Tájékoztató bruttó (ÁFA-s) ár egyedi méretű műanyag nyílászáróra (ablak/ajtó/redőny). Custom-size gross price estimate — computed live, no fixed SKU. Final price after on-site survey.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | window=ablak, door=ajtó, shutter=redőny | |
| color | No | Szín, pl. Fehér, Antracit | |
| glazing | No | 2 vagy 3 rétegű üveg | |
| quantity | No | ||
| width_cm | Yes | Szélesség cm-ben | |
| height_cm | Yes | Magasság cm-ben |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full burden. It discloses that the price is computed live, has no fixed SKU, and that the final price may change after an on-site survey. This sets realistic expectations. However, it does not mention rate limits, response structure, or error behavior, which would further aid an agent.
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 very concise: two short sentences per language, front-loaded with key points. Every sentence adds value (live computation, custom sizing, survey dependency). No redundant or vague language.
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, the description could better explain the return format (e.g., currency, number, validity period). It also omits error conditions or scope (valid for certain products). However, the schema covers input constraints, and the tool is simple, so the description is minimally adequate.
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 high (83%), so the baseline is 3. The tool description adds no additional meaning beyond the schema; it rephrases concepts in bilingual text but doesn't elaborate on parameter constraints or relationships. For example, 'quantity' is undocumented in the schema and not addressed in the description.
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 it provides a gross price estimate for custom-sized plastic windows/doors/shutters, with bilingual Hungarian/English text. It distinguishes from sibling tools (check_stock, confirm_quote, list_inventory, request_quote) by specifying it is a live estimate and not a final quote. The verb 'get_price_estimate' combined with definitions 'computed live' and 'no fixed SKU' makes the purpose unambiguous.
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 implies usage context (getting an instant estimate before ordering), but lacks explicit guidance on when to use this tool versus alternatives like request_quote or confirm_quote. No 'when not to use' or direct comparisons to siblings are provided, leaving the agent to infer relative purpose.
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.
