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Glama

Moltline Outbound Engine

Audit Copy

audit_copy
Read-onlyIdempotent

Audit outreach copy for spam triggers and deliverability risks. FREE.

Checks spam-trigger phrases, length, structure, caps, links, and personalization signals. Typical input {"subject": "Quick question", "body": ""} returns {"score": 0-100, "findings": ["Spam-trigger phrases: ...", "Long for cold outreach (200 words; aim 50-125)"], "note": "..."}.

Use on the body of an outreach message. Not for the subject line alone (subject_line_scorer) and not for the send schedule (sequence_planner). 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
bodyNoThe email body text to audit.
subjectNoThe email subject line; may be empty when auditing body copy alone.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

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, destructiveHint=false. The description adds critical context beyond that: 'this tool never raises a protocol error — it returns an error object', the exact error format, and the safety of retry after correction. It also discloses that it's free ('FREE').

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 tightly packed: first sentence declares purpose, second lists checks, third shows example input/output, fourth clarifies proper use vs alternatives and error behavior. Every sentence earns its place. Front-loaded with key info.

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?

The description covers all needed context: what it does, what it checks, example I/O, when to use, when not to, alternative tools, error handling behavior, and safety to retry. With output schema present and annotations rich, the description perfectly fills any remaining 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 coverage is 100%, so the description need not elaborate on each parameter. The description does add a typical usage example showing format and structure, which helps clarify usage but is not essential given the schema already fully describes both parameters. 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 states a specific verb ('Audit') and resource ('outreach copy for spam triggers and deliverability risks'), and clearly distinguishes from siblings like 'subject_line_scorer' and 'sequence_planner' by saying 'Not for the subject line alone' and 'not for the send schedule'.

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 tells when to use ('Use on the body of an outreach message'), when not to use ('Not for the subject line alone... not for the send schedule'), and names specific alternative siblings ('subject_line_scorer', 'sequence_planner'). It also gives a typical input example.

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