调研、论文、教育、考证学习（4186 个）
Use this skill when the user asks about driver fatigue management — circadian rhythm impact on driving, recognizing fatigue, fatigue risk management programs (FRMS), night driving safety, microsleep recognition, drowsiness detection technology, and how HOS rules relate to actual fatigue (and why 11-hour driving is risky even when legal). Reference FMCSA Fatigue Management research.
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Use this skill when the user asks about driver ergonomics — back/neck/shoulder injury prevention, seat adjustment + lumbar support, entering and exiting cab safely, load handling techniques, vibration reduction, stretching protocols, and how ergonomics affects workers compensation costs in trucking. Reference OSHA + ATA ergonomics research.
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Use this skill when the user asks the economic + operational tradeoffs of broker-mediated freight vs direct shipper relationships — margin difference, capital + operational cost, sales effort, payment terms, relationship investment, when to pursue direct, and the hybrid model. Reference industry research on freight broker margins.
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Use this skill when the user asks about cargo securement requirements under 49 CFR 393 Subpart I — Working Load Limit (WLL), tiedown counts, tiedown types, commodity-specific securement rules (lumber, metal coils, paper rolls, concrete pipe, intermodal containers, vehicles, large boulders, dressed lumber, building materials), CVSA out-of-service criteria, and how to calculate aggregate WLL. Cite 49 CFR 393.100-136.
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Structured interview and observation techniques for extracting tacit knowledge from domain experts
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Apply practical DAG decomposition, transitive-edge reduction, and reachability indexing to dense dependency graphs. Use when low width and repeated queries justify preprocessing. NOT for cyclic graphs, one-off graph checks, or exact-minimum-chain requirements.
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An innate exploratory drive that guarantees no graph node remains permanently invisible to an agent population. After a warm-up period (step > 3), each agent fires a coverage scan with probability |unseen_nodes| / |all_nodes|. When triggered, the agent teleports directly to the globally unseen node with the highest belief uncertainty, works it, and returns control to the normal action-selection loop. Probability is self-annealing: it starts near 1.0 when almost everything is unseen and decays toward 0.0 as coverage saturates, requiring no manual schedule. The mechanism is "innate" (hard-coded into the agent step loop) as distinct from the "adaptive" EFE path, which requires local neighbors and learned precision weights. Together they form a two-layer exploration architecture: adaptive for locally-guided foraging, innate for topological completeness.
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Adversarial reviewer for The Federated Harbor whitepaper — the third paper in the Curiositech sequence after Anchor and Bonded Commons. Probes federation-specific threats: trust transitivity, cross-harbor token forgery, federated revocation under partition, cross-harbor Sybil, cross-domain settlement, equivocation, bond-pool draining, cold-start joining, federation-operator Sybil. Use during a versioned red-vs-white round; pairs with federated-harbor-whitehat. NOT for incident response, NOT for the Anchor or Bonded papers (use redteam-review).
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Analyze undirected cycle structure within a valid DAG using the source paper's orientation and contraction method. Use for cycle-basis analysis with explicit graph and reduction choices. NOT for directed feedback loops, workflow deadlocks, or runtime resilience claims.
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Learns from DAG execution history to improve future performance. Identifies successful patterns, detects anti-patterns, and provides recommendations. Activate on 'learn patterns', 'execution patterns', 'what worked', 'optimize based on history', 'pattern analysis'. NOT for failure analysis (use dag-failure-analyzer) or performance profiling (use dag-performance-profiler).
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Analyze hierarchical DAG-like systems by separating undirected substrate from ordering metadata, then classifying diamonds, mixers, shortcuts, and hidden cycle structure. Use for workflow architecture, citation or genealogy DAG comparison, and information-flow diagnosis. NOT for ordinary cycle detection in arbitrary graphs, one-node runtime debugging, or systems with no real ordering constraint.
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Conduct Critical Decision Method (CDM) interviews to elicit expert reasoning strategies (L3 knowledge) from practitioners about specific challenging past incidents. Use when capturing expertise for skill development, preserving knowledge before practitioner departure, building post-incident learning artifacts, or investigating decisions in complex sociotechnical systems. Outputs structured incident reconstructions with cues, decisions, alternatives considered, and counterfactual analysis suitable for distillation into skills or training material.
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Naturalistic causal reasoning for failures and disputed attribution. Use when postmortems or root-cause debates need reframing. NOT for causal inference, fault trees, or fully observed failures.
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Revise the Harbor Book so prose, drawings, and marginalia explain the same argument without unpublished development-document dependencies. Use for chapter additions, substantive rewrites, caption editing, visual exposition, and eliminating internal ADR citations.
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Expert legal research agent for finding and scraping expungement data state by state. Knows authoritative sources, URL patterns, Firecrawl configuration, and 2026 legal landscape.
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Use for insight, reframing, contradiction, impasse, and anomaly-driven problem solving when execution effort no longer helps. NOT for routine optimization, error correction, or well-specified tasks with known solution paths.
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Apply AlphaGo-style patterns: learned priors plus search, mixed evaluators, self-play, and asynchronous fast/slow loops. Use for intractable search and compute allocation. NOT for basic supervised learning, tractable optimization, or domains without search bottlenecks.
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Research AI coding assistant products, audiences, user stories, social proof, hacks, and unmet needs for apps like Cursor, Claude Code, Codex, Warp Code, Devin, Windsurf, GitHub Copilot, Cline, Aider, and homegrown agent stacks. Use when designing or positioning agentic developer tools, Port Daddy Agent Harbor, swarm consoles, background coding agents, or competitive/product research for AI software engineering. NOT for implementing the coding agent runtime, generic market research, or UX mockups without developer workflow evidence.
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Pipeline that turns a big system idea into briefs for an agent fleet. Use when Arman says 'let's plan out X', 'build or overhaul the X system', 'create the vision and plan for X', 'do the full discovery process', 'get this ready for a fleet', or 'do what we did for education', or when carrying forward a VISION, COMPETITIVE_INSIGHTS, roadmap, or briefs doc. NOT for one feature in a live system (use build-sub-feature).
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Working playbook preloaded into the researcher helper; the coach updates its Lessons after each round. Use only when acting as researcher or coaching it. NOT for general research tasks.
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Generates creative, research-backed domain name ideas and checks availability with competitor analysis, pattern recognition, and quality scoring. Use when brainstorming brandable domains for a product or project.
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実行中・実行済みのプログラムやジョブの状況を知りたいとき，自分が起動したものか無関係のものかを問わず調べて答える．「どうなってる？」「学習状況は？」「進捗見せて」など，実行そのものを頼んでいるわけではなく既存の何かの様子を尋ねられたときに使う．新しく実行を頼まれたときは /ops:exec を使う．
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ユーザーからの修正・指摘を受けた際の学習記録と自己改善ループ。ユーザーから「違う」「そうじゃない」「前にも言ったけど」といった修正を受けた時、同じミスを繰り返していると気づいた時、セッション開始時の教訓確認で使う。修正やフィードバックを受けたら必ずこのスキルを参照する。
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X上の技術知見・障害・運用事例・公式発表を調べる依頼に使う。ログイン済みXのネイティブ検索から一次情報と反証を確認する。
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