MCP server for orchestrating browser workspace management with contextual AI sidebar, tab isolation, and memory optimization
This server has a single tool 'execute_skill_action' with virtually no definition. The tool description is generic (28 chars, below the 20-char floor for scoring). No input schema is visible in the source code, the mcp_server.py file only prints a JSON status message with no actual tool registration, parameter definitions, or output schema. The tool appears to be inferred from the supported_tools list rather than explicitly defined with a schema. The server is non-functional as an MCP implementation.
Execute a skill action within the contextual workspace browser environment
No input schema defined for execute_skill_action. Tool registration is missing entirely, only a string name appears in a JSON status message.
Tool description is 28 characters ('Execute a skill action within the contextual workspace browser environment'), generic and lacks WHAT, WHEN, and WHY guidance. Does not meet the 10-1024 character guideline or LLM-optimized 50-200 char baseline.
Tool name 'execute_skill_action' is vague. 'execute' and 'action' are generic verbs that do not convey what the tool actually does. Does it browse? Scrape? Click? Type? LLMs cannot infer intent from this name alone.
No output schema documented. LLMs cannot plan downstream calls or extract results. The client.py file shows a mock response structure, but this is not exposed as a tool output schema.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 17 | 2026-07-28+ | v2 |
No error handling or recovery guidance. Tool has no documented error cases, retryability, or actionable error messages. Per pattern:recovery-guide, errors must tell the LLM what to do next.