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Copilot: plan a campaign

copilot_plan

Given a company website, the honest AI SDR builds an ideal-customer-profile (ICP) and a suggested cold-email sequence. Read-only — creates nothing. Returns the ICP (personas, titles, industries, suggested Sales Navigator keywords) and a draft sequence you can review or pass to copilot_launch.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextNoOptional extra context, e.g. 'we sell to dental clinics in the US'
websiteYesThe company website to analyze, e.g. https://acme.com
descriptionNoOptional: what the company sells and to whom, in its own words. When given, the plan is built from it and the website is not read. Send it when copilot_plan answers that the website shows a placeholder page.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / description
      Added value: +{
      +  "description": "Optional: what the company sells and to whom, in its own words. When given, the plan is built from it and the website is not read. Send it when copilot_plan answers that the website shows a placeholder page.",
      +  "type": "string"
      +}
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations only declare openWorldHint and destructiveHint, so 'Read-only — creates nothing' adds real safety context (no readOnlyHint is present). With no output schema, describing the returned payload (personas, titles, industries, keywords, draft sequence) is genuine added value; only auth/rate-limit details are absent.

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 capability and its read-only nature are front-loaded, and every clause (scope, safety, output contents, next step) earns its place.

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?

For a 3-param, non-destructive planning tool with no output schema, the description covers inputs, outputs, safety, and the downstream handoff. It omits any prerequisite or failure context (e.g., what happens if the site cannot be analyzed), keeping it just short of fully complete.

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 description coverage is 100% and each parameter is well documented there, including the 'description' fallback for placeholder pages. The description adds no parameter meaning beyond the schema, so the baseline 3 applies.

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?

States a specific verb and resource: given a website, it builds an ICP and a draft cold-email sequence. It also names the sibling it hands off to (copilot_launch), so an agent can distinguish it from create_icp/plan_autopilot without opening a 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?

Clearly positions the tool as a planning step whose output is reviewed or passed to copilot_launch, giving real workflow context. It never states when-not to use it (e.g., versus plan_autopilot or create_icp), so the guidance is strong but not exhaustive.

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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