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syrian963

django-chainsaw-mcp

by syrian963

project_info

Read-onlyIdempotent

Verify a Django project loads correctly and report its identity to confirm MCP transport and Django boot are working.

Instructions

Check that the target Django project loads, and report what it is.

Run this first when something is not working. It is the smallest call that
proves both halves of the setup: the MCP transport and the Django boot.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.3

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds valuable behavioral context beyond those annotations by explaining what the call proves about the environment (MCP transport and Django boot), which is exactly the kind of context an agent needs for a first-step diagnostic. No contradiction with 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?

The description is a compact two-sentence definition with the primary purpose front-loaded. The second sentence earns its place by giving usage context and explaining why this tool is the correct first call. There is no redundant or filler language.

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?

For a zero-parameter, read-only health-check tool, the description covers what the tool does, when to run it, and what it proves about the setup. The presence of an output schema means return-value details do not need to be spelled out in the description, and annotations cover the behavioral safety profile.

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?

This tool has zero parameters, so the baseline is 4. The description does not need to explain parameter behavior, and schema coverage is effectively complete with an empty input schema.

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 states a specific verb ('Check that the target Django project loads') and a clear resource (the Django project), making the tool's purpose immediately understandable. It does not explicitly distinguish itself from siblings like 'check' or 'project_profile', but the 'report what it is' phrasing and emphasis on setup verification make the identity reasonably clear.

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 explicit usage timing: 'Run this first when something is not working.' It also explains why it should be run first, because it is the smallest call proving both MCP transport and Django boot. It does not name alternatives or state when not to use this tool, but the guidance is clear and actionable.

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