Fluently provides 11 tools with consistent naming (verb_noun pattern: list_, find_, get_, evaluate_, contribute_) and complete input schemas. However, descriptions are generic and lack LLM-optimization guidance. Most tool descriptions are 50-100 chars, below the 194-char baseline for A+ tools. Parameter descriptions exist but are minimal (e.g., 'The cycle id' for get_cycle_detail). No output schemas are documented, critical for agents planning downstream calls. Error handling and recovery guidance are absent. Tool composition is sound (each does one thing), but descriptions don't explain WHEN to use each tool vs. similar ones (e.g., find_relevant_cycles vs. get_cycle_detail). STDIO transport caps protocol readiness at 50.

• Document output schemas for all 11 tools. Include field names, types, and which fields are needed for chaining (e.g., cycle_id from find_relevant_cycles → get_cycle_detail). Use JSON Schema format.
• Expand tool descriptions to 100-200 chars. Add WHEN guidance: 'Use find_relevant_cycles to discover cycles matching a task; use get_cycle_detail to retrieve full context for a known cycle_id.'
• Add error handling with recovery hints. E.g., get_cycle_detail: 'If cycle not found, try find_relevant_cycles() with a task description to discover available cycles.'
• Migrate from STDIO to Streamable HTTP transport to enable remote access and hosted client compatibility.
• Define a strict schema for contribute_cycle's 'dimensions' parameter (object with required keys: delegation, discernment, diligence, etc., each with description, example, antipattern fields).