add_observations

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states the tool adds observations to existing entities, implying a mutation operation, but lacks critical details: whether it requires specific permissions, if it's idempotent, what happens on errors (e.g., invalid entity names), or rate limits. For a mutation tool with zero annotation coverage, this is a significant gap in 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 a single, efficient sentence that directly states the tool's purpose without redundancy. It's front-loaded with the core action and target, making it easy to parse. Every word earns its place, with no wasted verbiage.

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 complexity of a mutation tool (adding observations to a knowledge graph) with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what constitutes a valid observation, how duplicates are handled, error conditions, or the return format. For a tool that modifies data, more context is needed to ensure safe and correct usage.

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%, with clear documentation for the 'observations' array and its nested 'entityName' and 'contents' fields. The description adds no additional parameter semantics beyond what the schema provides (e.g., no examples of valid observation formats or entity naming conventions). Baseline 3 is appropriate since the 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 action ('Add new observations') and target ('to existing entities in the knowledge graph'), which is specific and unambiguous. It distinguishes from siblings like 'create_entities' (creates new entities) and 'delete_observations' (removes observations). However, it doesn't explicitly contrast with 'search_nodes' or 'open_nodes', leaving some sibling differentiation incomplete.

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 compare to siblings like 'create_entities' for new entities or 'search_nodes' for querying. Without such context, an agent might misuse it.

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