Graforest MCP

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

Annotations cover key behavioral traits (readOnlyHint: true, destructiveHint: false, idempotentHint: true, openWorldHint: false), so the description doesn't need to repeat these. It adds useful context about what the tool returns ('node/relationship counts broken down by type') and its utility ('understanding the graph's size and composition'), which goes beyond annotations. However, it doesn't disclose additional behaviors like rate limits, auth needs, or error conditions. No contradiction with annotations.

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 utility statement. Every sentence earns its place by adding value: the first defines the action, and the second explains why it's useful. It's appropriately sized with zero waste.

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 low complexity (2 parameters, no output schema), rich annotations (covering safety and idempotency), and clear purpose, the description is mostly complete. It explains what the tool does and its utility, which is sufficient for a read-only, idempotent tool. However, it could benefit from more detail on output format or usage examples, but annotations help fill gaps.

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 50% (one parameter has a description, one does not). The description doesn't add any parameter-specific information beyond what the schema provides—it doesn't explain project_code or environment usage. Since schema coverage is moderate, the baseline is 3, as the description doesn't compensate for the lack of parameter details in the schema.

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's purpose: 'Get node/relationship counts broken down by type.' It specifies the verb ('Get') and resource ('node/relationship counts'), and distinguishes it from siblings like get_knowledge_entity or get_knowledge_schema by focusing on statistics rather than specific entities or schema details. However, it doesn't explicitly differentiate from all siblings (e.g., list_knowledge_entities might also provide counts), so it's not a perfect 5.

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 implied usage guidance: 'Useful for understanding the graph's size and composition.' This suggests when to use it (for analytics or monitoring), but it doesn't explicitly state when not to use it or name alternatives (e.g., vs. list_knowledge_entities for detailed listings). The context is clear but lacks explicit exclusions or sibling comparisons.

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