Moltline Educator Toolkit

Get Free Skill

get_free_skill

Read-onlyIdempotent

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

Typical input {"slug": "curriculum-architect-hs"} returns {"slug": ..., "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.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "slug": "<slug>"
    },
    "name": "get_free_skill"
  }
}

Input Schema

Name	Required	Description	Default
`slug`	Yes	Product slug exactly as returned by list_products, e.g. "curriculum-architect-hs"; must be non-empty.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedAug 17, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already declare read-only, idempotent, non-destructive, but the description adds context annotations cannot: no plan is required, exactly one skill is returned, and malformed input never raises a protocol error but returns a structured {"error": ...} object with remediation. It also states retry is always safe after correcting input.

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?

Front-loaded with the free-gateway purpose, then the example, then the sibling exclusion and error contract. The inline input/output JSON illustration is somewhat verbose given an output schema exists, but each sentence still carries routing or error-handling information.

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?

Covers prerequisites (no plan), selection behavior (automatic from slug), exclusion to get_full_skill, and a full error contract with remediation. An output schema exists, so the return-shape detail is redundant but harmless, and nothing an agent needs in order to call it correctly is missing.

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 100%, so the schema already documents slug, but the description adds a worked example ({"slug": "curriculum-architect-hs"}) and clarifies that the slug determines which skill is selected automatically. That is meaningful added meaning beyond the schema, though limited to a single parameter.

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 and resource ('Load a product's free gateway skill with its complete instructions') and immediately scopes it with 'FREE' and 'chosen automatically from the slug'. It explicitly distinguishes itself from the sibling get_full_skill, so an agent can route without opening either schema.

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?

Gives an explicit positive trigger ('Use when the caller wants usable instructions immediately') and an explicit negative one ('Not for the product's other skills: those are named and need get_full_skill with a skill_name, which requires a paid plan'). It even names the corrective path for bad input ('Use list_products').

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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