Flagpole demonstrates solid tool design with clear verb-based naming (list_, get_, evaluate_, toggle_, upsert_), complete input schemas using JSON Schema with type definitions, and consistent descriptions. All 5 tools have descriptions (avg ~90 chars, within baseline 34-392 range). Parameters are typed and described. However, output schemas are not explicitly documented in the code, responses are inferred from the implementation (e.g., 'flags' array, 'enabled' boolean, 'version' integer). Error handling is basic: the code returns raw store errors (ErrNotFound, ErrStaleVersion) without recovery guidance. No tool annotations (readOnlyHint/destructiveHint) despite clear risk profiles (3 READ_ONLY, 2 WRITE). Parameter descriptions lack format constraints (e.g., 'percentage' accepts 0-100 but this is not stated in the description text, only in the code comment). Composition is clean, each tool has one responsibility, and output includes chaining IDs (key, version) needed for follow-up calls.

• Add formal output schema documentation for each tool. E.g., 'Returns: {"flags": [{"key": string, "enabled": boolean, "version": integer, ...}]}' or use JSON Schema in the tool definition.
• Annotate tools with risk hints: add destructiveHint=true to toggle_flag and upsert_flag; add readOnlyHint=true to list_flags, get_flag, evaluate_flag. This enables LLMs to reason about idempotency and retry safety.
• Enhance error messages with recovery steps. E.g., when ErrNotFound is returned, wrap it as 'Flag "checkout" not found. Call list_flags() to see available flags, or check the key spelling.'
• State parameter constraints in description text, not just code comments. Update upsert_flag's percentage description to: 'optional percentage rollout between 0 and 100; omit to remove the rollout'.
• Clarify evaluate_flag's context parameter: 'evaluation context attributes as an object with string values (e.g., {"id": "user-123", "region": "us-west"}); include an "id" attribute for percentage rollouts'.