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delegate_file

Read and analyze local files (txt, md, csv, json, code, log) using a local worker to reduce token usage. Specify an objective to extract insights without loading content into the main AI context.

Instructions

Have the local worker read a file (txt/md/csv/json/code/log) without loading it into frontier context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
objectiveYes
persistentNo
output_modeNostructured
force_refreshNo
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions reading a file without loading into frontier context, but omits critical behavioral details: the worker processes the file based on an 'objective' (not just reading), the output_mode parameter controls return format, and the 'persistent' and 'force_refresh' options affect caching. The agent learns little about what happens or what to expect.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence of 18 words, which is very concise. However, conciseness is achieved at the expense of essential information. While there is no wasted text, the description is under-specified and does not earn its place by being informative enough.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 5 parameters (including required ones), no output schema, and no annotations, the description is grossly incomplete. It fails to explain the tool's full behavior, parameter roles, return value, or caching semantics. The agent cannot safely invoke this tool without additional guessing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, yet the description explains none of the five parameters. It does not mention that 'path' is the file location, 'objective' is the task, 'output_mode' controls output format, 'persistent' caches results, or 'force_refresh' bypasses cache. The agent must guess or rely on parameter names, which is insufficient for correct invocation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'read' and the resource 'a file (txt/md/csv/json/code/log)'. It also distinguishes from reading that loads into frontier context, and from sibling tools like delegate_pdf (different file type) and delegate_task/batch (task delegation). The purpose is specific and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description hints at when to use (when you want to avoid loading into frontier context) but does not explicitly state when not to use or provide alternatives. It lacks guidance on comparing with sibling tools like delegate_task or cache tools. The advice is implicit, not actionable.

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

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