/install agent-pattern-mining
Agent Pattern Mining
Mine reusable agent patterns from real codebases and turn them into concrete upgrades instead of vague inspiration.
Workflow
-
Scope the source repo and the upgrade target.
- Clarify whether the goal is analysis only, a new skill, workflow changes, implementation work, or all of them.
- Prefer targeted reading over exhaustive reading.
-
Map the architecture quickly.
- Inspect entrypoints, command/tool registries, memory/context code, planning/tasking, permissions, plugin/extensibility, remote/background execution, and observability.
- Ignore vendor-specific infrastructure unless it carries a transferable pattern.
-
Build a transfer matrix.
- For each promising pattern, capture:
- source feature
- user benefit
- portability/risk
- nearest OpenClaw equivalent
- concrete local action
- For each promising pattern, capture:
-
Classify findings.
- Adopt now: can be captured as a skill, workspace rule, reference note, or small implementation.
- Prototype later: good idea, but needs tool/runtime changes.
- Do not copy: tightly vendor-locked, high-complexity, or low-value for the local setup.
-
Apply improvements in this order.
- Create or improve a skill when the pattern is reusable.
- Update
AGENTS.mdfor stable workflow changes. - Update
TOOLS.mdfor environment-specific operational notes. - Update daily memory or
MEMORY.mdfor durable lessons. - Propose config/runtime changes only when the user explicitly asks for them.
-
Report the result concretely.
- Summarize what the source system does well.
- List what was adopted locally.
- List what still requires deeper implementation work.
- Name the exact files created or changed.
What to Look For
Prioritize patterns that reduce operator burden or improve agent reliability:
- explicit planning modes
- visible task tracking
- context budget awareness
- selective memory recall
- permission boundaries and review gates
- multi-agent orchestration
- deferred tool discovery
- plugin/skill hot reload
- change/diff observability
- session recovery and history search
Deprioritize patterns that are mostly infrastructure-specific:
- first-party SaaS integrations
- internal telemetry wiring
- organization-specific policy systems
- vendor-only remote services without a local analogue
Output Shape
Use this structure when delivering results:
- Architecture sweep — the subsystems reviewed
- Best transferable ideas — ranked by impact
- Concrete local upgrades — skill/doc/workflow changes already made
- Gaps left open — good ideas not yet implemented
- Files changed — exact paths
References
- Read
references/claude-code-patterns.mdwhen the source is Claude Code or when the user wants proven patterns from agentic coding CLIs.
Guardrails
- Do not claim an upgrade happened unless a file, workflow, or configuration actually changed.
- Prefer lean skills: keep
SKILL.mdprocedural and move detailed analysis toreferences/. - When the repo is large, read representative files first, then deepen only where the pattern is promising.
- If the user asks for self-upgrade, translate findings into persistent artifacts, not just commentary.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install agent-pattern-mining - 安装完成后,直接呼叫该 Skill 的名称或使用
/agent-pattern-mining触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Agent Pattern Mining 是什么?
Study another AI agent, coding CLI, or assistant codebase and extract transferable patterns into concrete local improvements. Use when asked to learn from Cl... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 10 次。
如何安装 Agent Pattern Mining?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install agent-pattern-mining」即可一键安装,无需额外配置。
Agent Pattern Mining 是免费的吗?
是的,Agent Pattern Mining 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Agent Pattern Mining 支持哪些平台?
Agent Pattern Mining 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Agent Pattern Mining?
由 cndbot(@cndbot)开发并维护,当前版本 v1.0.0。