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shrimp-task-manager__analyze_task

[Shrimp Task Manager] Analyze technical requirements, dependencies, risks, and edge cases for a planned task.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "summary": "<summary>"
    },
    "name": "shrimp-task-manager__analyze_task"
  }
}

Input Schema

NameRequiredDescriptionDefault
summaryYesTask summary to analyze
technicalContextNoRelevant architecture or constraints

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.4/5.0
Behavior3/5

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

The annotations declare readOnlyHint=false and openWorldHint=true, so an agent already knows this is not a pure read and involves external/model-side work. The description adds nothing about what the analysis produces, whether results are persisted, or that it is non-idempotent, but it does not contradict the annotations either — an 'analyze' step plausibly writes its output back.

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

Conciseness4/5

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

A single front-loaded sentence with no filler; the bracketed namespace prefix is the only removable noise. It is well-sized, though its brevity is also the source of the missing behavioral detail.

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?

For a two-parameter tool with no output schema, the description covers the input side adequately and correctly implies LLM-driven reasoning over a task. It never says what the agent receives back or how the result feeds into split_tasks or verify_task, which leaves a real gap for a workflow tool.

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 coverage is 100% with only two clearly described parameters (summary, technicalContext), so the schema already carries parameter meaning. The description adds no guidance on what belongs in technicalContext (architecture vs. constraints vs. both).

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?

Specific verb 'Analyze' applied to a task, with the analyzed dimensions enumerated (technical requirements, dependencies, risks, edge cases). 'For a planned task' places it in the planning lifecycle relative to siblings, though it never names plan_task/split_tasks/verify_task explicitly, so the differentiation stays implicit.

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 phrase 'for a planned task' implies this runs after planning and before splitting or verification, which is useful sequencing context. However, there is no explicit when-to-use statement, no exclusion of verify_task, and no prerequisite (e.g., must a task exist or a plan be created first).

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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