freedom-mcp

link_agent_okrs

Link an agent to one or more company OKRs. This creates a live connection between the agent and the company objectives they are working toward. Their system prompt will include live OKR context (objectives + key results with progress).

[write-tier — first use may require a manager's approval; a from-now-on approval makes future calls seamless, a just-once approval re-asks next time.]

Input Schema

TableJSON Schema

Name	Required	Description
`append`	No	If true, add to existing linked OKRs. If false (default), replace all linked OKRs.
`okr_ids`	Yes	Array of OKR UUIDs to link to this agent
`agent_id`	No	UUID of the agent to link OKRs to
`companyId`	Yes	FreedomOS company id to act within (you must be a member). Required for company-scoped tools.
`agent_name`	No	Name of the agent (used to look up agent_id if not provided)

TDQS

A3.8/5.0

Behavior4/5

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

With no annotations provided, the description effectively discloses behavioral traits: the live connection effect, inclusion of OKR context in system prompt, and the write-tier approval workflow (manager approval, approval types). It adds value beyond basic mutation disclosure.

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 clear sentences plus a useful bracketed note. It is front-loaded with the core purpose and action. The note about approval could be integrated, but overall it's efficient and scannable.

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

Completeness3/5

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

For a tool with 5 parameters, no output schema, and no annotations, the description covers purpose and approval but lacks details on parameter conflict resolution (e.g., agent_id vs. agent_name) and what the tool returns. It is adequate for basic understanding but not comprehensive.

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%, so baseline 3 is appropriate. The description adds minimal extra meaning: it explains the overall purpose but not parameter interactions (e.g., agent_id vs. agent_name conflict). The append parameter is already well-defined in schema.

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 the verb (link), the resource (agent to OKRs), and the specific effect (creates a live connection; system prompt includes live OKR context). It distinguishes this tool from siblings like get_okrs or update_agent by focusing on the linking function.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when an agent needs to be aware of company OKRs, but does not explicitly state when to use vs. alternatives (e.g., get_okrs for viewing, or other agent modification tools). The approval note hints at sensitivity but no direct when-not or alternative guidance.

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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