Enhanced Knowledge Graph Memory Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'add new observations' implies a write/mutation operation, the description doesn't address critical behavioral aspects: whether this requires specific permissions, if it's idempotent, what happens on duplicate observations, rate limits, error conditions, or the response format. For a mutation tool with zero annotation coverage, this is a significant gap.

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 a single, efficient sentence that communicates the core purpose without unnecessary words. It's appropriately front-loaded with the main action and target, making it easy to parse quickly. Every word earns its place.

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 mutation tool with no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It doesn't address behavioral implications, parameter meanings, error handling, or what the tool returns. Given the complexity of modifying a knowledge graph and the lack of structured documentation elsewhere, the description should provide more context about how this operation works.

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 description provides no parameter information beyond what's implied by the tool name. With 0% schema description coverage (the schema has no descriptions for its properties beyond the nested object), the description doesn't compensate by explaining what 'observations' contains, what 'entityName' represents, or what 'contents' should include. This leaves parameters largely undocumented.

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 action ('add new observations') and target ('to existing entities in the knowledge graph'), providing a specific verb+resource combination. It distinguishes from siblings like 'create_entities' (which creates new entities rather than adding to existing ones) and 'delete_observations' (which removes rather than adds). However, it doesn't explicitly differentiate from 'normalize_observations' or other observation-related tools.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., entities must exist), exclusions (e.g., cannot create new entities), or when to choose this over similar tools like 'create_entities' (for new entities with observations) or 'normalize_observations' (for processing existing observations).

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