god_nodes

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

No annotations are provided, so the description carries the full burden. Beyond implying a read-only ranking by connectivity, it discloses nothing about ordering, how many nodes come back, whether degrees are returned, or what happens when the graph is empty — all material for an unannotated tool.

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?

One front-loaded sentence with no filler. It is efficient, though its brevity is under-specification rather than true economy — the length is fine but the content budget is underused.

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, no output schema, and three parameters (one undocumented in the schema), the description should say more about result shape and the hub-exclusion behavior. As written an agent knows the gist but not enough to invoke it confidently or interpret the output.

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%, and the description mentions no parameters at all. Notably top_n has no schema description and the description doesn't compensate; 'most connected' vaguely relates to exclude_hubs_percentile but doesn't explain that it suppresses top-degree nodes.

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 ('Return the most connected nodes') plus an interpretive gloss ('the core abstractions of the knowledge graph'), which tells an agent what kind of result to expect. It doesn't explicitly contrast with siblings like graph_stats or query_graph, but the resource is distinct enough to separate it.

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?

Usage is only implied: an agent can infer this is for getting a high-level map of the graph's hubs. There is no statement of when to prefer this over graph_stats or query_graph, and no mention of prerequisites or when results are misleading (e.g. dense graphs).

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