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clerk.update_organization_metadata

Merge metadata into a Clerk organization (deep merge — existing keys are preserved unless overwritten).

Call clerk.get_connected_accounts first. Pass clerk_instance_id to target a specific connection, or omit it to use the default account.

Returns the updated organization summary.

Cost = 8 tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
organization_idYesClerk organization id (org_...) to operate on.
public_metadataNoPublic metadata to merge into the organization.
private_metadataNoPrivate metadata to merge into the organization.
clerk_instance_idNoClerk instance id (ins_...) from clerk.get_connected_accounts. Omit to use the default connected account.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
organizationNoUpdated Clerk organization summary.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full burden of behavioral transparency. It discloses deep merge semantics ('existing keys are preserved unless overwritten'), a prerequisite call ('Call clerk.get_connected_accounts first'), default account behavior, return value ('Returns the updated organization summary'), and cost ('Cost = 8 tokens'). This is exceptionally transparent.

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 three short sentences, each serving a distinct purpose: function semantics, usage prerequisites, and return/cost. There is no wasted wording, and the most critical information is front-loaded.

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?

Given the output schema exists, the description need not explain return values in detail, but it still does ('Returns the updated organization summary'). It covers merge behavior, prerequisite steps, multi-account handling, and cost. For the tool's complexity, this is complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, providing baseline 3. The description adds value by explaining the deep merge behavior for metadata parameters and clarifying how clerk_instance_id should be used ('Pass clerk_instance_id to target a specific connection, or omit it to use the default account'). While it repeats some schema info, the merge semantics go beyond the 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 tool's function: 'Merge metadata into a Clerk organization (deep merge — existing keys are preserved unless overwritten).' This is a specific verb ('merge') + resource ('Clerk organization') + a key differentiator (deep merge), distinguishing it from sister tools like update_organization or replace_user_metadata.

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 provides explicit usage context: 'Call clerk.get_connected_accounts first' and explains the clerk_instance_id parameter behavior. It does not explicitly name alternative tools or exclusions, but the purpose is clear enough given the sibling list. A 4 is appropriate for clear context without explicit when-not-to-use.

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

A4.1/5.0
Disambiguation5/5

Each tool has a distinct purpose, further clarified by group prefixes and clear descriptions. Within each group, tools perform different operations (e.g., domains.lookup vs. domains.whois vs. domains.rdap) with no ambiguity.

Naming Consistency5/5

All tools follow a consistent group.tool_name pattern using snake_case. The naming is predictable and uniformly applied across all groups.

Tool Count4/5

78 tools is high, but the server aggregates multiple distinct API domains (11 groups). Each group has a reasonable number of tools, typically under 10, with TikTok having 17. The count reflects breadth, not bloat.

Completeness5/5

Each domain's tool set covers the primary expected operations (e.g., search, details, reviews, metrics, user info). There are no obvious gaps for read-only analytical use; features like posting are likely out of scope.