brainkb_deactivate_user
(Admin) Deactivate a user's account by email.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| Yes |
(Admin) Deactivate a user's account by email.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It does disclose an authorization requirement ('Admin'), but does not elaborate on side effects such as reversibility, session invalidation, or impacts on user data. This is a minimal but present disclosure for a mutation tool.
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?
The entire description is a single, front-loaded sentence that wastes no words. It immediately states the admin scope, action, and parameter usage.
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?
For a simple one-parameter tool with no output schema and no annotations, the description provides the core purpose, authorization level, and parameter role. It doesn't cover success/failure responses, but that's not critical for such a straightforward action.
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 schema lists only 'email' with no description (0% coverage). The description clarifies that email is the identifier used to locate the account for deactivation, adding essential meaning beyond the bare schema. It could be more specific about the expected email format, but it is adequate for a single parameter.
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 uses a specific verb 'deactivate' tied to a clear resource ('user's account') and identifies the lookup method ('by email'). This clearly distinguishes it from sibling tools like brainkb_activate_user, brainkb_ban_user, and brainkb_unban_user.
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?
The '(Admin)' prefix signals that this tool is restricted to admin users, giving some usage context. However, it neither explicitly states when to use this tool over alternatives nor provides exclusion criteria for when not to use it. Usage is implied by the action name rather than explicitly guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes, such as user management (activate, ban, assign role) vs. space management (create, add member, set visibility) vs. ingest/jobs (ingest_files, job_status, recover). A few pairs like grant_capability vs. grant_role_capability are similar but descriptions clarify the target, so an agent should be able to choose correctly.
All tools are prefixed with brainkb_ and the large majority follow a verb_noun pattern (e.g., add_space_member, list_tokens, revoke_token). Some exceptions like brainkb_delta, brainkb_search, brainkb_whoami, and brainkb_capabilities break the pattern, but these are few and still readable.
With 49 tools, the server is far above the 25+ threshold for 'too many'. While the broad scope (user admin, spaces, graphs, ingest, provenance, auth) justifies many operations, the sheer number makes it heavy and potentially unwieldy for an agent to navigate.
The tool set covers a wide range of use cases: user/role/capability management, space administration, graph registration, ingest, job monitoring, provenance, search, and SPARQL. However, there are notable gaps such as removing a space member, deleting a space, or updating space metadata, which could leave agents without a way to fully manage the lifecycle of a space.