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, constraints, or examples of valid payloads. No output schema is documented, the tool returns a hardcoded JSON string with no structure definition. No error handling guidance, no parameter validation rules, and no indication of what 'deterministic, zero-dependency Autonomous Agent Commerce operations' actually entails. The tool name 'execute_skill_action' is generic and does not follow verb_noun convention clearly (what action? what skill?). No evidence of idempotency, permission gates, or audit logging.

• Document the output schema explicitly. Define the structure of the returned JSON object with typed fields (e.g., status: string, message: string, transaction_id?: string, error_code?: number). This enables LLMs to extract and chain results.
• Add format and constraint documentation to 'query_payload'. Specify: expected format (JSON object? string? base64?), required fields, example valid payloads, and character/size limits. Replace generic description with concrete guidance.
• Rename tool to a more specific verb_noun pattern. Examples: 'execute_payment_delegation', 'issue_vault_token', or 'authorize_agent_checkout', each clearly conveys the action and domain.
• Add error handling guidance. Document failure modes (invalid payload, authorization failure, vault unavailable) and what the LLM should do next (retry, ask user, escalate). Include error codes and recovery steps.
• Expand tool description to 100-200 characters explaining: (1) What it does in concrete terms, (2) When to use it (e.g., 'Call this to issue a delegated payment token for an autonomous agent'), (3) What it returns (e.g., 'Returns a signed token with spending limit and expiry').