Run an arbitrary SPARQL query. Requires an Admin/SuperAdmin role (the sparql_admin capability) — for ordinary questions prefer brainkb_search, brainkb_read_space, or the provenance/delta tools, which need no admin role.
| Name | Required | Description | Default |
|---|---|---|---|
| sparql_query | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavioral traits. It clearly states the admin role and capability requirement, which is crucial behavioral context. However, it does not explicitly mention potential side effects (e.g., SPARQL UPDATE/DELETE) or return format, so there is a minor gap in transparency.
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 description is two sentences, with the core purpose stated first, followed by a necessary authorization note and sibling-tool guidance. Every word earns its place; there is no fluff or repetition of schema details.
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 single-parameter tool with no output schema or annotations, the description covers the essential context: what it does, who can use it, and which alternatives to prefer. It does not describe return values or potential side effects, but given the admin-only nature and the explicit alternatives, it is sufficiently complete for an advanced query tool.
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?
Schema description coverage is 0%, and the description adds no detail about the sparql_query parameter beyond the schema's name/type. While the parameter's purpose is largely self-evident from the tool name, the description does not explain query language version, accepted formats, or constraints, so it fails to compensate for the low coverage.
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 opens with 'Run an arbitrary SPARQL query', which is a specific verb+resource combination that clearly states the tool's function. It also distinguishes from sibling tools by explicitly naming alternatives like brainkb_search and brainkb_read_space for ordinary questions, making its scope unambiguous.
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 description provides explicit guidance on when to use this tool versus alternatives: it requires an Admin/SuperAdmin role with the sparql_admin capability, and it recommends other tools for ordinary questions. This directly addresses usage criteria and exclusions.
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.