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Found 185 Skills
Set up and improve harness engineering (AGENTS.md, docs/, lint rules, eval systems, project-level prompt engineering) for AI-agent-friendly codebases. Triggers on: new/empty project setup for AI agents, AGENTS.md or CLAUDE.md creation, harness engineering questions, making agents work better on a codebase. ALSO triggers when users are frustrated or complaining about agent quality — e.g. 'the agent keeps ignoring conventions', 'it never follows instructions', 'why does it keep doing X', 'the agent is broken' — because poor agent output almost always signals harness gaps, not model problems. Covers: context engineering, architectural constraints, multi-agent coordination, evaluation, long-running agent harness, and diagnosis of agent quality issues.
Guides property and casualty (P&C) insurance—commercial and personal lines, major LOBs (property, GL, workers comp, commercial auto, umbrella, specialty), underwriting and risk selection, policy triggers (occurrence vs claims-made), limits and exclusions, claims (FNOL, reserving, litigation), reinsurance and catastrophe, distribution (agents, brokers, MGAs), metrics (loss ratio, combined ratio, cat load), and state DOI/rate filing overview—not legal advice. Use for P&C insurance, property and casualty, commercial lines, workers comp, general liability, combined ratio, loss ratio, underwriting, claims-made, occurrence policy, reinsurance, catastrophe, MGA, rate filing, or FNOL—not actuarial modeling (actuary), life/health depth, legal interpretation (commercial-counsel), or GRC controls without insurance context (compliance-engineer).
Identify risky assumptions for a feature idea in an existing product across Value, Usability, Viability, and Feasibility. Uses multi-perspective devil's advocate thinking. Use when stress-testing a feature idea, doing risk assessment, or preparing for assumption mapping.
Brainstorm feature ideas for a new product in initial discovery from PM, Designer, and Engineer perspectives. Use when starting product discovery for a new product, exploring features for a startup idea, or doing initial ideation.
Fleet orchestration for distributed coding agents across Azure VMs. Invoked as `/fleet <command>`. Covers all fleet operations: status, scout, advance, adopt, watch, snapshot, dry-run, start, add-task, queue, auth, dashboard, tui, and more. Use when: user mentions fleet, agents, VMs, sessions, or asks "what are my agents doing".
Inspect deal health, map stakeholders, identify risks, and recommend next actions. Use when reviewing a deal, assessing deal health, doing a MEDDPICC assessment, mapping stakeholders, analyzing deal risk, prepping for a deal review, inspecting pipeline deals, or evaluating champion strength. Do NOT use for portfolio-level pipeline management (use /sales-pipeline), revenue forecasting (use /sales-forecast), or reviewing a specific sales call (use /sales-call-review).
Token-efficient persistent memory system for Claude Code that extends your session limits by 3-5x. Layered architecture with progressive loading, compact encoding, branch-aware context, smart compression, session diffing, conflict detection, session continuation protocol, and recovery mode. Activates at session start (if MEMORY.md exists), on "remember this", "pick up where we left off", "what were we doing", "wrap up", "save progress", "don't forget", "switch context", "hand off", "memory health", "save state", "continue where I left off", "context budget", "how much context left", or any session start on a project with existing memory files. This skill solves two problems at once: Claude forgetting everything between sessions, AND sessions hitting context limits too fast. It replaces thousands of wasted re-explanation tokens with a compact, structured memory load that gives Claude full project context in under 2,000 tokens.
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or iterate on skill quality. Triggers: "create a skill", "make a new skill", "build a skill for", "write a skill that", "skill for doing X", "I want a skill to", "new skill", "design a skill", "scaffold a skill", "improve this skill", "optimize this skill", "this skill isn't working well", "evaluate this skill", "score this skill", "how good is this skill", "run evals on", "benchmark this skill", "test this skill's quality", "skill quality", "skill performance". Also triggers when a user describes a repeatable workflow they want to automate, says "I keep doing X manually", "can you remember how to do X", or "turn this into a skill".
Guides managers out of the bottleneck role — provides the Team Rep pattern, Epic Ownership model, Task-Relevant Maturity framework, kingdom ownership, and three-layer assignment strategy. Use when the user wants to delegate work or says "I'm doing everything," "team isn't taking ownership," "I can't let go," "team rep," "project ownership," "I'm the go-to person," "bus factor," "I work weekends," "how do I delegate," or "engineers don't take initiative." Do NOT use for managing a specific underperformer (use performance-reviews) or deciding what work to prioritize (use roadmap-planning).
Helps EMs assess their own effectiveness, avoid common traps, navigate bad days, and handle recurring tensions in their own mindset and behavior. Use when the user says "I feel stuck," "am I doing this right," "personal development," "EM effectiveness," "blind spots," "bad days," "sanity check on my behavior," "the same problem keeps coming back," "made a mistake with someone," or "my team isn't motivated." Do NOT use when the issue is about the user's relationship with their own manager (use managing-up) or giving specific feedback to someone (use feedback).
This skill should be used when the user says phrases like "record a topic", "new topic", "how is this topic", "I have an idea", "help me note this down", or shares a rough content idea that needs evaluation and recording. Even if the user casually mentions a content idea, actively trigger the evaluation process without waiting for the user to explicitly say "record". First, use the five-dimensional logic of dbs-content to diagnose whether the topic is worth doing. Only record it if it is worth doing, and recommend 3-5 similar topics by drawing inferences. Do not trigger: Deepen the topic to generate an outline (use li-topic), directly write scripts (use li-writer), or AI polish or beautify the topic title. Use when the user wants to "record a topic", "log a topic idea", "is this topic worth doing", or shares a rough contentclaise Du.弹应用样子Pr广解除禁 \ 诊断和记录.
Explanations of common asynchronous patterns used in tursodb. Involves IOResult, state machines, re-entrancy pitfalls, CompletionGroup. Always use these patterns in `core` when doing anything IO