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

With no annotations, the description carries the burden. It discloses output format (JSON-LD) and scope (one ingest job), but does not explicitly state read-only semantics, error handling, or rate limits. Provides some behavioral context but leaves important details implicit.

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?

A single sentence with no filler, front-loading the key information. It is appropriately brief for a simple one-parameter tool, though it omits useful context that could be included without losing conciseness.

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?

The description is too sparse for an agent to use confidently. It does not clarify how this relates to brainkb_provenance_graph, what the JSON-LD bundle contains, or whether the job must be in a specific state. Missing usage guidance and parameter explanation leave significant gaps.

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 coverage is 0%, so the description must compensate. It mentions 'one ingest job' but does not explain what job_id is, how to obtain it, or format constraints. The description adds minimal semantic value beyond the bare schema field.

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 identifies the resource (PROV-O provenance bundle in JSON-LD) and scopes it to a single ingest job, distinguishing it from brainkb_provenance_graph. However, it lacks an explicit verb like 'retrieve' or 'get,' making the action implicit.

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?

No guidance is provided on when to use this tool versus alternatives like brainkb_provenance_graph or brainkb_job_status. It does not state prerequisites, exclusions, or the context in which this tool is preferred.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.