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

Annotations already establish read-only, idempotent, and non-destructive behavior. The description adds meaningful behavioral detail beyond that: it specifies the output fields and interprets gate_mode values ('autonomous' vs 'human_pre_gate'), which is especially valuable because there is no output schema.

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?

Two sentences with no filler. The first sentence front-loads the purpose and output, and the second gives the practical use case. Every clause earns its place.

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 read with strong annotations and no output schema, the description covers the essential decision-relevant behavior. The only minor gap is that curate_only and source_corpus_ref are listed but not explained, though the primary gate_mode semantics are fully described.

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 100%, and the single companyId parameter is already documented in the input schema. The description adds only the 'current company' framing and does not introduce new parameter-level semantics, so the baseline score of 3 is appropriate.

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 names a specific verb (read) and a precise resource (content-grain/wisdom-layer publish policy), and explains what the tool returns: per-grain gate_mode, curate_only, and source_corpus_ref. It is clearly distinguishable from the write-oriented sibling set_grain_policy.

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 explicitly says to use this tool to understand which content may be published autonomously versus sent for human pre-approval. It does not name alternatives or exclusion cases, but the read-vs-set split and the stated use case make the intended context clear.

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