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complex-task-protocol
Auto-discoverable wrapper for `.hforge/library/skills/complex-task-protocol/SKILL.md`.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Auto-discoverable wrapper for `.hforge/library/skills/complex-task-protocol/SKILL.md`.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | complex-task-protocol |
| description | Auto-discoverable wrapper for `.hforge/library/skills/complex-task-protocol/SKILL.md`. |
.hforge/library/skills/complex-task-protocol/SKILL.md.hforge/runtime/agent-brief.md.hforge/generated/agent-command-catalog.json.hforge/runtime/recursive/language-capabilities.jsonUse the canonical skill under .hforge/library/skills/ for execution. Treat this wrapper as a discovery entrypoint only. Activate the protocol by task complexity thresholds rather than by requiring a slash command.
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.
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.