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delegate_task

Read-only

Offload bounded analysis of selected read-only workspace files to an auxiliary LLM, returning text, Markdown, JSON, or diff output for the calling agent to verify.

Instructions

Delegate a bounded task using optional read-only workspace files.

File paths must be relative to workspace_root. Use flash for routine work and pro for difficult analysis. Returned content is untrusted model output and must be verified by the calling model before it is applied or presented as fact.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYes
filesNo
modelNoflash
contextNo
providerNodeepseek
output_formatNotext
workspace_rootNo
reasoning_effortNohigh
max_output_tokensNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, destructiveHint=false, openWorldHint, idempotentHint=false), so the bar is lower. The description adds genuinely important context beyond that: returned content is untrusted model output that must be verified before being applied or presented as fact, and file paths must be relative to workspace_root.

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

Conciseness5/5

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

Four short sentences, each earning its place: purpose, path constraint, model choice, and verification warning. Front-loaded with the core action and free of filler.

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

Completeness3/5

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

An output schema exists so return values need no explanation, and the untrusted-output warning is valuable. However, for a 9-parameter tool with 0% schema coverage, six parameters receive no semantic explanation anywhere, leaving meaningful gaps an agent must guess at.

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

Parameters2/5

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

Schema description coverage is 0% across 9 parameters, so the description carries the full burden and only partially delivers. It clarifies files (read-only workspace files), model (flash vs pro), and workspace_root (relative path base), but leaves context, provider, output_format, reasoning_effort, max_output_tokens, and task undefined.

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

Purpose4/5

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

States a specific verb and resource ('delegate a bounded task') and scopes it with 'using optional read-only workspace files'. The annotation title confirms it as delegation to an auxiliary LLM. No siblings exist to differentiate from, so it lands at 4 rather than 5.

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

Usage Guidelines2/5

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

The description offers model-selection guidance ('Use flash for routine work and pro for difficult analysis'), which is really parameter advice rather than when-to-use guidance. It never states when delegation is appropriate versus doing the work inline, nor any exclusions or prerequisites.

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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