Critical gaps across all dimensions. Tool descriptions are minimal (10-30 chars, well below 50-200 char baseline for LLM optimization). No input schemas visible in source, only parameter names and types inferred from brief descriptions. No output schemas documented. Parameters lack detailed descriptions explaining format, constraints, or dependencies. No error handling guidance. No tool annotations (readOnlyHint/destructiveHint). Security-sensitive tool (post_message) lacks permission documentation. Composition is weak: tools are minimal stubs without chaining support (e.g., no user_id returned from whoami to enable downstream calls).

• Add formal JSON Schema for all tools with type declarations (string, number, boolean, object, array), required fields, and constraints (minLength, maxLength, enum, pattern, minimum, maximum).
• Expand tool descriptions to 50-200 characters. Include WHAT the tool does, WHEN to use it (vs similar tools), and WHAT it returns. Example: 'Read a workspace documentation file by path. Returns file content as plain text. Use this to retrieve documentation before posting summaries. Path must be relative to workspace root.'
• Document output schemas for each tool. Specify field names, types, and whether they are required. E.g., whoami should return {user_id: string, username: string, email: string, role: string}.
• Add parameter descriptions for all inputs. For read_doc's 'path' param: 'Relative path to the documentation file within the workspace (e.g., README.md, docs/api.md). Must not contain .. or absolute paths.'
• Add tool annotations: mark read_doc and list_docs with readOnlyHint=true; mark post_message with destructiveHint=true and document required permissions (e.g., 'write:messages').