Exposes CoWorker agent skills as MCP tools, enabling Claude Code, Cursor, and other MCP-compatible clients to call agent skills via the standard MCP protocol
CoWorker MCP exposes 8 tools with basic schemas but significant quality gaps. Tool names lack clear action verbs (skill_card_query vs search_skills, context_sync vs synchronize_context). Most parameter descriptions are minimal (10-30 chars), below the 72-char baseline. Output schemas are undocumented, callers cannot predict response structure. Error handling is absent from visible code. The skill_to_mcp_tool() conversion infers types from string names ('int', 'float', 'bool') rather than reading explicit schema definitions, suggesting incomplete parameter metadata. No tool has documented return types or pagination guidance. Security concerns: session_id and task_id parameters suggest stateful operations, but no audit trail or permission checks are visible.
Query context from a peer based on trust tier
Synchronize context items with a peer
Propose a collaboration session with specific skills and trust tier
Get a specific skill card by name
Query skill cards by tags or names filter
List all available skills
Execute a skill task with input data and receive results
Tool names lack clear action verbs. 'skill_card_query' should be 'search_skills' or 'list_skills'; 'context_sync' should be 'synchronize_context'. LLMs rely on verb_noun naming to infer intent.
Parameter descriptions are minimal (10-30 chars), far below the 72-char baseline. E.g., 'Optional list of tags to filter skills' lacks guidance on format, valid values, or when to use. LLMs cannot infer constraints from sparse text.
Output schemas are completely undocumented. Callers cannot predict response structure, field names, or types. No documentation of pagination, error responses, or chaining IDs (e.g., does task_request return a task_id for polling?).
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 43 | <=2025-11-25 | v2 |
Execute a workflow step with skill execution and context passing
No error handling guidance. Code shows _error() method but no documentation of error codes, recovery steps, or retryability. LLMs receive raw errors with no actionable next steps.
Stateful parameters (session_id, task_id, timeout) suggest session-based operations, but no audit trail, permission checks, or scope declarations visible. Security posture unclear.