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Map bodies (Hook Studio step 3)

bodies_map

[writes flayr data · write scope] Maps library clips, Shopify products, features or texts to draft bodies (what each shows and proves) so hooks can lead into them. Charges Embers once per call (refunded when nothing usable comes back). Needs the Pro plan or higher. (Wraps POST /api/v2/hook-studio/bodies/map.)

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "bodies_map"
  }
}

Input Schema

NameRequiredDescriptionDefault
textsNo
brandIdNoA brand id from GET /api/v2/brands. Required for an account-wide key; a brand-bound key may omit it.
featuresNo
productGidsNo
includeCollabNo
libraryContentIdsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

Annotations only declare the generic write profile; the description adds real behavioral facts an agent needs: it writes flayr data under `write` scope, charges Embers per call, refunds when nothing usable returns, and requires Pro. Not full marks because it omits what happens on repeated calls (non-idempotent per annotations, silent extra charges) and whether partial/empty results still bill.

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?

Dense but front-loaded: the scope/write marker and the core mapping statement come first, then cost and plan constraints. Every sentence carries information; the endpoint-wrapper note is low value but conventional.

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 billed mutation with no output schema and six unrequired params, the definition covers the essentials an agent must know before calling: scope, cost, refund behavior, plan gate. The gap is return-shape expectations (what a mapped body list looks like) and whether the parameter arrays are mutually exclusive.

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 17% — only brandId is documented — so the description must carry the load. It maps the four source categories to the corresponding array parameters in spirit (clips→libraryContentIds, products→productGids, features, texts), but never names them, and leaves includeCollab and the combinability rules entirely unexplained.

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?

Specific verb 'Maps' plus explicit resource types (library clips, Shopify products, features, texts) and an output object ('draft bodies'), with a clarifying gloss of what a body is. It does not name a sibling to contrast with, though the title's 'Hook Studio step 3' hints at pipeline position; the description body itself never links to hooks_generate.

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?

Prerequisites are well covered (write scope, Pro plan or higher, Ember cost), and 'so hooks can lead into them' implies it follows hook generation. But there is no explicit when-to-use vs alternative, no when-not, and no guidance on whether the four input types are alternatives or combinable.

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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