一键导入
capability-evolution
Use when a task needs controlled capability discovery and adoption across official plugins, local skills, and trusted GitHub projects.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Use when a task needs controlled capability discovery and adoption across official plugins, local skills, and trusted GitHub projects.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
Use when active work produces a memory-worthy signal. Direct-land explicit strong signal into ACTIVE.md or LEARNINGS.md when the destination is clear; use inbox only for unresolved inferred signal.
Use when a scheduled or manual Dream Loop pass should refresh ACTIVE.md, strengthen LEARNINGS.md, and drain unresolved inbox signal.
基于 SOC 职业分类
| name | capability-evolution |
| description | Use when a task needs controlled capability discovery and adoption across official plugins, local skills, and trusted GitHub projects. |
Use this skill during active work when the task may need a better capability than the ones already in hand.
It discovers, validates, and adopts capabilities. It does not promote memory by itself.
Classify before discovery:
repair: broken workflow, failed integration, or missing capabilityoptimize: better speed, quality, confidence, or repeatabilityinnovate: new capability or workflowexplore: external search after official and local choices are insufficientexplore is only for cases where official and local options fail.
Check in order and stop at the first sufficient fit:
Do not jump straight to GitHub search if a good official or local option already exists.
Capability discovery must leave evidence, not just a conclusion. For non-trivial decisions, show searched layers, skipped or blocked layers, selected and rejected candidates, and whether GitHub or external search was reached. See references/discovery-evidence.md for the full checklist.
Before adoption, check relevance, maintenance recency, source trust, and integration cost versus expected benefit. Report before or while adopting third-party GitHub capabilities or making material global setup changes.
capture-memoryACTIVE.md or LEARNINGS.md during active workcapture-memory for direct landing under the current AGENTS.md rulesWhen this skill influences a decision, show: intent, discovery path, searched/skipped/blocked layers, selected/rejected candidates, whether GitHub or third-party search was reached, and whether the result should be captured into Dream Loop memory.