Pipefire email deliverability tools

Cold email checker

check_cold_email

Read-onlyIdempotent

Score a cold email (subject and body) out of 10 against the rules Pipefire checks its own emails with: length, reading level, the ask, subject line, and spam-filter wording. Returns each issue with why it matters and how to fix it.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "subject": "<subject>",
      "body": "<body>"
    },
    "name": "check_cold_email"
  }
}

Input Schema

Name	Required	Description
`body`	Yes
`kind`	No	Which email in the sequence. Default first.
`subject`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 20, 2026

TDQS

A3.6/5.0

Behavior4/5

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

Annotations already declare this as a safe, idempotent, non-destructive read. The description adds useful behavior beyond that: it discloses the scoring rubric and, importantly, the return shape — each issue with why it matters and how to fix it — which no structured field provides.

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?

Two tight sentences with the verb and resource front-loaded, then the rubric, then the return contract. No filler and nothing that could be cut without losing information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the burden of explaining returns and does so (issues plus rationale and fix), and the annotation set covers the safety profile. The only gap is the absent guidance on sequence 'kind' handling and when this tool is preferable to its siblings.

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 only 33%, but the description does cover the two required parameters by naming 'subject and body'. It says nothing about the 'kind' parameter (first/follow-up/last), though the schema documents that itself. The rubric list refers to output checks rather than adding parameter-level meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource — score a cold email (subject and body) out of 10 — and enumerates the rubric dimensions (length, reading level, the ask, subject line, spam wording). It implicitly separates itself from test_subject_line by covering both subject and body, but never names a sibling tool outright.

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

Usage Guidelines2/5

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

There is no explicit when-to-use or when-not-to-use guidance, and no routing to alternatives such as test_subject_line or analyze_email_headers. Usage is only implied by the tool's subject matter.

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

All Pipefire email deliverability tools tools Inspect

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