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freedom-mcp

by com.getfreedomos

get_cac_strategy

THE tool for any question about this company's CAC strategy or LTV:CAC ratio — e.g. "is our CAC strategy standard or conservative?", "what's our LTV:CAC ratio?", "what's our max CAC per customer?". Returns the operator's chosen posture — aggressive (2:1), standard (3:1), conservative (4:1), or enterprise (5:1) — and the effective ratio (max CAC = average LTV ÷ ratio). The CAC strategy is NOT in company settings, profile, or financials — do not use get_company or get_financial_summary for it; this is the only tool that has it, so call it directly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses the return format (posture and ratio), explains the calculation (max CAC = average LTV ÷ ratio), and states the data is not in other tools. However, it does not explicitly state read-only behavior or discuss any side effects, but the 'get' prefix and context imply safe retrieval.

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 concise (four sentences) yet packed with valuable information: purpose, examples, return values, and disambiguation from siblings. It is well-structured and front-loaded with the primary purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description adequately explains the return values (posture and effective ratio) and the underlying logic. It covers everything needed for the agent to use the tool correctly, including the relationship between posture and ratio values.

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% for the single parameter (companyId), so the schema already documents it. The description adds no additional semantics or constraints beyond what the schema provides, meeting the baseline of 3.

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 it is 'THE tool for any question about this company's CAC strategy or LTV:CAC ratio' and provides specific example queries. It distinguishes itself from siblings by explicitly saying 'this is the only tool that has it' and lists what it returns (posture and effective ratio).

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 says not to use get_company or get_financial_summary for this data and to call this tool directly. It provides clear guidance on when to use it: for any question about CAC strategy or LTV:CAC ratio.

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