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Ingest voice corpus

ingest_voice_corpus
Destructive

Build or refresh the company's voice profile from REAL writing. Use this when the operator wants agents to learn their voice from their actual work — pass a URL to their blog / newsletter / posts (or an admired creator's page), or paste sample text. The system fetches it safely, distills the STYLE (cadence, word choice, argument-building — never faith substance), and merges it into the voice profile all drafting agents ground on. For any operator/brand setting up or improving how their content sounds.

Routing: Prefer the operator's own writing as the source; ingesting a page teaches STYLE only, never that page's claims — this UPDATES the shared grounding profile.

[sensitive-tier — first use may require a manager's approval; a from-now-on approval makes future calls seamless, a just-once approval re-asks next time. Call it on the first clear ask; the card is the yes — do not re-ask in chat.]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textNoA pasted writing sample to learn from.
urlsNoPublic URLs to learn the voice from — the operator's own writing, or admired creators' pages. Fetched HTTPS-only, SSRF-guarded, no crawling.
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.
faith_heavyNoMark the sources faith-heavy (style learned, faith substance excluded).
subject_kindNoWhose voice — 'person' (personal brand) or 'brand'. Defaults to the existing profile's subject if omitted.
subject_nameNoThe person or brand name.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / subject_kind / description
      Previous value: -"Whose voice — 'person' (personal brand) or 'brand'."New value: +"Whose voice — 'person' (personal brand) or 'brand'. Defaults to the existing profile's subject if omitted."
    • changedInput schema / properties / urls / description
      Previous value: -"Public URLs to learn the voice from (SSRF-guarded fetch)."New value: +"Public URLs to learn the voice from — the operator's own writing, or admired creators' pages. Fetched HTTPS-only, SSRF-guarded, no crawling."
  2. First observed

TDQS

A3.8/5.0
Behavior4/5

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

With destructiveHint=true, the description goes beyond annotations by explaining the update behavior: 'this UPDATES the shared grounding profile' and 'merges it into the voice profile.' It also scopes what is learned ('STYLE only, never faith substance') and notes safe fetch behavior. No contradiction with annotations; the description is consistent with a mutating, non-idempotent operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, but it is long and somewhat repetitive: 'For any operator/brand setting up or improving how their content sounds' restates earlier content, and the sensitive-tier approval paragraph adds valuable but lengthy operational detail. Every sentence has some use, but the description could be tightened.

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?

Despite no output schema, the description covers the main call scenarios, approval requirements, source types, style-vs-substance behavior, and side effects on the shared grounding profile. It does not clarify whether text and urls can be combined or what happens if both are omitted, but the overall guidance is sufficient for correct invocation in most cases.

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%, so the baseline is 3. The description adds some concrete context by mentioning URLs to blogs/newsletters/posts and pasted sample text, but it does not materially clarify parameter combinations, defaults, or constraints beyond what the schema already documents.

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 uses a specific verb and resource: 'Build or refresh the company's voice profile from REAL writing.' It clearly explains what the tool ingests and what it produces. It does not explicitly name or differentiate from sibling tools like update_voice_profile or get_voice_profile, so it stops short of a 5.

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?

The description gives explicit when-to-use guidance: 'Use this when the operator wants agents to learn their voice from their actual work.' It also provides routing preference ('Prefer the operator's own writing as the source') and approval-handling rules. It lacks an explicit when-not-to-use or named alternative, so it does not reach 5.

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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