brainkb_job_status
Detailed status of one ingest job: status, progress %, current file/stage, per-file failures, and (when complete) a summary.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes |
Detailed status of one ingest job: status, progress %, current file/stage, per-file failures, and (when complete) a summary.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the burden of behavioral disclosure. It adds useful context by detailing the returned fields and the conditional 'when complete' summary. However, it does not explicitly state that the operation is read-only, nor does it address error behavior, authentication, or rate limits, leaving some transparency gaps.
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 a single sentence, front-loaded with the core purpose and followed by a concise list of output components. Every phrase is informative; there is no redundancy or filler.
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 status tool, the description covers the key output content well, including the condition for a summary. It does not mention how to discover job_id (e.g., via brainkb_list_jobs) or error handling, but given the simplicity and lack of output schema, the description is largely sufficient.
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 only defines job_id, and the description adds that it concerns an 'ingest job', implying job_id is the identifier for that job. Still, with 0% schema coverage, the description does not fully compensate: it does not explain how to obtain job_id or provide formatting nuances, so semantic support is minimal.
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 clearly identifies the tool's purpose: reporting detailed status of a single ingest job. It lists specific output elements (status, progress %, current file/stage, per-file failures, summary), which distinguishes it from sibling tools like brainkb_list_jobs (plural, listing all jobs) and brainkb_recover_job (recovery action).
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 scope is made clear ('one ingest job') indicating use when a specific job ID is known and detailed status is needed. It does not explicitly mention alternatives or when-not to use, but the singular focus differentiates it from list-oriented or recovery tools without ambiguity.
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.