create_content_spec

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

No annotations are provided, so the description carries the full burden. It discloses key behaviors: the spec auto-creates tasks (write, optimize, schema/meta), keyword data is resolved dynamically, and the response includes a spec_id. It does not mention if it is destructive or any other side effects, but as a creation tool, it is expected to be non-idempotent. The level of disclosure is good.

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 with four sentences. It is front-loaded with the core purpose and efficiently provides usage context, key behaviors, and follow-up steps. Every sentence adds value, with no redundancy or fluff.

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?

The description covers purpose, usage, key behaviors, and follow-up. It mentions that the response includes a spec_id and recommends using get_feature_spec to retrieve full data. However, it does not mention error cases or prerequisites like the cluster must exist. This is a minor gap given the tool's complexity, so score 4.

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?

The input schema has 100% description coverage, so baseline is 3. The description adds extra meaning: it explains that 'domain' defaults to SEO_CLIENT_DOMAIN, 'title' is auto-generated from cluster if omitted, and 'priority' defaults to cluster priority. This enriches the semantics beyond the schema definitions.

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 purpose: creating a page-type feature spec linked to a keyword cluster. It uses the verb 'create' and specifies the resource 'content_spec'. It distinguishes from siblings by explaining its role in content strategy workflow, especially compared to tools like 'get_feature_spec' which retrieves data.

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 gives clear usage context: 'Use this after creating keyword clusters' and explains that each cluster maps to one page. It also recommends following up with 'get_feature_spec'. While it doesn't explicitly state when not to use it, the guidance is sufficient for an agent to understand the intended workflow.

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