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Moltline Outbound Engine

Get Free Skill

get_free_skill
Read-onlyIdempotent

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

Typical input {"slug": "linkedin-outreach"} 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.

Input Schema

NameRequiredDescriptionDefault
slugYesProduct slug exactly as returned by list_products, e.g. "linkedin-outreach".

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive), yet the description still adds material context: no plan required, automatic skill selection, and a full error contract (never raises protocol errors, returns {"error": ...} with remediation). That error behavior in particular is not derivable from annotations or schema.

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 purpose and cost ("FREE."), then example, then routing rule, then error contract. Slightly long because the inline JSON examples take vertical space, but no sentence is filler.

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 one-parameter read tool, everything an agent needs is present: what comes back, which skill is selected, what happens on bad input, and that retry is safe. Output and error shapes are described, which more than compensates for the single-parameter surface.

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% and the slug parameter is well documented, so the baseline is 3. The description goes further with a worked example ({"slug": "linkedin-outreach"}) and an error example that tells the agent what to do with a bad slug, adding meaning beyond the schema text.

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") plus the scoping rule that exactly one skill is returned, auto-selected from the slug. It also explicitly distinguishes itself from get_full_skill, so an agent can separate the two without inspecting 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 trigger ("Use when the caller wants usable instructions immediately") and an explicit exclusion ("Not for the product's other skills: those are named and need get_full_skill with a skill_name, which requires a paid plan"). When-to-use, when-not, and the alternative are all named.

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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