summarize_local

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

With no annotations provided, the description carries the full behavioral disclosure burden. It states that the tool 'Runs on the user's GPU at no cloud cost' and 'Returns a concise prose summary,' which are useful behavioral details. It does not mention potential latency, failures, or size limits beyond the schema, but the disclosure provided is solid.

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 concise and well-structured: a clear opening definition, a practical use-case sentence, a cost/location statement, and a return-value sentence. Every sentence contributes useful information without redundancy or padding.

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 that an output schema exists and all parameters are documented, the description covers the essential usage context well. It explains when to call the tool, what it returns, and why local execution is beneficial. It could be more complete by explicitly distinguishing from sibling tools like extract_local or ask_local, but nothing critical is missing for 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 description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds a small note about passing `focus` to bias the summary, but this largely repeats what the schema's focus parameter already says. A baseline 3 is appropriate because the schema does the heavy lifting.

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 identifies the tool as 'summarize a block of text using the local model', which is a specific verb and resource. It communicates the core purpose well, but it does not explicitly differentiate from sibling tools like extract_local or ask_local, so it falls short of full sibling distinction.

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 clear context for when to use the tool: 'Use to offload long files, logs, transcripts, or docs the cloud model does not need to fully ingest.' It also tells the agent to call this 'instead of reading a large blob into the cloud context,' giving practical usage guidance. However, it does not name specific alternatives or state when not to use it.

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