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AI 与智能体 Skill

「AI 与智能体」分类下共 187 个 Skill,按所在仓库的 GitHub star 排序。分类为自动归类,仅供参考。

agent-harness
alirezarezvani/claude-skills28k

agent-harness

暂无描述

agent-memory
alirezarezvani/claude-skills28k

agent-memory

暂无描述

agent-protocol
alirezarezvani/claude-skills28k

agent-protocol

暂无描述

agenthub
alirezarezvani/claude-skills28k

agenthub

暂无描述

aims-audit
alirezarezvani/claude-skills28k

aims-audit

暂无描述

andreessen
alirezarezvani/claude-skills28k

andreessen

暂无描述

hivemind
alirezarezvani/claude-skills28k

hivemind

Orchestrate free opencode workers from Claude Code to cut token costs. Use when delegating grunt work to a single worker or a parallel swarm (scout/coder/tester) with worktree isolation, benchmarking against opencode, or when the user says "spawn a worker", "swarm", "delegate to opencode", or "/oc".

loop-library
alirezarezvani/claude-skills28k

loop-library

Discover, find, compare, audit, repair, adapt, and design repeatable AI-agent loops with explicit triggers, actions, verification, stopping conditions, guardrails, and handoffs. Use when a user asks to analyze a codebase for potential loops, mine coding-thread history for work done more than once, turn repeated engineering work into a loop, find or recommend a published loop, create a recurring agent workflow or automation cadence, turn an outcome into a bounded copy-ready loop, or review an existing loop for weak checks, unsafe authority, unbounded repetition, stale state, or unclear stopping behavior.

strict-api
alirezarezvani/claude-skills28k

strict-api

Use when the user says 'no hallucinations', 'verify APIs', 'reality check', or 'don't invent functions'. Prevents the agent from calling methods, imports, or variables that do not provably exist in the user's installed version.

brainstorm-okrs
phuryn/pm-skills27k

brainstorm-okrs

Brainstorm team-level OKRs aligned with company objectives — qualitative objectives with measurable key results. Use when setting quarterly OKRs, aligning team goals with company strategy, drafting objectives, or learning how to write effective OKRs.

cohort-analysis
phuryn/pm-skills27k

cohort-analysis

Perform cohort analysis on user engagement data — retention curves, feature adoption trends, and segment-level insights. Use when analyzing user retention by cohort, studying feature adoption over time, investigating churn patterns, or identifying engagement trends.

intended-vs-implemented
phuryn/pm-skills27k

intended-vs-implemented

The method for finding the gap between what a system is supposed to do and what the code actually does — the class of bug generic scanners miss because they have no model of intent. Defines what counts as documented intent, what counts as implementation evidence, which mismatches matter, and how to avoid hand-wavy findings. Use when auditing AI-built code, reviewing access control against documented permissions, or checking whether a codebase matches its own documentation.