Universal CLI & Headless AI Agent Delegation Engine for MCG, LiteLLM, and LibreChat
Single tool 'delegate_task' has a well-structured schema with all parameters typed and described. Naming is clear (verb_noun pattern). Description is adequate (145 chars, within 10-1024 range). However, output schema is undocumented, the tool returns a string but does not specify the structure of success vs. failure responses. Error handling is minimal: failures are concatenated into the return string rather than providing actionable recovery guidance. No tool annotations (readOnlyHint, destructiveHint, idempotentHint) despite the tool having WRITE risk. Parameter descriptions could be more prescriptive about constraints (e.g., executor enum values, timeout bounds, workspace path validation rules).
Delegate a coding, analysis, or troubleshooting task to a local AI agent engine.
Output schema undocumented. Tool returns a string but does not specify structure of success vs. error responses. LLMs cannot plan downstream actions or extract structured data.
Error handling lacks recovery guidance. Failures concatenate error + output into a single string. Should categorize errors (retryable, user-fixable, fatal) and provide actionable next steps.
Tool marked WRITE risk but has no destructiveHint annotation. Agents need explicit signal that this tool modifies state and may have irreversible consequences.
Parameter 'executor' accepts free-form string with implicit enum (opencode|agy). Should declare as enum type in schema to prevent hallucinated values.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | C | 61 | <=2025-11-25 | v2 |
Parameter 'timeout' lacks bounds. Description says 'default: 180' but does not specify min/max. Unbounded integers let LLMs pass absurd values (e.g., 999999 seconds).