Two tools with basic schemas and minimal descriptions. register_operator has a complete JSON Schema with 4 required parameters (name, preconditions, add_effects, del_effects), each with type and description. plan_task_network similarly has 2 required parameters with types and descriptions. However, descriptions are extremely brief (under 20 chars for both tools), violating the critical baseline that descriptions must be 10 - 1024 chars and actionable for LLM selection. No output schemas documented. No error handling guidance. No parameter constraints (e.g., enums, ranges, patterns). Tool names lack clarity on when to use each vs. alternatives. No idempotency guarantees, no recovery guidance, no audit trail hints.

• Expand tool descriptions to 50 - 200 chars. Example: 'register_operator: Register a primitive action (operator) with preconditions and effects. Preconditions are ground predicates (e.g., "at(robot, lab)") that must hold before execution. Add/delete effects update the state. Call this before plan_task_network to define available actions.'
• Document output schemas in tool metadata. Add 'outputSchema' field: register_operator returns {type: 'object', properties: {status: {type: 'string'}}}; plan_task_network returns {type: 'object', properties: {plan: {type: 'array', items: {type: 'string'}}}}.
• Add parameter constraints and examples. Preconditions/effects should be described as 'Ground predicates in the form predicate(arg1, arg2, ...), e.g., "at(robot, lab)", "has_key(door1)". Each predicate is a string.'
• Implement error recovery guidance. If plan_task_network returns null, respond with 'No plan found. Verify: (1) initial_state contains required preconditions, (2) all tasks are registered as operators or methods, (3) method decompositions are acyclic.'
• Add idempotency and confirmation patterns. Document that register_operator overwrites existing operators silently. Consider adding a 'dry_run' parameter to plan_task_network to preview the plan without side effects.