coda_whoamiRetrieve the current API token owner's name, email, and scopes to verify token validity and confirm expected Coda permissions.
Get information about the current API token owner.
Returns the user's name, email, and token scopes. Use this to verify that the API token is valid and has the expected permissions. If this returns an error, the token is invalid or expired.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.12.1Output schema / (root)Previous value: -{
- "properties": {
- "result": {
- "type": "string"
- }
- },
- "required": [
- "result"
- ],
- "type": "object",
- "x-fastmcp-wrap-result": true
-}New value: +nullv0.4.14Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it read-only, idempotent, and open-world, and the description adds concrete behavioral context beyond them: the returned identity fields and the meaning of an error response. This tells an agent what success and failure look like without an output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four short sentences, front-loaded with the core action, then return values, then usage and error semantics. Every sentence adds distinct information with no repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description correctly supplies the return shape (name, email, token scopes) and error meaning. Annotations cover safety and network traits, so nothing needed for correct invocation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so there are no parameter semantics to document. Per the rubric, a zero-parameter tool receives a baseline of 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb and resource ('Get information about the current API token owner') and enumerates the returned fields. This makes it unmistakable and distinct from all sibling tools, which operate on docs, pages, rows, permissions, and analytics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It states the exact purpose ('Use this to verify that the API token is valid and has the expected permissions') and interprets an error as an invalid or expired token. No alternative tool serves this identity-verification function, so the lack of a named sibling alternative is not a gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.