一键导入
double-diamond-feature
Auto-discoverable wrapper for `.hforge/library/skills/double-diamond-feature/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/double-diamond-feature/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 | double-diamond-feature |
| description | Auto-discoverable wrapper for `.hforge/library/skills/double-diamond-feature/SKILL.md`. |
bug-investigation.hforge/library/skills/double-diamond-feature/SKILL.md.hforge/generated/agent-command-catalog.json.hforge/runtime/repo/repo-map.json.hforge/runtime/repo/recommendations.json.hforge/runtime/tasks/<taskId>/ when task artifacts existUse the canonical skill under .hforge/library/skills/ for execution. Treat this wrapper as a discovery entrypoint only. Keep the workflow lightweight unless risk or ambiguity requires Standard or Deep mode.
Auto-discoverable wrapper for `.hforge/library/skills/bug-investigation/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.
Auto-discoverable wrapper for the Harness Forge recursive-investigate workflow. Use when a task is ambiguous, cross-module, investigation-heavy, or likely to benefit from Typed RLM, bounded subcalls, and durable recursive artifacts.