Skip to main content
Glama

Moltline Outbound Engine

Get Full Skill

get_full_skill
Read-onlyIdempotent

Load one paid skill's complete instructions from a product. PREMIUM (license).

Typical input {"slug": "linkedin-outreach", "skill_name": "Connection Openers"} returns {"slug": ..., "skill": ..., "instructions": ""}.

Returns one named skill, selected by skill_name. Use when the caller wants one specific paid skill. Not for the free gateway skill, which get_free_skill returns with no plan, and not for every skill at once (get_full_product). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""} (for example {"error": "unknown slug ''"}). 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.
skill_nameYesExact skill name as listed in that product's "skills" array from list_products.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds significant context: 'Every call is read-only and idempotent, so after correcting the input it is always safe to retry' and describes error handling behavior ('never raises a protocol error — it returns {"error": ...}'). No contradiction with annotations.

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?

The description is moderately long but front-loaded with purpose and premium status. Each section (purpose, example, usage guidance, error behavior) earns its place. Minor redundancy with annotations but still efficient. Could be slightly tighter.

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?

Given the tool has two parameters (no enums), an output schema, and sibling tools, the description covers all essential aspects: purpose, usage context, example, error handling, and retry safety. It is fully sufficient for an agent to correctly select and invoke this tool.

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% (all parameters documented), so baseline is 3. The description adds value beyond schema by explaining the slug comes from list_products and skill_name from the product's 'skills' array, and provides a concrete example of typical input and output. This enriches the parameter meaning.

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 clearly states the tool loads 'one paid skill's complete instructions from a product.' It distinguishes itself by explicitly mentioning it is for paid skills (not the free gateway skill) and contrasts with get_free_skill and get_full_product. The verb 'load' plus resource 'paid skill' is specific and 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?

The description explicitly says 'Use when the caller wants one specific paid skill' and immediately provides exclusions: 'Not for the free gateway skill, which get_free_skill returns with no plan, and not for every skill at once (get_full_product).' This gives clear guidance on when to use and when not to, naming sibling alternatives.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.6/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: audit_copy for message bodies, subject_line_scorer for subject lines, sequence_planner for cadences, utm_builder for UTM URLs, and separate tools for product/skill retrieval (list_products, get_free_skill, get_full_skill, get_full_product) with explicit differences in scope. No two tools overlap in function.

Naming Consistency5/5

All tools follow a consistent snake_case naming convention with a verb_noun pattern (e.g., audit_copy, list_products, subject_line_scorer). The naming is predictable and easy to understand.

Tool Count5/5

With 8 tools covering copy auditing, subject line scoring, cadence planning, UTM building, and product/skill access, the tool count is well-scoped for an outbound outreach server. Each tool serves a necessary function without any redundancy or missing essential operations.

Completeness4/5

The tool surface covers the core tasks of outreach planning and analysis: copy auditing, subject line ranking, cadence planning, UTM building, and product/skill instructions. Minor gaps exist (e.g., no tool for generating outreach copy or managing contacts), but these are outside the server's stated scope and can be handled by other servers.

Resources