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Think MCP

Think MCP

by GofMan5
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript

Think Logic

think_logic
Read-only

Generate a read-only code-analysis checklist for a specified target, depth, focus, and tech stack. Use this methodology to guide analysis without inspecting code or storing results.

Instructions

Return a read-only code-analysis checklist. It does not inspect code, store progress, or produce findings.

Use only when a model needs a methodology; use think or think_cycle to perform the analysis.

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": {
      "target": "<target>"
    },
    "name": "think_logic"
  }
}

Input Schema

NameRequiredDescriptionDefault
depthNoMethodology depthstandard
focusNoFocus areas to prioritize
stackNoTech stacks for stack-specific checks
targetYesWhat to analyze (feature, flow, component, system description)
contextNoAdditional context (tech stack, constraints, requirements)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv5.6.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true, and description reinforces read-only behavior and adds boundaries (no code inspection, no storage, no findings). No contradictions, and description adds context beyond annotations.

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?

Two concise sentences plus one usage directive; front-loaded with purpose, no wasted words. Every sentence adds value.

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

Completeness5/5

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

Given the tool's simplicity (read-only checklist with well-described schema), the description covers purpose, usage, and behavioral boundaries adequately. No gaps for an AI agent to select and invoke correctly.

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 baseline is 3. Description does not add additional meaning beyond schema; parameters are already well-described in the input schema.

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?

Description clearly states it returns a read-only code-analysis checklist, explicitly stating what it does not do (inspect code, store progress, produce findings). It also distinguishes from siblings by directing to use think or think_cycle for analysis.

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

Usage Guidelines5/5

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

Explicit usage guidance: 'Use only when a model needs a methodology' and specifies alternatives (think, think_cycle) for performing analysis. This provides clear when-to-use and when-not-to-use conditions.

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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