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Backend Architect MCP Server

Backend Architect MCP Server

by jemhakdog
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

save_test_plan

Store simulation scenarios for structured backend development workflows, enabling organized test planning and state management.

Instructions

Saves simulation scenarios to state.

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": {
      "tests": "<tests>"
    },
    "name": "save_test_plan"
  }
}

Input Schema

NameRequiredDescriptionDefault
testsYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations, the description carries full burden but only states 'Saves simulation scenarios to state' without disclosing behavioral traits such as permissions needed, whether it overwrites existing data, error handling, or side effects. It's inadequate for a mutation tool with zero annotation coverage.

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 a single, front-loaded sentence with no wasted words, making it highly concise. However, this brevity contributes to its lack of detail, but structurally it's efficient.

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

Completeness2/5

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

Given the tool's mutation nature (implied by 'Saves'), no annotations, 0% schema coverage, and an output schema (which helps but isn't described), the description is incomplete. It doesn't cover key aspects like behavior, parameters, or usage context, making it insufficient for effective tool selection.

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%, and the description provides no parameter information beyond the tool name implying 'tests'. It doesn't explain what 'tests' should contain, their structure, or examples, failing to compensate for the schema's lack of descriptions.

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

Purpose3/5

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

The description 'Saves simulation scenarios to state' provides a basic verb ('Saves') and resource ('simulation scenarios'), but it's vague about what 'state' means and doesn't differentiate from sibling tools like save_database_plan or save_roles_plan. It's not tautological but lacks specificity.

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?

No guidance is provided on when to use this tool versus alternatives like save_database_plan or save_roles_plan. The description implies a save operation but offers no context on prerequisites, timing, or exclusions, leaving the agent with minimal usage cues.

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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