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freedom-mcp

by com.getfreedomos

get_ads_performance

Get Meta ads results: spend, impressions, clicks, CTR, CPC, CPM, reach, conversions (actions), cost per action, and purchase ROAS — at account, campaign, adset, or ad level over a chosen window. Use when the user asks how their Facebook/Instagram ads are doing, what they spent, or what it returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
levelNoAggregation level: 'account', 'campaign' (default), 'adset', or 'ad'.
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.
time_rangeNoExact window: { since: 'YYYY-MM-DD', until: 'YYYY-MM-DD' }. Mutually exclusive with date_preset.
campaign_idNoOptional: scope the report to one campaign (id from list_ad_campaigns).
date_presetNoReporting window preset, e.g. 'last_7d', 'last_30d' (default), 'this_month', 'lifetime'. Mutually exclusive with time_range.
ad_account_idNoAd account id (act_<digits> or bare digits). Optional when the connection has exactly one ad account.

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It describes the returned metrics but does not disclose behavioral traits such as rate limits, authentication requirements, data freshness, pagination, or error handling. For a read-only tool, this is acceptable but could be improved.

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

Conciseness5/5

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

The description is two sentences: the first lists the metrics and structure, the second gives usage context. No unnecessary words, fully front-loaded with essential information.

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?

With no output schema, the description compensates by listing the metrics. It covers the core functionality (metrics, levels, time range) and usage context. Lacks details on error conditions or permissions, but is largely complete for a read-only 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 the input schema already documents all parameters. The description adds marginal value by restating the aggregation levels ('account', 'campaign', 'adset', 'ad') and the time window concept, but does not enrich beyond what the schema provides. Baseline 3 is appropriate.

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 explicitly states the tool gets Meta ads results, lists the metrics (spend, impressions, clicks, etc.), and specifies the aggregation levels (account, campaign, adset, ad) and time window. It also distinguishes itself from sibling tools like get_page_performance or get_search_performance by focusing on ad performance.

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 clearly tells when to use the tool: 'Use when the user asks how their Facebook/Instagram ads are doing, what they spent, or what it returned.' It does not explicitly mention when not to use or provide alternatives, but the context is clear and sufficient.

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