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Create content pack

create_pack

Create a finished multi-format content pack (LinkedIn post, X thread, newsletter section, SEO article, summary) from a brief, bullets, draft, transcript, or URL, in the caller's brand voice. Returns every piece with its visible quality gate (voice match, factual flags, platform fit).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesThe source: brief text, bullet list, draft, transcript, or URL (for input_type=url)
formatsNoSubset of formats to generate. Omit for all five.
input_typeYesWhat the content is: brief | bullets | draft | transcript | url
voice_profile_idNoVoice profile id from list_voice_profiles. Omit for the default voice.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare write (readOnlyHint=false), non-idempotent, non-destructive, open-world. The description adds valuable context beyond them: the completed pack carries a visible quality gate (voice match, factual flags, platform fit). However, it omits whether the call returns synchronously or hands off to a job (the get_job_status sibling strongly implies async), plus any cost or failure behavior, so it only partly fills the gap.

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?

A single dense sentence, front-loaded with the verb and the deliverable, then the accepted sources. No filler or repetition of the schema. It is slightly overpacked (output list plus quality-gate parenthetical) but earns its length.

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, describing the returns (each piece plus its quality gate) is the right move and it does so. But for a write, open-world, non-idempotent tool it leaves out sync-vs-async execution, what happens on partial format failure, and how it relates to get_job_status and the two specialized create siblings, leaving the agent to infer key operational behavior.

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 schema already defines content, input_type, formats, and voice_profile_id semantics (including the list_voice_profiles reference). The description adds marginal meaning by tying voice_profile_id to 'the caller's brand voice,' but no syntax, defaults, or format-selection guidance beyond the schema. Baseline 3 applies.

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 (create) and resource (multi-format content pack), enumerates the exact outputs (LinkedIn post, X thread, newsletter section, SEO article, summary) and the accepted input forms. This is far more specific than a tautology. It stops short of 5 because it never contrasts itself with the sibling tools create_from_transcript and create_from_url, which overlap heavily with two of the listed input types.

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

Usage Guidelines2/5

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

There is no when-to-use versus when-not-to-use guidance. The description lists accepted inputs (transcript, URL) that are covered by dedicated siblings (create_from_transcript, create_from_url) without telling the agent which tool to prefer, and it never mentions get_job_status despite the write/open-world annotations implying a long-running job. Only implied usage is available.

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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