Ask the Project Brain

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

No annotations are provided, so the description must disclose behavior on its own. It explicitly states the tool returns 'nothing answers that' rather than guessing when the brain has not read the source, and that results include the source. This covers the key behavioral trait of avoiding fabrication.

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?

The description is two sentences, front-loaded with the action, and includes essential behavioral details without any redundant text.

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?

With no output schema and no annotations, the description covers the input scope, output format, and empty-result behavior. It could mention potential pagination or ordering details, but for a simple query tool with a limit parameter, it is sufficiently complete.

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 schema already documents both parameters with coverage 100%, so the baseline is 3. The description adds meaningful context for the 'question' parameter by specifying the kind of questions allowed (history, decisions, constraints, customer feedback), and clarifies the output format (fragments with sources), which enriches the parameter semantics.

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?

The description uses a specific verb ('Ask') and identifies the resource ('the product's own history') and scope ('decisions, constraints, what customers said'). It distinguishes from sibling tools like get_fragment and list_sources by focusing on natural-language question retrieval rather than direct retrieval or enumeration.

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?

It gives clear context for when to use: asking plain-language questions about the product's history. It does not explicitly name alternatives or exclusions, but the context is unambiguous.

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