Skip to main content
Glama
closermethod

Outbound Engine MCP

by closermethod

audit_cold_message

Audit a cold message draft against outreach rules for compliance, returning PASS/FAIL with specific violations and a rewrite recipe.

Instructions

Audit a drafted cold message against the engine rules: no money/rates, no identity-first opener, specific hook required, soft ask only, under ~90 words, one ask. Returns PASS/FAIL with named violations and a rewrite recipe.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYesThe full draft cold message text
target_typeNoOptional target type for pack-specific reminders
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the return behavior (PASS/FAIL with named violations and rewrite recipe) and lists the specific rules it enforces. Though it doesn't explicitly state that it modifies nothing, the term 'audit' implies a read-only operation.

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 a single, well-structured sentence that front-loads the core action, then lists the key rules and return format. No filler words or redundant phrases.

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 that there is no output schema, the description adequately covers the return format and criteria. It explains what inputs are expected (a drafted message) and what to expect as output, making the tool's usage fully self-contained despite the optional target_type parameter not being mentioned in the description.

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%, with both parameters already described in the input schema. The description adds no additional parameter-level detail, which is acceptable given the schema's completeness; the rule list is about message content rather than parameter usage.

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 identifies the tool's function with a specific verb ('audit') and resource ('a drafted cold message'). It enumerates the exact rules checked, distinguishing it from sibling tools like structure_cold_pitch or detect_red_flags.

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 implies usage context: it is for auditing an already-drafted cold message, while siblings handle other stages (replying, pricing, structuring). It does not explicitly mention when not to use it or name alternatives, but the context is clear enough for an agent to decide.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/closermethod/outbound-engine-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server