brain_absorb

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

With no annotations, the description must convey behavior on its own. It does disclose a key behavioral trait: the brain structures input into memories, strategies, and knowledge automatically. However, it does not mention side effects such as deduplication, overwriting, auth requirements, or processing time, leaving some transparency gap.

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 a single, well-structured sentence that front-loads the verb and resource ('Feed raw text into the brain'), then provides examples and a brief note on processing. Every phrase contributes meaning, with no redundancy or filler.

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?

For a simple ingest tool with full schema coverage and no output schema, the description covers the purpose, acceptable content types, and post-processing behavior. It could optionally mention querying the ingested data, but that is not essential for using this tool correctly. Overall, 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?

All three parameters are fully documented in the schema, so the baseline is 3. The description's examples like 'CLAUDE.md' and 'brand guidelines' add a hint of source/content values but do not go beyond the schema's own descriptions. No additional parameter semantics are 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?

The description clearly states the action ('Feed raw text into the brain') and the resource, with concrete examples like CLAUDE.md files, brand guidelines, and meeting notes. It also distinguishes itself by noting that the brain 'structures it into memories, strategies, and knowledge automatically,' which differentiates ingestion from simple storage.

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?

The description gives clear context for when to use this tool: when feeding raw text or documents into the brain. It does not explicitly mention alternatives or when not to use it, but the examples and phrasing make the primary use case obvious. Sibling tools like brain_query and brain_remember imply complementary roles.

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