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

Annotations declare the safety profile (destructive, idempotent, not read-only). The description adds valuable context: no AI call, a versioned snapshot with a specific label, and the exact return payload including applied count, rejected reasons, counts, and link. This goes beyond annotations, though it doesn't cover auth or rate limits.

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?

Three short sentences, front-loaded with purpose, then behavior and returns. No wasted words; each sentence adds distinct information.

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 output schema, the description supplies return values, snapshot behavior, and AI-call status. Coupled with comprehensive annotations and full schema coverage, an agent has enough to invoke correctly.

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 the schema documents id, kind, label, source, target, note. The description only restates 'by edge id' and 'label or kind', adding minimal meaning beyond the schema; baseline 3 is appropriate.

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?

States a specific verb (Change) and resource (label or kind of existing edges) scoped by edge id. It distinguishes itself from add_edges/remove_edges by targeting existing edges, but does not name a sibling alternative explicitly, so 4.

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?

No explicit when/when-not guidance or alternatives. 'Change ... existing edges' implies use for modifying edge attributes rather than adding/removing, but an agent must infer this from sibling names alone.

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