local_map_reduce_file

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It reveals the local Ollama dependency and map-reduce approach, but it does not mention runtime expectations, side effects, file modification behavior, return format, failure modes, or resource requirements.

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, front-loaded sentence with no filler; the action and resource appear immediately. It is structurally efficient, though its brevity contributes to the lack of operational detail.

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?

The tool has six parameters, no schema descriptions, and no annotations, yet the description is only one sentence. Prerequisites, parameter semantics, output behavior, and relationship to sibling tools are left unexplained, so the definition is not complete enough for reliable 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 0% and the description names none of the six parameters. An agent cannot infer the meaning of file_path, extraction_goal, model, chunk_size, overlap, or concurrency from the text, so the description does not compensate for the schema gap.

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 names a specific action (compress), specific target resources (large files, traces, logs), a distinguishing method (local Ollama Map-Reduce), and its intended purpose (before ingesting into context). This differentiates it from sibling summarization/extraction tools by the map-reduce mechanism and pre-ingestion use case.

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 clearly situates usage: apply this when dealing with large files, traces, or logs that need compression before context ingestion, using local Ollama. It does not explicitly name alternatives or exclusion criteria, but the 'before ingesting into context' framing and large-file focus provide practical guidance.

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