Moltline Outbound Engine

Get Full Product

get_full_product

Read-onlyIdempotent

Load one product in full: its persona plus every paid skill. PREMIUM (license).

Typical input {"slug": "linkedin-outreach"} returns {"slug": ..., "name": ..., "persona": "", "skills": [{"name": ..., "instructions": ...}, ...], "free_skill": {...}}.

Returns persona plus every skill for one product. Use when the caller wants the whole product. Not for a single skill (get_full_skill) and not for a free look, which list_products and get_free_skill provide with no plan. 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

Name	Required	Description	Default
`slug`	Yes	Product slug exactly as returned by list_products, e.g. "linkedin-outreach".

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context beyond annotations: the non-protocol error behavior (returns error object instead of raising errors) and the exact retry semantics. Slightly redundant on idempotence but adds enough unique behavior detail.

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 front-loaded with the core purpose and example, then adds usage guidance and error behavior. Every sentence is informative, though the second paragraph slightly repeats the first paragraph's intent. Efficient overall, no 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?

Given a single parameter, full schema coverage, rich annotations, an output schema, and clear sibling differentiation, the description leaves no gaps. It covers purpose, alternatives, error behavior, and retry safety. The agent has everything needed for correct invocation.

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 description reinforces the slug parameter with a concrete example ('linkedin-outreach') and tells the agent to use values from list_products. The description adds operational context (source of truth for valid inputs) beyond the schema's type definition, earning above the baseline of 3.

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 explicitly states 'Load one product in full: its persona plus every paid skill' and shows a typical input/output. It clearly distinguishes from siblings by naming get_full_skill and list_products/get_free_skill as alternatives.

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 provides explicit 'when to use' ('Use when the caller wants the whole product') and 'when not to use' ('Not for a single skill... not for a free look') with named sibling alternatives. The error handling section also tells the agent it's safe to retry after correcting input.

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

All Moltline Outbound Engine tools Inspect

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TDQS

A4.7/5.0

Disambiguation5/5

Each tool has a well-defined, unique purpose. The product/skill tools (list_products, get_free_skill, get_full_skill, get_full_product) are differentiated by scope and access level, and the writing tools (audit_copy, subject_line_scorer, sequence_planner, utm_builder) cover distinct aspects of outreach creation with no overlap. Descriptions explicitly state what each tool is not for, further reducing ambiguity.

Naming Consistency5/5

All tool names use snake_case with a consistent verb_noun pattern: 'verb_object' for actions like list_products, get_free_skill, and 'noun_verb' for compound tools like subject_line_scorer. There is no mixing of styles or inconsistent abbreviations.

Tool Count5/5

With 8 tools, the set is well-scoped for an outbound engine. It covers product discovery, skill retrieval, copy auditing, subject line scoring, sequence planning, and UTM building—neither too few to be useful nor too many to be overwhelming.

Completeness5/5

The tool surface appears complete for its stated domain: product/skill lookup, content quality checks (audit_copy, subject_line_scorer), cadence planning (sequence_planner), and campaign tracking (utm_builder). There are no obvious gaps for the knowledge and planning phase of outbound outreach.

Resources

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