Single tool 'execute_skill_action' has a minimal description (97 chars) that lacks actionable context for LLM selection. Input schema is present but parameter 'query_payload' has only a generic description ('Input execution payload for this skill') with no format, length, or content constraints. No output schema is documented, the tool returns a hardcoded JSON string with no structure definition. No error handling guidance, no idempotency markers, and no indication of side effects despite the WRITE risk classification. The tool name is vague (execute_skill_action could mean anything) and does not follow verb_noun conventions clearly. No parameter validation rules, no recovery guidance, and no composition hints for chaining with other tools.

• Document the output schema explicitly. Define what fields the response contains (e.g., status, message, result_data, execution_id) so LLMs know what to extract and how to chain downstream calls.
• Add format and length constraints to 'query_payload'. Specify: is it JSON, plaintext, a specific schema? What is the max length? What are valid values or patterns? Replace generic description with actionable constraints.
• Expand tool description to 150 - 250 chars. Answer: What does this skill do? When should the LLM call it instead of other tools? What does it return? Include a brief example of a valid use case.
• Add error handling guidance. Document failure modes (e.g., 'Invalid payload format', 'Skill timeout', 'Permission denied') and tell the LLM what to do next (retry, ask user, try alternative tool).
• For a WRITE tool, add idempotency documentation or a dry-run parameter. State whether repeated calls with the same input produce the same result, or if the LLM must track execution IDs to avoid duplicates.