mcp_engram_relate

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

With no annotations provided, the description carries the full burden. It discloses the storage mechanism ('ZEDOS_RELATION block'), the directional linking format ('concept_a →[label]→ concept_b'), and the semantics of the volatility parameter (α as a 'RoMem semantic speed gate' with static≈0.1 and dynamic≈0.85). It also explicitly notes the precondition that both concepts must exist. It does not cover return values or error behavior, but for a creation tool this is substantial transparency.

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 concise, with two sentences plus a clearly labeled 'WHEN TO USE' callout. Every sentence adds unique information: the core action, the storage format, the optional parameter semantics, and the usage context. There is no wasted wording, and the structure front-loads the primary purpose.

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 complexity (a simple edge creation with 4 parameters), the description covers the core elements: purpose, parameter semantics, usage context, and a critical precondition. It does not specify return values or behavior on failure, but since there is no output schema, a brief statement about the response would improve completeness. Still, it is adequate for most use cases.

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 input schema already has 100% description coverage, so the baseline is 3. The description adds significant value by explaining the volatility parameter with concrete examples ('static≈0.1, dynamic≈0.85') and the behavior when omitted ('auto-infer from label'). It also clarifies the orientation of concept_a and concept_b through the arrow notation, providing meaning beyond the schema's simple 'Source' and 'Target' descriptions.

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 function: 'Create a directional knowledge graph edge between two concepts using VSA OP_BIND.' This specifies the verb (create), the resource (knowledge graph edge), and the directional nature. It distinguishes itself from siblings like mcp_engram_relate_batch by focusing on a single edge, and from mcp_engram_remember which likely stores concepts rather than relations.

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 includes a dedicated 'WHEN TO USE' section: 'When you discover a meaningful relationship — depends_on, implements, contradicts, supersedes, etc.' It also provides a clear precondition: 'Both concepts must already exist in memory before relating them.' However, it does not mention alternatives such as mcp_engram_relate_batch for batch operations, so it lacks explicit exclusions.

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