context_stuff_lessons

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

Discloses key behaviors: returns all lessons sorted by confidence, single text block, bypasses RAG/search, token estimate. Adds value beyond readOnlyHint annotation.

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?

Two sentences, front-loaded with core action, no wasted words. Efficient and scannable.

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 optional params with full schema coverage and no output schema required, description covers purpose, behavior, and expected scale, enabling correct invocation.

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?

Schema coverage is 100% with descriptions for all 3 params; description adds no further parameter-specific detail beyond stating default behavior, so baseline 3 is appropriate.

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?

Clear verb+resource: 'Dump ALL prevention lessons into a single text block' distinguishes from siblings like search_lessons by explicitly bypassing RAG/search.

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?

Implicitly states when to use (context injection, bypassing search) and gives size guidance (20-200 lessons, 1K-10K tokens), but lacks explicit when-not or alternative tool names.

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