Graforest MCP

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

Annotations cover key traits (read-only, non-destructive, idempotent, closed-world), but the description adds valuable context: it implies that entity types are not known upfront and must be discovered via another tool ('get_knowledge_schema'). This behavioral nuance about dependency and discovery is not captured in annotations, enhancing transparency without contradiction.

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 two sentences, front-loaded with the core purpose and followed by a crucial usage guideline. Every word serves a clear purpose, with no redundancy or unnecessary elaboration, making it highly efficient and well-structured.

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's moderate complexity (5 parameters, no output schema), the description is fairly complete. It covers purpose and usage, and annotations provide safety and behavioral traits. However, it lacks details on output format or error handling, which could be helpful for an agent, leaving a minor gap in completeness.

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 high (80%), so the baseline is 3. The description adds minimal parameter semantics by mentioning 'entity type' as an example, but it doesn't provide additional meaning beyond what the schema already documents (e.g., details on 'project_code' or pagination behavior). It compensates slightly but not significantly.

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 verb ('List') and resource ('entities of a specific type'), making the purpose understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'list_knowledge_projects' or 'search_knowledge_graph', which might also list entities in different contexts, so it misses full sibling differentiation.

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 provides explicit guidance on when to use this tool: 'Use get_knowledge_schema first to see available entity types.' This indicates a prerequisite step and helps the agent understand the proper sequence, effectively distinguishing it from alternatives by specifying a preparatory action.

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