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

No annotations are supplied, so the description carries the full burden, and it does disclose ordering ('largest first'), the resolution of members to names/types, and the per-call cost ('Free · 1 credit'). It doesn't say whether this is purely read-only or how large a result set can get, which matters given the undocumented `limit`.

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 plus a cost tag, with the output shape front-loaded and the workflow instruction second. Every clause carries usable information and there is no 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?

With no annotations and no output schema, the description does enough by sketching the return structure (communities, hub nodes, member samples) and the level semantics. The remaining shortfall is that `limit`'s effect on the returned number of communities is unexplained.

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 67%, with `level` and `topic_id` already documented in the schema; the description mostly restates the level semantics rather than adding new detail. The `limit` parameter (1–50, default 20) is explained in neither the schema nor the description, leaving a genuine gap in a read tool where result truncation matters.

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 algorithm, resource, and scope: 'Louvain communities of a topic expert's knowledge graph at one dendrogram level.' It also declares the output shape (largest first, hub nodes plus a member sample resolved to names/types), which lets an agent distinguish this from sibling graph tools like expert_graph_map or citation_walk without opening a schema.

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?

Gives explicit usage context — 'use to get the shape of a field before drilling in' — and names the follow-up call ('Then expert_node_context on a hub'), plus level semantics guidance (0 = finest, max_level = coarsest). It does not state when to prefer a different overview tool instead, so the when-not side is absent.

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