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create_pipeline

Create a new content pipeline to automate content creation. Use when user says "set up a changelog", "create a newsletter pipeline", "send team updates", "automate my X posts", or describes input→output automation. Output types: changelog (public product updates), team_update (internal team email via Freedom OS), report (email to specific recipients), customer_newsletter (external customers - requires user Email MCP like Mailchimp), social_post (x/linkedin/instagram/facebook/threads via the gated publish owner).

[write-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.]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesName for the pipeline (e.g., "Weekly Newsletter", "GitHub to Changelog")
inputsNoInput sources to listen to
outputYesOutput type: changelog (public), team_update (internal team email), report (specific recipients), customer_newsletter (external - requires Email MCP), social_post (x/linkedin/instagram/facebook/threads)
personaNoMarketing persona to use (alex, elon, or custom ID)
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description must disclose behavior. It explains the write-tier approval flow (first use may require manager approval, from-now-on vs just-once). It also mentions that social_post requires the 'gated publish owner.' However, it does not detail what happens immediately after creation (e.g., whether the pipeline is active, any default settings).

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?

The description is mostly concise and front-loaded with the main action. It contains a long list of output types and a parenthetical approval note, but every sentence adds value. Minor redundancy in the output list could be tightened.

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?

Given the tool has 5 parameters (including nested inputs) and no output schema, the description covers inputs and outputs adequately but lacks details on the pipeline's lifecycle post-creation (e.g., whether it is immediately active, how to manage it later). The approval flow is a helpful addition, but overall completeness is moderate.

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

Parameters4/5

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

Schema coverage is 100%, so the description's added value is considered. It expands on the output enum (e.g., linking customer_newsletter to Email MCP, social_post to gated publish owner) and clarifies the approval implications. This exceeds the schema descriptions.

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?

The description clearly states the tool's purpose: 'Create a new content pipeline to automate content creation.' It lists specific use cases (e.g., 'set up a changelog', 'create a newsletter pipeline') and output types, distinguishing it from siblings like update_pipeline or list_pipelines.

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

Usage Guidelines5/5

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

The description explicitly tells when to use the tool: 'Use when user says...' and explains output types with conditions (e.g., 'customer_newsletter... requires user Email MCP'). It also includes the write-tier approval behavior, guiding the agent on authorization needs.

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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TDQS

A3.6/5.0
Disambiguation4/5

The tool set is heavily disambiguated by detailed routing descriptions, domain prefixes, and lifecycle verbs, so most tools have a clear intended purpose. However, at 297 tools there are still close pairs and overlapping decision surfaces (e.g., approval workflows, 'what should I work on' readers, multiple finance/ads readers) that require careful description reading to avoid misselection.

Naming Consistency4/5

Naming is predominantly consistent snake_case verb_noun with strong domain prefixes like shopify_, x_, posthog_, and list_/create_/update_ patterns. Minor inconsistencies exist, such as several collection-returning tools using get_ (get_team_members, get_icps, get_okrs) instead of list_, and some generate_ vs create_ vs draft_ verbs, but the pattern is still predictable overall.

Tool Count1/5

297 tools is an extreme outlier and far beyond a usable MCP tool surface. Even a large suite has no justification for this count in one server; the agent would struggle to select among hundreds of similarly descriptive tools, and the natural 3-15 tool range is exceeded by nearly 20x.

Completeness4/5

The individual domains represented — OKRs, CRM/leads, Shopify, content pipelines, ads, PostHog, team hiring, knowledge, finance, and session management — are covered remarkably well with full lifecycle patterns. Minor gaps exist, such as no full deal CRUD, no delete for several Google/Shopify artifacts, and some analytical surfaces being read-heavy, but most workflows can be completed without dead ends.

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