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

With no annotations, the description carries the full burden and does so richly: it discloses graph registration, the PROV-O import record contents (who, when, file media type/size/sha256, exclusions), the asynchronous job → job_id lifecycle with polling (brainkb_job_status) and delta reconciliation, the work/ exclusion, the 409 duplicate behavior, and that it reads the server filesystem under MCP_INGEST_ROOT. This is far beyond minimal disclosure.

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?

Front-loaded with the core action and input definition, and every sentence adds distinct operational value (permissions, job flow, errors). It is dense with nested parentheticals in a single block, which slightly impedes scanning, but there is essentially no wasted content.

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?

No output schema exists, yet the description covers the return signal (job_id) and the follow-up tools needed to track it, plus error semantics (409), permission requirements, and input format. For a two-parameter ingest tool with no annotations or output schema, nothing an agent needs to call it correctly is missing.

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%, so the description must compensate, and it does: output_dir is defined precisely as the folder holding review.json and review.ttl as the synthscholar skill writes it, and space_slug is characterized as a space the caller may write to as owner/editor. Both required parameters gain real meaning not present in the bare schema.

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?

States a specific verb and resource ('Ingest a SynthScholar review') and immediately defines the precise input: the run's output directory containing review.json and review.ttl. This clearly distinguishes it from the generic siblings brainkb_ingest_files, brainkb_ingest_text, and brainkb_ingest_upload.

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?

Explicitly names the precondition (a space you may write to, owner or editor), routes the agent to brainkb_list_writable_spaces to find one, and states the uniqueness rule (once per review per space). The 409 refusal condition on re-ingesting the same run into the same space is spelled out, so an agent knows exactly when this call will succeed or fail.

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