Moltline Outbound Engine

Sequence Planner

sequence_planner

Read-onlyIdempotent

Plan an outreach cadence with expanding gaps and per-touch purposes. FREE.

Spaces N touches across D days, alternating channels. Typical input {"touches": 5, "days": 14, "channels": ["email", "linkedin"]} returns {"days": 14, "plan": [{"touch": 1, "day": 0, "channel": "email", "purpose": "open with a specific, researched reason"}, ...], "rule": "..."}.

Use when cadence and per-touch purpose are the question. Not for the wording of any single message (audit_copy). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""}. 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
`days`	No	Total span of the sequence in days; values outside 1-365 are clamped. Default 14.
`touches`	No	Number of touches in the sequence; values outside 2-10 are clamped. Default 5.
`channels`	No	Channel names to alternate through in order, e.g. ["email", "linkedin", "phone"]. Default ["email", "linkedin"].

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description builds on these. It adds critical context: the tool never raises a protocol error but returns structured error objects, and it is safe to retry after correcting input. This surpasses what annotations alone convey.

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 concise (8 lines) and front-loaded with the core purpose and a key signal ('FREE'). The example is compact yet informative. Every sentence adds value: usage guidance, error behavior, and idempotency guarantee. 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 the tool's moderate complexity (3 optional parameters, no enums, no nested objects) and the presence of a complete output schema, the description covers everything needed: purpose, usage boundaries, error handling, and idempotency. There are no gaps.

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%, so the schema already documents all three parameters with defaults and ranges. The description's example input shows a typical call but does not add meaning beyond what is in the schema. 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 opens with a specific verb+resource: 'Plan an outreach cadence with expanding gaps and per-touch purposes.' It immediately distinguishes the tool from its sibling 'audit_copy' by explicitly stating what it handles (cadence planning) versus what it does not (message wording). The example JSON clarifies the exact output structure.

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 states when to use this tool ('Use when cadence and per-touch purpose are the question') and when not to ('Not for the wording of any single message (audit_copy)'). It names the alternative sibling tool, giving clear guidance for the AI agent to choose correctly.

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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