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

Beyond the readOnlyHint=false annotation, the description discloses two critical runtime behaviors: unknown field names are silently skipped rather than erroring, and passing null clears a field. It also notes that 'name' and 'description' are universally valid across types — exactly the failure mode and value semantics an agent needs before invoking.

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?

Purpose is front-loaded and the paragraph is dense but efficient, with each sentence carrying distinct information. Minor redundancy between 'other field names come from the type's field dictionary' and 'a name the dictionary does not have is skipped' costs a point for perfect economy.

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 2-param mutation tool with 100% schema coverage, the operational essentials are present: field-name sourcing, silent-skip failure, null semantics, and ID discovery via search_graph_objects. With no output schema, the description omits the return value and behavior for a non-existent object_id, which are the main gaps.

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 baseline is 3, but the description adds substantial meaning beyond the schema's example-based parameter docs: field names are validated against the type's dictionary, unknown names are silently skipped, and null clears a value. It also clarifies that object_id comes from search_graph_objects, enriching both parameters.

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?

Description opens with a specific verb+resource ('Rename or re-describe an object in the user's graph') and concrete type-specific examples (contact phone/email/headline/location, company funding stage). This clearly distinguishes it from the many graph siblings: it is neither creation (create_graph_object), deletion (delete_graph_object), reading (get_graph_object), nor search (search_graph_objects).

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?

Provides explicit prerequisites: read the type's field dictionary from get_graph_object ('editable_fields') before choosing field names, and obtain object_id from search_graph_objects. This is clear context, but there is no explicit when-not-to-use statement naming alternatives such as create_graph_object, so it stops short of a 5.

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