claude-session-continuity-mcp

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

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: it's read-only, returns connected memories with relation details, supports filtering by relation type and direction, and mentions performance implications ('Higher values return more results but may be slower'). It doesn't cover error conditions or response format, but provides substantial operational context.

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 efficiently structured in three sentences: first states core functionality, second specifies return data and constraints, third provides usage alternatives. Every sentence adds value with zero waste, and key information is front-loaded.

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?

For a read-only tool with 100% schema coverage but no output schema, the description provides good context about what the tool returns (connected memories with relation types, strengths, directions) and performance considerations. It could benefit from clarifying the output structure since there's no output schema, but it's largely complete for its complexity level.

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 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema—it mentions filtering by relation type and traversal direction, but these are already clear from the schema. Baseline 3 is appropriate when schema does the heavy lifting.

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 specific action ('traverse the knowledge graph from a starting memory using depth-first search') and resource ('knowledge graph'), distinguishing it from siblings like memory_related (combined graph+semantic approach) and graph_connect (add new edges). It provides a precise verb+resource combination with explicit 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 explicitly states when to use alternatives: 'use memory_related instead for a combined graph+semantic approach; use graph_connect to add new edges.' This provides clear guidance on tool selection based on functional differences, with named alternatives and their purposes.

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