Get the DeskCrew.ai agentic catalog: what is for sale (a managed AI phone agent for a business), the exact price and payment rails, the spec schema, and why an agent operating for a call-missing business would buy it.
| Name | Required | Description | Default |
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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 describes the content but not behavioral traits like side effects (likely read-only), authentication requirements, or rate limits. The description implies no mutability, but does not explicitly confirm it.
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 two sentences long, front-loading the purpose in the first sentence and providing essential details in the second. No extraneous content, earning its place.
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 no output schema and zero parameters, the description provides sufficient detail about the return content. However, it omits format details (e.g., response structure), but the simplicity of the tool (single retrieval) makes this acceptable.
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?
There are zero parameters, and schema coverage is 100% (empty schema). The description adds significant meaning by detailing what the catalog returns, which goes beyond the schema's scope. This meets the baseline of 4 for zero-parameter tools.
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 explicitly states 'Get the DeskCrew.ai agentic catalog' with a clear verb-resource pair. It lists exactly what the catalog contains (items, price, payment rails, spec schema, buyer rationale), distinguishing it from sibling tools like create_purchase_challenge and submit_payment.
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-to-use or when-not-to-use guidance is provided. While the tool's purpose is clear from the description, it does not discuss alternatives or context relative to siblings, leaving the agent to infer usage without direct comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct role: browsing catalog, initiating purchase with challenge, submitting payment, and checking order status. No overlap.
All tool names follow a consistent verb_noun pattern (create, get, submit) with clear nouns (purchase_challenge, catalog, order_status, payment).
With 4 tools, the set is minimal and focused, exactly covering the purchase workflow without excess or insufficiency.
The tools cover the full purchase lifecycle: viewing catalog, creating a challenge, submitting payment, and tracking order status. No missing steps.