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invoke_integration

Execute a tool on a connected MCP integration. First use list_integrations to discover available tools.

[outbound-tier — EVERY call needs a manager's approval (per-send human rail): each request queues its own approval card and sends exactly once on approve. There is no standing grant for this tool.]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argumentsNoArguments to pass to the tool
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.
tool_nameYesName of the tool to execute on the integration
integration_nameYesName of the integration (e.g., "stripe", "calendar")

TDQS

A4.2/5.0
Behavior4/5

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

The description discloses important behavioral traits: each request queues an approval card and sends exactly once on approve, and there is no standing grant. This goes beyond what annotations (none provided) would offer, giving the agent crucial context about the tool's execution model and safety profile.

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 extremely concise: two sentences that cover purpose, prerequisite, and behavioral constraint. No wasted words; every sentence adds value. It is front-loaded with the core action.

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 that the tool has nested objects and no output schema, the description covers the essential aspects: what it does, the prerequisite (list_integrations), and the approval model. It is mostly complete for a straightforward execution tool, though it could mention expected response or error behavior.

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 four parameters with descriptions. The description does not add extra meaning beyond the schema, such as valid values or format constraints. A baseline score of 3 is appropriate since the schema handles parameter semantics adequately.

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-resource relationship ('Execute a tool on a connected MCP integration') and distinguishes from siblings by referencing the prerequisite tool list_integrations, which is a sibling. This helps the agent understand what the tool does and how it relates to other tools.

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 explicitly advises to first use list_integrations to discover available tools, providing clear context for when to use this tool. It also details the approval requirement (every call needs manager approval, no standing grant), which helps in understanding usage constraints. However, it does not explicitly state when not to use this tool or list alternatives.

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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