brain_file_map

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

With no annotations, the description carries the full burden of behavioral disclosure. It clearly states the tool shows authorship (from learn_from_attempts) and related lessons, and provides an example output format. This makes the behavior transparent, though it does not explicitly state that the operation is read-only or non-destructive. The example strongly implies read-only behavior.

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 extremely concise: a single sentence covering purpose, a sentence for usage guidance, and an example. Every sentence earns its place. There is no redundancy or fluff. The structure front-loads the purpose and follows with actionable context.

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 query tool with 2 fully documented parameters and no output schema, the description adequately covers the return value (experts and lessons per file, including example). It does not specify edge cases (e.g., missing files, multiple files), but the example and language imply per-file results. Slightly more detail on grouping or error handling would improve completeness, but it is largely sufficient.

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%, so baseline is 3. The description adds meaning via the example usage and explanation of output, but it does not add new semantic details about the 'file_paths' or 'instance_id' parameters beyond what the schema already provides. The example clarifies the format but does not add conceptual depth.

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 ('show') and resource ('what cachly knows about a list of files — experts + related lessons per file'), clearly distinguishing itself from sibling tools like brain_who_knows (which focuses on who knows a file) and brain_conflicts (conflicts). It immediately conveys the tool's unique value.

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 provides explicit, actionable guidance: 'Call this before starting work on unfamiliar files, or in sync_file_changes to see what knowledge exists.' This gives clear context for when to use it. It does not explicitly state when not to use or alternatives, but the guidance is specific enough to be highly useful.

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