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freedom-mcp

by com.getfreedomos

analyze_team_needs

Gather comprehensive team and company context for talent strategy analysis. Returns current team composition, growth signals, capability gaps, and integration status. Use when the user asks "what roles am I missing?", "who should I hire next?", "analyze my team", or "what gaps does my team have?". YOU are the strategist — this tool gathers the data, YOU provide the PhD-level talent recommendations.

Input Schema

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

TDQS

A3.6/5.0
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 tool as a data-gathering operation (reads team context) and lists outputs, implying a read-only, non-destructive action. However, it does not disclose authorization details beyond being a member, rate limits, or response format specifics.

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 sentences plus a short meta-instruction, all front-loaded with purpose and usage. No wasted words; the meta-instruction adds value for the agent's role. Slightly above average due to efficiency.

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 one required parameter, 100% schema coverage, and no output schema, the description adequately explains what the tool returns (composition, gaps, integration status) and provides usage examples. It is complete enough for an agent to understand and invoke the tool correctly.

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?

The single parameter 'companyId' has full schema coverage (100%) with a clear description. The tool description adds no additional meaning beyond what the schema already provides, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it gathers team/company context for talent strategy analysis and lists specific returns (team composition, growth signals, capability gaps, integration status). It specifies a verb (gather) and resource (team needs), but does not explicitly differentiate from sibling tools like get_team_roster or get_team_members.

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?

Explicitly lists example user queries that trigger this tool (e.g., 'what roles am I missing?') and clarifies that the tool gathers data while the agent provides recommendations. Lacks explicit when-not-to-use or alternative tool mentions, but the context is clear.

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