get_community_insights

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

Without annotations, the description must disclose behavioral traits. It mentions anonymization and no exposure of raw paths, which is good. But it lacks details on data freshness, latency, or any limitations that might affect agent decisions.

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?

The description is concise, with three sentences that each add value: the first explains the action and outputs, the second emphasizes anonymization. It is front-loaded with the verb 'Aggregate' and free of fluff.

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?

Given the tool has no parameters, no output schema, and no annotations, the description covers key aspects: what it does, what it returns, and a privacy note. It could be considered complete for a simple read-only tool, though additional context on data source freshness would improve it.

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?

There are no parameters, so the input schema provides no information. The description adds value by explaining the output data, but since there are no parameters, a baseline of 4 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 clearly states the tool aggregates cross-project signals from the Knowledge Graph and lists specific outputs like deployment success rates, technology stacks, drift sources, and health distribution. It distinguishes itself from siblings that operate on individual repositories.

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 implicitly suggests usage for obtaining community-level insights with anonymized data. However, it does not explicitly state when not to use it or name alternatives, though the context makes it clear this is for aggregated data.

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