plan-validate by closedloop-ai/claude-plugins
npx skills add https://github.com/closedloop-ai/claude-plugins --skill plan-validate确定性的 plan.json 验证,替代 plan-validator Sonnet 代理进行所有结构检查。语义一致性检查(存储/查询对齐、任务/架构矛盾)仍需要 LLM 代理,应在需要时单独运行。
在每个计划验证点代替启动 @code:plan-validator 来激活此技能。编排器应仅在计划创建或修改阶段之后,为纯语义检查启动完整的 plan-validator 代理。
运行验证脚本。scripts/ 目录相对于此技能的基础目录(如上所示"此技能的基础目录"):
python3 <base_directory>/scripts/validate_plan.py <WORKDIR>
脚本向标准输出打印 JSON,匹配 plan-validator 的精确输出格式。
{
"status": "VALID",
"issues": [],
"has_unanswered_questions": false,
"unanswered_questions": [],
"has_answered_questions": false,
"answered_questions": [],
"has_addressed_gaps": false,
"addressed_gaps": [],
"pending_tasks": [{"id": "T-1.1", "description": "...", "acceptanceCriteria": ["AC-001"]}],
"completed_tasks": [],
"manual_tasks": []
}
操作: 解析提取的数据字段。使用 、 等,就像 plan-validator 代理返回它们一样。
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pending_taskscompleted_tasks{
"status": "FORMAT_ISSUES",
"issues": ["Missing required field: openQuestions", "Task missing checkbox in content: '- **T-1.2**: ...'"],
...
}
操作: 以与 plan-validator 的 FORMAT_ISSUES 相同的方式处理——酌情启动修复子代理。
EMPTY_FILE: plan.json 不存在或为空INVALID_JSON: plan.json 包含格式错误的 JSON**T-X.Y** 行都有 - [ ] 或 - [x] 前缀## 标题都存在语义一致性验证(plan-validator 中的第 6 步):
仅在修改计划内容的阶段(第 1 阶段创建、第 2.6 阶段批评合并、第 2.7 阶段最终确定)之后,运行专注于纯语义检查的 plan-validator 代理。
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Deterministic plan.json validation that replaces the plan-validator Sonnet agent for all structural checks. The semantic consistency check (storage/query alignment, task/architecture contradictions) still requires the LLM agent and should be run separately when needed.
Activate this skill instead of launching @code:plan-validator at every plan validation site. The orchestrator should only launch the full plan-validator agent for semantic-only checks after plan creation or modification phases.
Run the validation script. The scripts/ directory is relative to this skill's base directory (shown above as "Base directory for this skill"):
python3 <base_directory>/scripts/validate_plan.py <WORKDIR>
The script prints JSON to stdout matching the exact plan-validator output format.
{
"status": "VALID",
"issues": [],
"has_unanswered_questions": false,
"unanswered_questions": [],
"has_answered_questions": false,
"answered_questions": [],
"has_addressed_gaps": false,
"addressed_gaps": [],
"pending_tasks": [{"id": "T-1.1", "description": "...", "acceptanceCriteria": ["AC-001"]}],
"completed_tasks": [],
"manual_tasks": []
}
Action: Parse the extracted data fields. Use pending_tasks, completed_tasks, etc. as if the plan-validator agent returned them.
{
"status": "FORMAT_ISSUES",
"issues": ["Missing required field: openQuestions", "Task missing checkbox in content: '- **T-1.2**: ...'"],
...
}
Action: Handle the same way as plan-validator FORMAT_ISSUES — launch fix subagents as appropriate.
EMPTY_FILE: plan.json doesn't exist or is emptyINVALID_JSON: plan.json contains malformed JSON**T-X.Y** line has - [ ] or - [x] prefix## headers present in contentSemantic consistency validation (Step 6 in plan-validator):
Only run the plan-validator agent with semantic-only focus after phases that modify the plan content (Phase 1 creation, Phase 2.6 critic merge, Phase 2.7 finalization).
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