compose-bridge

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get_naming_convention

Detect whether a Compose project uses camelCase, snake_case, or PascalCase for tokens before adding or replacing tokens, so new tokens match existing naming conventions.

Instructions

Read-only analysis. Detects if project uses camelCase, snake_case, or PascalCase for tokens.

What it does: Analyzes existing tokens to detect whether project uses camelCase, snake_case, or PascalCase.
When to use: Use BEFORE creating new tokens with add_token or replace_pattern to maintain project consistency.
When NOT to use: Do not use to inspect actual token values; use list_tokens instead.
Side effects: Read-only. No files modified.
Parameters:
  - token_type: 'dimension' (default) or 'color'.
Returns:
  JSON string with detected style (e.g. 'camelCase'), confidence score, examples, and recommendations.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`token_type`	No		dimension

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 19, 2026

TDQS

A4.6/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and does disclose the safety profile: 'Read-only. No files modified.' It also describes the return shape (detected style, confidence, examples, recommendations). It stops short of auth/rate-limit context, but for a pure analysis tool this is solid disclosure.

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?

Labeled sections (What it does / When to use / When NOT to use / Side effects / Parameters / Returns) make it skimmable and front-loaded. There is mild redundancy between the opening 'Read-only analysis. Detects...' line and the 'What it does' line that restates the same detection behavior.

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 single-parameter read-only tool it covers everything an agent needs: purpose, routing to/away from siblings, side effects, parameter values, and returns. An output schema exists, so the added return summary is a bonus rather than a requirement.

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 coverage is 0%, so the description must compensate, and it does: it documents token_type as 'dimension' (default) or 'color', supplying the enum-like values the schema omits. It adds real meaning beyond the raw schema, though there is only one parameter to explain.

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?

States a specific verb+resource: detects the token naming convention (camelCase/snake_case/PascalCase) used by the project. It is clearly distinguishable from siblings like list_tokens or add_token, and the scope is unambiguous.

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?

Explicitly says when to use (BEFORE creating tokens with add_token or replace_pattern) and when not to use (do not use to inspect token values; use list_tokens instead). Both the alternative and the condition that selects it are named.

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