openai_add_project_user

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the key constraint (cannot invite new org members), the prerequisite (must already be a member), and the role options. It does not cover potential idempotency or error behavior, but the core mutation semantics are clear.

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 concise and well-structured. The main action is front-loaded, followed by a key limitation, then parameter documentation. Every sentence adds value with no redundancy.

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 tool's simplicity (3 required params), no annotations, and presence of an output schema, the description is complete. It covers purpose, usage constraints, prerequisites, and parameter semantics, providing enough context for correct invocation.

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 0%, so the description fully compensates. Each parameter is explained with meaningful context: project_id references openai_list_projects, user_id references openai_list_users, and role specifies valid values 'owner' or 'member'.

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's function with a specific verb and resource: 'Add an existing organization member to a project.' It distinguishes this from invite_user by explicitly noting this call cannot invite someone new to the org.

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 explicit usage guidance, stating the prerequisite (user must already be an org member), directly referencing alternatives (openai_invite_user / openai_list_users), and providing cross-references for parameter lookups (openai_list_projects, openai_list_users).

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