Detect wikilink-graph communities (GraphRAG-light)

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

The description provides extensive behavioral details beyond the annotations (readOnlyHint, idempotentHint). It explains computational complexity, typical performance, caching policy (not cached, call once per session), output semantics (modularity range, convergence condition), and that it's pure structural. This adds significant value for agent decision-making.

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 front-loaded with the core action and contains no wasted sentences; each sentence adds value. However, it is somewhat lengthy due to the inclusion of performance metrics and a promotional line ('First MCP server'), which could be trimmed slightly for conciseness without losing essential information.

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 description fully covers the tool's functionality, input, output, behavior, and performance. Even without an output schema, it explains the return structure thoroughly. It addresses all relevant aspects for an agent to use the tool correctly and understand its constraints.

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?

The parameter schema already covers both parameters with clear descriptions (100% coverage). The description adds extra context beyond the schema, such as describing min_size as useful for 'filtering dust' and clarifying default behavior. This provides additional semantic value.

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 computes structural communities over the vault's wikilink graph using greedy modularity optimization (Louvain). It provides a specific verb ('computes') and resource ('communities'), and distinguishes itself from sibling tools by focusing on structural community detection without embeddings.

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 gives clear context on when to use: for analyzing wikilink graph structure, with a note that it's pure structural (no embeddings) and the server remains LLM-free. It advises calling once per session and reuse, but does not explicitly mention when not to use it or compare with alternatives like embedding-based clustering.

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