Single tool (tooling_discover) with adequate naming and clear description, but schema completeness is hampered by returning a generic dict without documented structure. Parameters are typed and described, following good naming conventions. However, the return type annotation is vague (→ dict), lacking specification of output fields, structure, and what the 'trust tier' grouping contains. The tool follows verb_noun naming (discover) and includes parameter descriptions with context, but falls short of production-grade schema documentation. The implementation is read-only and well-scoped, but documentation of what fields the LLM should expect in the response would significantly improve usability.

• Add explicit output schema documentation to tooling_discover docstring. Example: 'Returns dict with keys: {tools_by_tier: {tier_name: [{name, description, type, risk_level}]}, total_count: int, search_keywords: [str]}' so LLMs know what fields to extract.
• Document error modes and recovery paths in the docstring. Example: 'If project_path detection fails, returns {error: str} with explanation; suggest use of explicit project_path parameter next time.' This follows the recovery-guide pattern.
• Add validation constraints to parameter descriptions. For domain_keywords, specify: '1-10 comma-separated keywords, each 2-30 characters, alphanumeric + hyphen only. Example: "jira,project-management"'.
• Consider accepting human-friendly formats in project_path (~/myproject, ./src) in addition to absolute paths, and document accepted formats in the parameter description.
• Return structured result with per-tool metadata (name, description, source: registry|mcp|dependencies|cli, risk_level) instead of bare dict so LLMs can reason about tool trustworthiness.