deepseek-mcp

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deepseek_task

Delegate repository exploration, debugging, and bounded implementation to a DeepSeek worker. Complete end-to-end tasks with test runs and evidence, returning advisory results with token usage.

Instructions

Delegate a high-context repository task to the DeepSeek worker. Use it for exploration, architecture tracing, evidence collection, debugging, and — when write/Bash tools are enabled — bounded implementation, targeted test execution, and status/diff inspection. The worker should complete the assigned repository work end to end when safe and supported. Output is advisory and ends with a DeepSeek token usage footer.

Input Schema

TableJSON Schema

Name	Required	Description
`task`	Yes	The repository task to delegate. For code changes, request the complete loop: inspect, implement, write/update targeted tests, run checks, inspect status/diff, and report evidence. Keep the task bounded, recoverable, and testable.
`repo_root`	No	Repository root override; only honored when repository.allow_repo_root_argument is true.
`focus_paths`	No	Optional repository-relative paths to inspect first; the worker may follow evidence elsewhere.
`output_detail`	No	Result compactness: brief, normal (default), or detailed. One of: brief \| normal \| detailed.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 4, 2026

TDQS

A3.8/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does disclose that output is 'advisory,' that the worker completes work 'end to end when safe and supported,' and that output includes a 'DeepSeek token usage footer.' However, it does not explicitly warn about potential file modifications, command execution side effects, latency, or cost implications beyond the token footer, leaving meaningful behavioral gaps.

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?

The description is three sentences with no filler. It front-loads the core delegation purpose, then adds use cases and behavioral caveats. Every sentence earns its place, and the content is dense but readable.

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

Completeness4/5

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

Given 100% schema coverage, an output schema, and the description's explicit use-case list, the definition is largely complete for selecting and invoking the tool. The main gap is the lack of direct comparison with deepseek_review and deepseek_usage, which would help an agent choose among siblings in ambiguous situations.

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

Parameters3/5

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 four parameters. The description adds general guidance about keeping tasks 'bounded, recoverable, and testable,' but it does not enrich individual parameter meaning beyond what the schema provides. Baseline 3 is appropriate.

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?

The description opens with a clear verb-plus-resource statement: 'Delegate a high-context repository task to the DeepSeek worker.' It enumerates concrete use cases (exploration, architecture tracing, evidence collection, debugging, bounded implementation) that make the tool's scope understandable. It does not explicitly distinguish itself from sibling tools deepseek_review and deepseek_usage, so it stops short of a 5.

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

Usage Guidelines4/5

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

The description gives clear context about when to use the tool, listing several task categories and adding the important condition 'when write/Bash tools are enabled' for implementation-related work. It does not name alternatives or provide explicit when-not-to-use guidance, so it does not reach the 5 level.

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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