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seekrit — secrets for agents

list_members

Read-onlyIdempotent

List organization members with their public keys. The public keys are what you pass to grant_env on the LOCAL crypto plane to give a human the ability to decrypt — so call this when handing a project off to a person. Returns [{ userId, email, name, role, publicKeyJwk }]; publicKeyJwk is null for a member who has not finished key setup, and such a member cannot be granted decryption yet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
orgNoOrganization slug or id. Omit it when the credential can reach exactly one org — that org is used automatically. With several, the error names every slug you may pass; list them yourself with list_orgs.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / org / description
      Added value: +"Organization slug or id. Omit it when the credential can reach exactly one org — that org is used automatically. With several, the error names every slug you may pass; list them yourself with list_orgs."
  2. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already mark the tool as read-only and idempotent, and the description adds meaningful behavioral detail on top: the exact return shape and the critical edge case that publicKeyJwk is null for members who have not finished key setup, meaning they cannot be granted decryption. This is valuable beyond the annotations and compensates for the lack of 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the core action, then gives the practical reason to call it, then the return shape and null-key caveat. Every sentence adds information an agent needs, with no fluff or repetition of schema content.

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?

For a simple, read-only listing tool, this is complete: purpose, invocation context, return shape, and an important behavioral edge case are all covered. The schema fully documents the only parameter, and annotations cover the safety profile, so nothing critical is missing.

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?

The single optional org parameter is fully documented in the input schema, including slug-or-id semantics and multi-org error behavior. The description itself adds no parameter-level detail, so the baseline of 3 applies.

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?

States a specific verb and resource ('List organization members with their public keys') and goes beyond a generic list by tying the result to grant_env, a concrete downstream use. This clearly distinguishes it from sibling list tools like list_groups or list_invites.

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?

Gives a clear when-to-use signal: 'call this when handing a project off to a person.' It explains the purpose of the returned keys in the grant_env flow. It doesn't explicitly discuss exclusions or alternatives, but the intended context is unambiguous.

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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