktree or branch. Works without any access to Arman.
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。
Doctrine for fixing TypeScript errors against generated types (database.types.ts, api-types.ts). Use when fixing tsc or type-check failures or a type-errors batch, writing supabase .rpc()/.from() calls or DB shape guards, errors mention Json/unknown/Database, or you are tempted to cast or suppress.
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。
Follow-up sweep for pending third-party provider access campaigns. Use when the recurring 30-minute Provider Access Launch dispatcher wakes, or for a manual status check of due email threads, developer portals, support cases, or review deadlines.
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Custom-entry fix for pickers with no way to add a choice (Select, Popover list, DropdownMenu). Use when building or touching any choice control (tier, category, tag, status, owner), `pnpm check:picker-add` names a file, running Pattern Patrol P13, or the user says 'no way to add my own' or 'why can't I type a new one'.
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Lifecycle for AI Matrx agent-aware UI surfaces. Use when creating a surface in features/surfaces/manifests/, or completing or repairing one that is partial, stubbed, unregistered, missing runtime context or context menus, or not agent-wired. NOT for certifying a surface (use surface-check).
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 agent.review_queue register for work Arman must see or test in the UI. Use at the end of any task that produced something reviewable, at the start of a task to check prior feedback, and when reviewing, claiming, routing, or repairing a queue row.
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End-of-task routine: health checks, fixes, then commit and push. Use when finishing a unit of work, or when the user says 'commit and push', 'ship it', 'get it ready', 'wrap up', or just 'do this' with no push instruction.
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。
One-time recovery when a shared checkout has drifted far from GitHub main: hundreds ahead/behind, stacked worktrees and PRs, a dirty tree nobody owns. Use when tempted to reset or force-push. NOT for the ordinary 30-minute release loop (operations/INTEGRATION_MAINTAINER.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。
The provision for a call site: the exhaustive menu of values that place in the code can realistically produce. Use before creating or fixing a mandate or agent that reasons about more than its own input, when deciding whether an agent can answer at all with what it is sent, or when its output 'looks right' but nobody checked it could be. NOT for building the agent (use create-agent).
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。
Early-user discovery and feedback trials. Use when reviewing unfamiliar AI Matrx accounts, classifying owner relationships, recommending trial plans, or running approved outreach and reply checks.
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Disclosing a surface's existing fixed AI jobs in the shell's top Agents menu. Use when a page, panel, overlay, or window already runs a mandate behind a button, assist, automatic action, or mode; when the agent-disclosure guard names a file; or during a surface check.
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。