bulk_read

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

With no annotations provided, the description carries the full burden and does well: it discloses use of a cheap/fast worker model, ~90% token savings, and structured bullet-point output. It could mention accuracy/fidelity tradeoffs or failure behavior, but the core behavior is transparent.

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 concise sentences with key info front-loaded: what it reads, what it answers, and the major benefit. No filler or redundancy.

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?

No output schema exists, but the description specifies output format (structured bullet points) and the token-saving tradeoff. It omits edge-case details like acceptable file types, size limits, or failure modes, but is adequate for a straightforward read-and-summarize tool.

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 the baseline is 3. The description adds light context for 'question' (targeted) and 'file_paths' (multiple or large), but does not provide new parameter-level syntax or constraints beyond the schema.

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 states a specific verb ('Reads'), target resource ('multiple or large files'), and purpose ('answers a targeted question'). It clearly differentiates from siblings like code_write and get_available_models by describing a read/analyze operation.

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: multiple or large files with a targeted question, implying a cost/speed benefit over full reads. It does not explicitly state when not to use or name alternatives, but siblings are not close alternatives, so the implied guidance is sufficient.

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