一键导入
recursive-structured-analysis
Auto-discoverable wrapper for `.hforge/library/skills/recursive-structured-analysis/SKILL.md`.
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
Auto-discoverable wrapper for `.hforge/library/skills/recursive-structured-analysis/SKILL.md`.
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。
基于 SOC 职业分类
| name | recursive-structured-analysis |
| description | Auto-discoverable wrapper for `.hforge/library/skills/recursive-structured-analysis/SKILL.md`. |
.hforge/library/skills/recursive-structured-analysis/SKILL.md.hforge/runtime/recursive/language-capabilities.json.hforge/runtime/recursive/sessions/<sessionId>/execution-policy.json.hforge/generated/agent-command-catalog.jsonUse the canonical skill under .hforge/library/skills/ for execution. Treat
this wrapper as a discovery entrypoint only, and check the recursive language
capability map before describing recursive structured analysis as available
for a specific language or execution mode.
Auto-discoverable wrapper for `.hforge/library/skills/bug-investigation/SKILL.md`.
Auto-discoverable wrapper for `.hforge/library/skills/double-diamond-feature/SKILL.md`.
Use for defects, regressions, outages, flaky tests, and unexpected behavior. Guides the agent through triage, containment, reproduction, hypotheses, root-cause evidence, fix verification, and recurrence prevention. Do not use as the primary workflow for new features; use double-diamond-feature instead.
Use for meaningful feature development before coding. Guides the agent through Discover, Define, Develop, and Deliver with evidence, options, validation, and rollback notes. Do not use for bugs, regressions, outages, or flaky tests; use bug-investigation instead.
Auto-discoverable wrapper for `.hforge/library/skills/complex-task-protocol/SKILL.md`.
Automatic operating protocol for complex agent tasks. Use when work is multi-step, risky, cross-module, orchestration-heavy, or likely to benefit from bounded sidecar help, verification discipline, recovery checkpoints, and durable learning capture.