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clerk.revoke_sign_in_token

Revoke a sign-in token in a connected Clerk application so it can no longer be used.

Sensitive — invalidates a high-privilege token.

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 revoked sign-in token object.

Cost = 5 tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sign_in_token_idYesClerk sign-in token id to revoke.
clerk_instance_idNoClerk instance id (ins_...) from clerk.get_connected_accounts. Omit to use the default connected account.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
sign_in_tokenNoRevoked Clerk sign-in token object from the Backend API.

Schema Changelog

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

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It explicitly warns 'Sensitive — invalidates a high-privilege token', explains the result (so it can no longer be used), and states the return value and cost. This goes well beyond just naming the operation, though it could mention reversibility or error cases.

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 compact and well-structured: a one-sentence purpose, a sensitivity warning, a usage note, a return note, and a cost note. Every line provides distinct value, and the most important information is front-loaded.

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?

For a straightforward revocation tool with an output schema and rich parameter schema, the description covers purpose, prerequisite, sensitivity, return value, and cost. It is functionally complete, though it omits potential failure scenarios or what happens if the token is already revoked. These are not critical for selection and invocation.

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 schema already documents both parameters. The description adds some context for clerk_instance_id by tying it to get_connected_accounts and 'target a specific connection', but this is largely a restatement of the schema's 'Omit to use the default connected account.' No new meaning is added for sign_in_token_id.

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 starts with a specific verb and resource: 'Revoke a sign-in token in a connected Clerk application so it can no longer be used.' It clearly states the action and the effect, distinguishing this from sibling revoke_* tools by naming the exact token type and purpose.

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 gives explicit usage context: call clerk.get_connected_accounts first and either pass clerk_instance_id for a specific connection or omit it for the default. It does not spell out when not to use it or name alternatives, but the prerequisite and parameter choice guidance are clear and actionable.

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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