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Moltline Outbound Engine

by com.moltlinestudio

Subject Line Scorer

subject_line_scorer
Read-onlyIdempotent

Score and rank up to 20 email subject lines, best first. FREE.

Scores 0-100 on length, spam triggers, caps, personalization merge fields, and curiosity cues. Typical input {"subjects": ["Quick question about {{company}}", "ACT NOW!!!"]} returns {"ranked": [{"subject": ..., "score": 92, "notes": ["personalized (+)", "question format"]}, ...]}.

Use when several subject lines need ranking against deliverability and curiosity signals. Not for article headlines, which the creator server's headline_analyzer ranks, and not for message bodies (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
subjectsYesList of candidate subject lines as plain strings; only the first 20 are scored.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.2/5.0
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 goes further by detailing error behavior ('never raises a protocol error — returns error object') and affirming idempotency with retry guidance. This adds value beyond the 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 well-structured with front-loaded purpose, followed by scoring details, example, use cases, exclusions, error handling, and idempotency note. The word 'FREE' is minor fluff, but overall each sentence earns its place.

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 a single parameter, output schema exists, and annotations cover safety, the description covers everything necessary: purpose, input/output format, scoring criteria, use cases, exclusions, error handling, and idempotency. No gaps identified.

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 coverage is 100%, so the description adds limited value. It reinforces the 20-item limit and gives a typical input example, but the schema already documents the parameter adequately. Baseline score 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 clearly states the tool scores and ranks up to 20 email subject lines, best first. It explicitly differentiates from siblings audit_copy and the creator server's headline_analyzer, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use the tool ('when several subject lines need ranking against deliverability and curiosity signals') and provides explicit exclusions for article headlines and message bodies. However, it could also mention when not to use it relative to other sibling tools like utm_builder or sequence_planner.

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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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.

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