communities

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

With no annotations provided, the description carries the full burden and does substantial work: it explains the algorithm (label propagation), the input domain (call graph), the independence from directory structure, the community attributes (label, size, cohesion, files, top members), modularity reporting, and connector hubs. It does not explicitly state read-only behavior or side-effect absence, but the behavior it discloses is rich and accurate for a graph-analysis 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?

The description is dense but well structured: it front-loads the core concept, then output details, then the report-level outputs, then the parameter condition, then the usage workflow. Every sentence adds distinct information, and the length is justified by the algorithmic complexity.

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?

The tool is complex and has no output schema, but the description compensates well by enumerating the community fields and the graph-level reports (modularity, connector hubs). The main gap is that four of five parameters are not semantically explained in the description or schema, so an agent cannot fully reason about how n, members, and min_size affect the returned communities. Overall this is close to complete for default-parameter usage.

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 only 20%, so the description must compensate for the four undocumented parameters. It only meaningfully explains include_dispatch ('set include_dispatch for C function-pointer trees'). The parameters n, members, and min_size remain ambiguous despite defaults; the description mentions 'size' and 'top members' but does not clearly tie them to members or specify what n controls.

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 what the tool does: it partitions the call graph into communities/clusters using label propagation, independent of directory layout. It names the output concept ('codebase's SUBSYSTEMS'), gives concrete output fields, and distinguishes itself from the sibling tool hubs by sequencing: 'Use AFTER hubs to go from what is central to what are the parts.'

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 it after hubs, which gives a clear workflow context and differentiates it from that sibling. It also gives a specific condition for include_dispatch on C function-pointer trees. However, it does not mention when NOT to use it or name other alternatives beyond hubs, so it stops short of full guidance.

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