5dive MCP demonstrates solid fundamentals: all 6 tools are explicitly registered with complete input schemas, clear descriptions, and well-structured parameters. Naming follows verb_noun convention consistently (task_create, task_show, task_list, agent_send, agent_list, digest_get). Descriptions are concise and action-oriented (average ~120 chars), answering what the tool does and when to use it. All parameters have descriptions and type constraints. However, output schemas are entirely undocumented, the code shows the CLI returns JSON but provides no schema guidance to LLMs about response structure, cardinality, or fields. Error handling is present (rejects with readable messages) but lacks recovery guidance, errors do not suggest next steps or classify retryability. Composition is clean: each tool has one responsibility, names are unambiguous, and parameter inputs align well with expected outputs (e.g., task_create returns an id that task_show accepts). The server lacks security annotations (no destructiveHint/readOnlyHint on tools), which is a gap for an agent-accessible tool that modifies state.

• Document output schemas for all 6 tools. For task_create, explicitly state the return format (e.g., {id: string}). For task_show and task_list, document the task object structure and available fields. For agent_send and agent_list, clarify response types.
• Add error recovery guidance. Modify the run5dive() error handler to catch specific error codes or messages and annotate responses with recovery hints. E.g., if a task ID is not found, suggest checking task_list(); if an assignee is invalid, suggest agent_list().
• Add tool annotations. Mark task_create and agent_send with destructiveHint: true and idempotentHint: false (since sending a message twice to the same agent is not idempotent). Mark read-only tools with readOnlyHint: true.
• Document task_list pagination. If the 5dive CLI supports limit/offset or cursors, expose them as optional input parameters. If unbounded, state a hard default limit (e.g., 'Defaults to first 20 tasks') in the description.
• Add parameter format hints. For the 'id' parameter in task_show, clarify the expected format: 'Task ID (numeric like 923 or DIVE-923). Numeric IDs are preferred.' This avoids ambiguity and guides LLM input generation.
• Document the from parameter's purpose clearly in task_create. Current description is bare ('Who is filing the task'); clarify whether this is a required agent audit field and what format it expects (agent name, email, etc.).
• Add examples to error messages. When run5dive() fails, include the invalid input value if appropriate. E.g., 'Invalid priority: got "critical", must be one of: low, medium, high, urgent'.