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Glama

Convert Code Tool

convert_code
Read-onlyIdempotent

Convert code between text formats (e.g. JSON↔YAML, CSS↔SCSS). Pure text transformation: the source is parsed and re-serialized, never executed and never stored. Use list_code_converters for valid from/to ids and per-converter options. Rate limit: 30 calls/min per IP.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesTarget format id.
codeYesSource code to convert.
fromYesSource format id (see list_code_converters).
optionsNoPer-converter options (see optionsSchema in list_code_converters).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the readOnlyHint and idempotentHint annotations, the description adds important behavioral context: the source is 'parsed and re-serialized, never executed and never stored.' It also discloses a rate limit of 30 calls/min per IP, which is valuable operational information not present in the schema or 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?

Three sentences, each serving a distinct purpose: what the tool does, safety behavior, and how to find required identifiers/options. The description is front-loaded and contains no filler or redundancy.

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?

Despite no output schema, the tool's behavior is adequately described for invocation: it takes code and format IDs, uses list_code_converters for valid values, and has a documented rate limit. The pure-transformation guarantee and no-storage note give sufficient context for an agent to use it safely without additional queries.

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?

The input schema already covers all four parameters with descriptive text (100% coverage), so the description does not need to compensate. It reinforces the meaning of from/to by pointing to list_code_converters, and the JSON↔YAML/CSS↔SCSS examples add semantic flavor, but the schema carries the primary parameter documentation burden.

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?

The description begins with a specific verb and resource: 'Convert code between text formats,' supported by concrete examples (JSON↔YAML, CSS↔SCSS). It clearly distinguishes this from sibling tools by emphasizing pure text transformation, which separates it from minify_code, detect_code, and other tools.

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 explicitly directs users to list_code_converters for valid from/to IDs and per-converter options, which is a clear alternative for setup. It also clarifies that this is a pure transformation tool, but it does not explicitly address when to choose this over closely related siblings like minify_code.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct operation within the color, font, or code utility domains. Descriptions clearly differentiate retrieval, search, and action tools, so an agent can reliably select the right one without ambiguity.

Naming Consistency4/5

All names use snake_case and are readable, but there's a mix of direct verb_noun patterns (check_contrast, extract_colors) and a get_ prefix for retrieval tools (get_font, get_palette). The inconsistency is minor and the pattern remains predictable overall.

Tool Count5/5

15 tools is at the upper end of the well-scoped range, but each tool serves a clear, distinct purpose across three focused domains (fonts, colors, code). No tool feels redundant or unnecessary for the server's mission.

Completeness5/5

The server provides a comprehensive lifecycle for its domains: font search, metadata, file access, CSS generation, and image recognition; color extraction, naming, shading, contrast checking, and palette search; and code detection, conversion, and minification. No obvious gaps exist.