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create_x_ad_draft

Create an X (Twitter) ads draft — campaign + line item — ALL in PAUSED state, spending nothing. Use when the user wants to set up or draft an X ad. Activation is a separate human-approved step (set_x_ad_status). Distinct from create_meta_ad_draft.

[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.]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bidNoOptional bid in major units (default 1)
countryNoISO-2 country for location targeting, default US
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.
objectiveNoLine-item objective, default WEBSITE_CLICKS
daily_budgetYesDaily budget in the account currency, major units (e.g. 25 = 25 USD/day)
ad_account_idNoAds account id. Optional when the connection has exactly one.
campaign_nameYesCampaign name, e.g. "PCAI cold traffic v1"
funding_instrument_idNoPayment method id. Optional when the account has exactly one.

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses that the draft is created in PAUSED state and spends nothing, and it surfaces the sensitive-tier approval requirement (manager approval on first use, with options for just-once or from-now-on). It does not mention potential side effects like whether it overwrites existing drafts or what happens on failure, but the key safety and authorization behaviors are clearly stated.

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 two paragraphs. The first sentence conveys the core purpose and state, and the second paragraph covers the approval nuance. It is front-loaded with the most important information and avoids redundancy, though the sensitive-tier note could be more compact. Overall, it is efficient and readable.

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?

Given the tool creates a campaign and line item, the description covers the active state (paused, no spend) and the approval step. It does not describe return values (no output schema exists), but that is not strictly required. The essential prerequisites like companyId and ad_account_id are documented in the schema. The description is sufficiently complete for an agent to call it correctly without ambiguity.

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 100% — every parameter has a description in the input schema. The description does not add extra meaning to the parameters; it only mentions 'campaign + line item' which loosely maps to campaign_name and objective, but that is already implied by the schema. Thus, the baseline of 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?

The description opens with a specific verb and resource: 'Create an X (Twitter) ads draft — campaign + line item'. It clearly states the scope (campaign + line item) and the crucial state (PAUSED, spending nothing). It also distinguishes itself from the sibling create_meta_ad_draft, so an agent can immediately tell this is the X-specific draft tool.

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?

It explicitly says 'Use when the user wants to set up or draft an X ad' and clarifies that activation is a separate human-approved step via set_x_ad_status. It also notes that it is distinct from create_meta_ad_draft, directing the agent toward the right sibling for Meta ads. This gives clear when-to-use and when-not-to-use guidance.

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.

Resources