A request_quote után az ügyfél e-mailben kapott 6 jegyű megerősítő kód beváltása. CSAK a sikeres megerősítés után továbbítódik az ajánlatkérés az irodához. Paraméterek: a request_quote válaszában kapott lead_ref + az ügyfél által bemondott kód. A kód 30 percig érvényes, max 5 próbálkozás.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | Az ügyfél e-mailjére érkezett 6 jegyű kód. | |
| lead_ref | Yes | A request_quote válaszában kapott hivatkozás. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It mentions code expiry (30 minutes) and max 5 attempts, but does not disclose whether the operation is read-only or destructive, or what happens on failure beyond implied blocking.
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 a single, clear paragraph that front-loads the purpose. It is concise but could be improved with bullet points for readability.
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 no annotations, the description provides critical behavioral constraints (30-min validity, 5 attempts) and clear parameter sources. It sufficiently covers the tool's context for a confirmation step.
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 already describes both parameters (100% coverage). The description adds that 'lead_ref' comes from the 'request_quote' response and that the code is delivered via email and spoken by the customer, adding practical context.
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: redeeming a 6-digit confirmation code after a 'request_quote' call. It distinguishes itself from siblings by specifying it is a post-request_quote confirmation step.
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 explicitly states it should be used after 'request_quote' and provides context about code validity and max attempts. It does not explicitly list alternatives but implicitly tells when to use this tool.
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.
Tools mostly target distinct operations, but check_stock and list_inventory both relate to ready-stock items, which could cause minor confusion. Descriptions clarify the difference (specific size vs. full listing), but the overlap is noticeable.
All tool names follow a consistent verb_noun pattern with underscores (e.g., check_stock, request_quote). The verb choice is varied but appropriate for each action, and no naming style deviations exist.
With 5 tools, the server is well-scoped for its purpose—handling stock inquiries, price estimates, and quote requests. No tool feels redundant or missing for the core workflow.
The tool set covers pre-sales actions (stock check, inventory, price estimate, quote request, confirmation) but lacks any post-quote functionality like order placement, status tracking, or cancellation, leaving an incomplete lifecycle.
