freedom-mcp

segment_leads

Organize, select, or clear a lead segment on the Leads tab by its exact source tag (e.g. 'csv:apc-cch-2024'). Validates the tag against the company's live segment tags and returns the exact-token filter plus a server-computed lead count (excluding do-not-contact, archived, and test leads). Read-only: the Leads tab applies the action; this tool changes no data and CANNOT enroll anyone. To enroll the segment, call enroll_by_segment — do not ask the operator to click Enroll or paste emails. Use when the operator wants to focus the Leads tab on one segment or event — group it, select all its leads for enrollment, or clear that selection.

Routing: CRM/sales → select or organize leads by segment/event tag → use this

Input Schema

TableJSON Schema

Name	Required	Description
`action`	Yes	'organize' = group Leads tab by this segment; 'select' = select all leads in it; 'clear' = clear that selection.
`companyId`	Yes	FreedomOS company id to act within (you must be a member). Required for company-scoped tools.
`segment_tag`	Yes	Exact segment tag token from crm_leads.source, e.g. 'csv:apc-cch-2024'. No substring matching — must match a live tag exactly.

TDQS

A4.6/5.0

Behavior5/5

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

The description explicitly says 'Read-only', 'changes no data', 'CANNOT enroll anyone', and describes validation against live segment tags. It also discloses return behavior (exact-token filter and server-computed lead count with exclusions for do-not-contact, archived, and test leads). With no annotations, this fully compensates.

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 front-loaded with primary purpose, packs rich behavioral details into a few sentences, and ends with a concise routing hint. It is slightly long but every sentence contributes meaningful information.

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?

Despite lacking an output schema, the description explains what the tool returns (filter + count) and important filtering exclusions. It also documents side-effect-free behavior and the intended workflow context. This is fully sufficient for an agent to invoke it 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?

Schema coverage is 100%, with detailed descriptions for all three parameters, including enum meanings and exact-match requirements. The description adds an example tag and reinforces the exact-token requirement, but does not introduce new param-level semantics beyond what the schema already provides.

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 set ('Organize, select, or clear') plus resource ('lead segment') and scope ('Leads tab', 'exact source tag'). It clearly distinguishes itself from the enrollment sibling by explicitly directing users to enroll_by_segment, and includes a routing line.

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?

Explicitly states when to use ('Use when the operator wants to focus the Leads tab on one segment or event...') and when not to use ('To enroll the segment, call enroll_by_segment — do not ask the operator to click Enroll or paste emails'). This provides a clear alternative and exclusion.

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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