Moltline Outbound Engine

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

Name	Required	Description	Default
`subjects`	Yes	List of candidate subject lines as plain strings; only the first 20 are scored.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.9/5.0

Behavior5/5

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

Beyond annotations (readOnly, idempotent), the description adds that errors return a structured error message instead of protocol errors, and details scoring factors (length, spam, caps, personalization, curiosity). This extra context is valuable for safe invocation.

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 compact (four sentences) and front-loaded with the main action and key perk (FREE). Every sentence adds essential information without redundancy. Perfectly balanced.

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 simplicity (one parameter, output schema exists), the description covers purpose, usage scope, scoring criteria, error behavior, idempotency, and alternative tools. No obvious gaps remain; the agent has all needed context.

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 already fully describes the single parameter with 100% coverage. The description reinforces the limit (first 20) and provides a concrete example, which adds clarity but does not significantly extend beyond the schema. Baseline 3, slight improvement for utility example.

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 email subject lines, specifies a limit of 20, and orders results best first. It also distinguishes from siblings like audit_copy and 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 Guidelines5/5

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

Explicitly says to use when ranking subject lines for deliverability and curiosity, and explicitly excludes article headlines (headline_analyzer) and message bodies (audit_copy). Also provides error handling and retry guidance, covering when to retry safely.

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

A4.7/5.0

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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