update_call

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

No annotations are provided, so the description carries full burden. It discloses critical behaviors: spam-flagged calls become hidden from GET endpoints (404 on re-read), empty-string fields are rejected, length caps for note (4000), customer_name (200), tags (100). It also explains why `value` is not exposed (server error), providing exceptional 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 well-structured with bullet points for Args and separate notes. It front-loads the main purpose. While lengthy, every sentence provides unique value. Minor improvement could be merging some points, but overall excellent organization 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 with 7 parameters, no annotations, and an output schema (likely covering return values), the description covers all nuances: error conditions (empty strings, spam 404), alternative tools, length caps, and auto-resolution. It is comprehensive and leaves no obvious 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?

With 0% schema description coverage, the description fully compensates. It explains each parameter's purpose (e.g., account_id auto-resolves, tags replaces, note replaces) and adds constraints (length caps, empty-string behavior, tag count limit). This adds significant meaning beyond the schema's raw types.

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 'Update an existing call: notes, tags, spam flag, customer name, lead status.' It provides a specific verb+resource and distinguishes from siblings by explicitly referencing `add_call_tags` and `remove_call_tags` for additive tag changes, and `update_form_submission` for the `value` field.

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 context on when to use this tool vs alternatives: it mentions using `add_call_tags`/`remove_call_tags` for additive changes, and warns about spam flagging hiding calls. It also advises against empty strings. However, it does not explicitly list when not to use it, relying on implied context.

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