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by com.emailchaser
OverviewDiscussionsAdmin

Edit AI reply draft

update_reply_draft
Idempotent

Edits the subject and/or body of an AI reply draft before it goes out. Provide at least one field; provided fields must be non-empty. This never changes the draft's status or sends anything: the draft stays a draft until it is sent. Emails that are not AI reply drafts (sent or scheduled emails, inbound replies, sequence templates) are refused. API reference: https://www.emailchaser.com/docs/api-reference/replies

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": {
      "id": "<id>"
    },
    "name": "update_reply_draft"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesThe numeric reply draft ID (from list_reply_drafts)
bodyNoNew body
subjectNoNew subject line

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Beyond the annotations (readOnlyHint=false, idempotent=true, destructive=false), the description discloses the key behavioral fact that status is untouched and nothing is sent, plus the refusal behavior for non-draft targets. That is real added value an agent could not infer from the annotations. It does not spell out what happens to omitted fields, which would have made it a 5.

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 text is front-loaded with the action and the constraints, and every sentence carries information about scope, safety, or validation. The trailing documentation URL is mildly extraneous but does not disrupt the structure.

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?

For a three-parameter, single-object mutation with full schema coverage, no output schema, and annotations already declaring safety, the description covers action, validation, and failure modes. Nothing essential is missing for correct invocation.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds a cross-parameter constraint the schema cannot express: at least one of subject/body must be supplied and values must be non-empty (the schema marks only id as required). That meaningfully reduces the chance of an empty-update call.

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 opens with a specific verb and resource ('Edits the subject and/or body of an AI reply draft') and explicitly scopes it to editing before sending, which cleanly separates it from the send_reply_draft sibling. An agent can identify the operation and target object without opening the schema.

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?

It gives clear preconditions ('Provide at least one field; provided fields must be non-empty') and a hard exclusion ('Emails that are not AI reply drafts ... are refused'), which tells the agent both when this applies and when it will fail. It stops short of naming a sibling alternative explicitly (e.g. send_reply_draft for sending), so it is strong context rather than full routing guidance.

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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