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Moltline Outbound Engine

by com.moltlinestudio

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
NameRequiredDescriptionDefault
daysNoTotal span of the sequence in days; values outside 1-365 are clamped. Default 14.
touchesNoNumber of touches in the sequence; values outside 2-10 are clamped. Default 5.
channelsNoChannel names to alternate through in order, e.g. ["email", "linkedin", "phone"]. Default ["email", "linkedin"].

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.9/5.0
Behavior5/5

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

The description discloses the error handling behavior (never raises a protocol error, returns error object) and confirms read-only and idempotent nature, which adds context beyond the annotations that already declare readOnlyHint and idempotentHint. It also explains the clamping behavior for days and touches.

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 with a brief overview, a concrete example, usage guidance, and error handling notes. Every sentence serves a purpose and the key information is front-loaded.

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 complexity (3 parameters, simple output schema), the description fully covers purpose, usage, behavior, parameters, and error handling. The output schema exists and the description explains the return format with an example, making it complete for an AI agent.

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?

The input schema has 100% coverage with descriptions for all three parameters. The description adds value by showing a typical input example and explaining the output structure, but the schema already documents defaults and ranges well. The description does not add new info beyond the schema, but the baseline is 3 and the example enhances clarity.

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 plans an outreach cadence with expanding gaps and per-touch purposes. It specifies the verb (plan), the resource (outreach cadence), and provides a concrete example of input and output, distinguishing it from siblings like audit_copy.

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 cadence and per-touch purpose are the question. Not for the wording of any single message (audit_copy).' This provides a clear when-to-use and when-not-to-use directive, naming an alternative sibling tool.

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 toolsInspect
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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