@instantreply/mcp

validate_template_draft

Read-only

Validate a WhatsApp template objective before creation. Get policy risk, category prediction, issues, and UTILITY coaching.

Instructions

Validate a plain-language WhatsApp template objective before creating it. Returns policy risk, likely category, issues, and UTILITY coaching.

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": {
      "objective": "<objective>"
    },
    "name": "validate_template_draft"
  }
}

Input Schema

Name	Required	Description	Default
`name`	No
`language`	No
`objective`	Yes
`variables`	No
`categoryHint`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Sep 12, 2026

TDQS

A3.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description is consistent with them. Beyond that it discloses the shape of the response (policy risk, likely category, issues, UTILITY coaching), which tells the agent this is a non-mutating advisory check rather than an enforcement action.

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: the purpose and its timing constraint come first, the return payload second. Nothing is redundant and no sentence fails to earn its place.

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

Completeness3/5

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

With no output schema, the description correctly summarizes what comes back, which is a real strength. Against five parameters and an enum, though, the input side is under-specified, so the definition is only adequate for calling the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across five parameters, so the description must carry the burden and it does not. It clarifies only 'objective' (plain-language, free text) and gestures at category via 'likely category'; name, language, variables, and categoryHint are left entirely undocumented.

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?

States a specific verb (validate) and resource (a plain-language WhatsApp template objective), and the phrase 'before creating it' implicitly separates it from submit_template/submit_stored_template. It never names a sibling, so the differentiation rests on the reader inferring that this is the pre-flight check versus the structured-template validators.

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

Usage Guidelines3/5

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

'before creating it' gives an implied usage window, which is more than most sibling tools offer. However, no alternative is named (validate_template, submit_template) and there are no when-not conditions, so the agent must infer the workflow position.

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