TailFlow exposes 4 read-only log-querying tools with complete JSON schemas and reasonable descriptions (avg 60 chars). All tools have proper input schemas with typed parameters and descriptions. However, descriptions are terse and lack LLM-optimized guidance on WHEN to use each tool vs. alternatives. Output schemas are not documented. Error handling is minimal, no recovery guidance or actionable error messages visible. Tools are well-named (verb_noun pattern) and focused, but lack composition hints and chaining IDs.

• Document output schemas for all 4 tools. Example: 'get_errors returns {errors: [{message: string, stack_trace: string[], count: integer, first_seen: ISO8601, last_seen: ISO8601}], total: integer}'. This enables LLMs to extract and chain data.
• Expand tool descriptions to 50 - 150 chars with WHEN guidance. E.g., 'get_errors: Returns deduplicated error groups with stack traces. Use this to find recurring failures; use search_logs for individual lines matching a pattern.'
• Add enum constraints to 'level' parameter across all tools: ['trace', 'debug', 'info', 'warn', 'error']. Replace description examples with formal enums.
• Document error cases and recovery paths. E.g., 'If grep regex is invalid, returns {error: "Invalid regex: <reason>", suggestion: "Try escaping special chars or use a simpler pattern"}.'
• Add composition hints in descriptions. E.g., 'wait_for_logs: After calling this, pass the returned cursor to search_logs to fetch full context around the match.'

Inferred effective spec: <=2025-11-25.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry