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PyEye Server

by okeefeco

find_flask_extensions

Locate Flask extensions in use across the main project or configured namespaces to identify dependencies and analyze framework usage.

Instructions

Find Flask extensions in use.

Args: scope: Search scope (default: this tool's scope_defaults entry in the project config, else scope_defaults.global, else "main"): - "main": Only the main project (default for plugins) - "all": Include configured namespaces - "namespace:name": Specific namespace

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "find_flask_extensions"
  }
}

Input Schema

NameRequiredDescriptionDefault
scopeNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.0.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the burden, and it does disclose a real behavioral detail: the default scope resolution chain (tool's scope_defaults entry, then scope_defaults.global, then "main"). It does not state that the operation is read-only, whether results are deduplicated or ordered, or anything about cost/latency, and it relies on the output schema for return shape.

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?

The one-line purpose statement is front-loaded and the scope semantics follow in a compact list. RST-style backticks and the "Args:" docstring boilerplate are mild noise but not enough to obscure the content.

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?

For a single optional-parameter lookup with an output schema available, the definition covers purpose, the parameter's value space, and the default-resolution behavior. Only the array form of scope and any read-only/mutation assurance are absent.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate, and it does: it names the three accepted scope forms ("main", "all", "namespace:name") and spells out the fallback order for the default. The only gap is that it does not say the parameter also accepts an array of strings, which the schema allows but never describes.

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?

"Find Flask extensions in use" gives a specific verb and resource, and among the many find_flask_* siblings the resource word "extensions" alone identifies what is returned. It stops short of differentiating itself from neighboring tools like find_flask_config or configure_packages, so an agent must infer the boundary.

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?

Usage is implied by the verb "find" and the scope argument's semantics (main project vs configured namespaces), but there is no statement of when to reach for this tool versus find_flask_config or configure_packages, and no exclusions or prerequisites. Nothing is misleading, but the routing signal is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.