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Get Free Skill

get_free_skill
Read-onlyIdempotent

Load a product's free gateway skill with its complete instructions. FREE.

Typical input {"slug": "brand-voice"} returns {"slug": "brand-voice", "skill": "", "instructions": ""}.

Returns exactly one skill - the product's free gateway skill - chosen automatically from the slug, with no plan required. Use when the caller wants usable instructions immediately. Not for the product's other skills: those are named and need get_full_skill with a skill_name, which requires a paid plan. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""} (for example {"error": "unknown slug ''. Use list_products."}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesProduct slug exactly as returned by list_products, e.g. "brand-voice".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. The description goes beyond by explaining error behavior: 'never raises a protocol error — it returns an error object' and that after correcting input it is 'always safe to retry'. This adds critical behavioral context above the 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 well-structured: it opens with the core purpose, then provides an input/output example, usage guidelines, differentiation from sibling, error handling, and safety guarantees. Every sentence adds value, and there is no unnecessary repetition or jargon.

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 tool with output schema and clear annotations, the description covers everything needed: purpose, usage context, error recovery, and linkage to list_products for valid slugs. It is complete for an agent to select and invoke the tool correctly without additional information.

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?

Schema description coverage is 100% and already states the slug must be exactly as returned by list_products. The description adds a concrete example and clarifies the slug determines which skill is loaded, but does not provide additional semantics beyond what the schema covers. Baseline 3 is appropriate.

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 states it loads a product's free gateway skill with complete instructions, specifying it returns exactly one skill chosen automatically from the slug. It explicitly differentiates from get_full_skill, which handles other skills and requires a paid plan. This provides a specific verb-resource scope and clear sibling distinction.

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?

The description says 'Use when the caller wants usable instructions immediately' and explicitly warns 'Not for the product's other skills: those are named and need get_full_skill with a skill_name, which requires a paid plan.' This gives clear when-to-use and when-not-to-use guidance, along with the alternative tool.

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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Glama MCP Gateway

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TDQS

A4.7/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: prose analysis, headline scoring, reading stats, platform length check, product listing, free/paid skill retrieval, and full product details. There is no ambiguity between any pair of tools, and descriptions explicitly note what not to use them for.

Naming Consistency5/5

All tool names use consistent snake_case verbs followed by nouns (e.g., analyze_writing, list_products, get_free_skill). Even reading_time and social_length_check follow the pattern, albeit with nouns first, but the style is uniform and predictable.

Tool Count5/5

With 8 tools, the server is well-scoped. It covers both content analysis (4 tools) and product catalog access (4 tools) without overloading or underrepresenting either domain. The number feels appropriate for a focused studio toolkit.

Completeness4/5

The tool set covers the core functions of a Creator Studio: writing analysis, headline optimization, reading time, social length checks, plus full product catalog introspection. Minor gaps like grammar checking or content generation exist but are outside the stated scope. The set has no dead ends for the intended workflows.

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