智能体调用服务,支持智能体管理和调用、工作流程执行、任务管理、模板处理、状态跟踪。基于 .bmad-core 的智能体调用服务,支持双 LLM 模式(内置 LLM 和外部 API)。
Critical gaps across all dimensions. Tool descriptions are present but minimal (10-30 chars, well below 50-200 char baseline for LLM optimization). Input schemas visible for most tools but lack parameter descriptions, a hard violation of the rubric. No output schemas documented. Parameter types are defined but descriptions are missing or trivial. 5 test tools (test_connection, test_agents, test_llm_mode, test_workflows, test_templates) should not be exposed as production tools. Error handling is absent, no recovery guidance, no categorization. No evidence of idempotency, pagination, or composition patterns. Tool names are reasonable (verb_noun style) but descriptions fail to explain WHEN to use each tool or what it returns.
激活指定的智能体
获取特定智能体的详细信息
获取系统信息
获取特定工作流程的详细信息
列出所有可用的 BMAD 智能体
列出所有可用的工作流程
运行完整测试套件
启动指定的工作流程
Parameter descriptions missing across all tools. Input schemas define types (string) but lack descriptions explaining what each parameter controls, expected format, or constraints. Hard violation of pattern:tool-description.
Output schemas not documented. Tools return complex objects (agents list with id/name/title/icon/description/when_to_use/role/focus) but no schema is declared in tool definitions. LLMs cannot plan downstream calls or extract fields reliably.
Test tools exposed as production tools. test_connection, test_agents, test_llm_mode, test_workflows, test_templates, run_full_test should not be callable by agents, they are internal diagnostics. Pollutes the tool namespace and invites misuse.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 40 | 2026-07-28+ | v2 |
测试智能体功能
测试 BMAD 服务连接
测试 LLM 模式
测试模板功能
测试工作流程功能
No error handling or recovery guidance. Tools lack descriptions of failure modes, retryability, or next steps. A failed activate_agent call returns nothing, LLM cannot determine if it should retry, ask the user, or try a different agent.
Tool descriptions are minimal (10-30 chars). Baseline for LLM-optimized descriptions is 50-200 chars. Current descriptions ('列出所有可用的 BMAD 智能体', '获取特定智能体的详细信息') lack WHEN to use, prerequisites, or what the tool returns. LLMs cannot reliably select the right tool.