get_lambda_overview

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, description carries full burden. It discloses that environment variable values are never returned, and that it returns correct handler event shapes. It does not mention data freshness, pagination, or limits, but for a read-only list tool this is acceptable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, each serving a purpose: first enumerates returned fields, second specifies use cases, third contrasts with sibling. No filler and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description explains return values in detail (runtime, memory, timeout, env key names, triggers). However, it does not clarify what 'correct handler event shape' means or whether data is real-time, leaving minor gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters. Baseline for 0 params is 4. No additional explanation needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description states it returns Lambda functions with specific fields (runtime, memory, timeout, env key names, triggers with handler shapes) and distinguishes from sibling analyze_function by noting when to use each: for audits or trigger event shape without full analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Call this when auditing Lambda configuration for default memory or high timeouts, or when you need the trigger event shape without running analyze_function.' Provides clear context but does not comprehensively list when not to use or all alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.