summarize_entity

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

No annotations are provided, so the description bears full responsibility for disclosing behavioral traits. It only states the high-level purpose without detailing side effects (e.g., whether observations are modified or deleted), authorization needs, or return format. This is insufficient for a tool that likely mutates data.

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 consists of two concise sentences that immediately convey the tool's purpose and differentiate it from a sibling. No extraneous words or redundant information, making it highly efficient for an AI agent.

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 tool that likely modifies entity observations, the description lacks essential details: the output (e.g., confirmation, new summary observation), process (in-place modification vs. creation), and handling of redundant observations. Without this, an agent might misuse or misunderstand outcomes.

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 coverage is 100%, so parameters are already documented. The description does not add extra meaning beyond the schema's definitions for 'entityName' and 'threshold'. Baseline score of 3 applies because no additional value is contributed.

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 auto-summarizes redundant observations within a single entity, using a specific verb and resource. It also distinguishes from the sibling tool 'compress_graph' by explicitly noting the difference in scope (within one entity vs. merging similar entities).

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 clear guidance by contrasting with 'compress_graph', indicating when to use this tool (within a single entity) versus when to use the sibling (merging entities). It lacks explicit when-not conditions or alternative tools, but the comparison is sufficient for an effective guideline.

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