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update_meta_ad_budget

Change the daily budget of a Meta ad set (account currency, major units; structural cap applies). Moves real money, so it always requires the human — agents cannot change budgets. Use when the user explicitly asks to raise or lower spend on a campaign.

[outbound-tier — EVERY call needs a manager's approval (per-send human rail): each request queues its own approval card and sends exactly once on approve. There is no standing grant for this tool.]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
adset_idYesNumeric ad set id
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.
daily_budgetYesNew daily budget, account currency major units
ad_account_idNoOptional — for currency resolution when several accounts exist

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description fully discloses that the tool moves real money, always requires human approval, and every call needs per-send manager approval queuing its own approval card. This is rich behavioral context beyond what annotations would provide.

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, front-loaded with purpose, then approval details. It is concise but could be slightly tighter; every sentence earns its place. Minor redundancy in the approval block.

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 no output schema and no annotations, the description covers purpose, behavioral constraints, and approval process well. It mentions structural cap but does not explain it, and lacks return value or error details. Still fairly complete for a mutation tool.

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 baseline is 3. The description does not add additional meaning beyond the schema; it only reiterates 'account currency, major units' already in the schema. No extra semantic value for parameters.

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 'Change the daily budget of a Meta ad set', which is a specific verb+resource. It adds clarifying details like account currency, major units, and structural cap, and distinguishes it from siblings like set_meta_ad_status by focusing on budget changes.

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 explicitly says 'Use when the user explicitly asks to raise or lower spend on a campaign' and notes that agents cannot change budgets, providing clear when-to-use and when-not-to-use guidance. It lacks mention of specific sibling alternatives but effectively sets usage context.

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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