Vráti jeden overený fakt podľa jeho id (napr. "sk/tax/vat-standard"). Obsahuje value, unit, valid_from, source{url,quote,published,retrieved}, confidence a freshness{source_dated,last_checked,next_check,stale} — vek faktu posúdiš bez počítania.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ID faktu, napr. sk/wages/minimum-wage |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the response structure (value, unit, valid_from, source, confidence, freshness) and includes a behavioral instruction on how to assess the fact's age without calculation, adding useful context beyond the schema.
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, compact sentence that front-loads the primary action and then lists response fields efficiently. Every clause adds value, with no redundant or filler content.
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 single-parameter read tool with no output schema and no annotations, the description is functionally complete. It enumerates the response fields and gives an interpretation note for freshness, covering the key aspects an agent needs to use the tool correctly.
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 schema already provides a description and example for the 'id' parameter, achieving 100% coverage. The description adds a different example ('sk/tax/vat-standard') but no additional semantic details, so the baseline 3 is appropriate.
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 returns one verified fact by ID, using the verb 'Vráti' (returns) and specifying the resource ('jeden overený fakt'). It differentiates from sibling tools like list_facts and search by focusing on single fact retrieval by ID.
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 for when an ID is available but does not explicitly mention when to use this tool versus alternatives like search or list_facts. No exclusions or alternative suggestions are provided, so guidance is only implicit.
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 clearly distinct purpose: compare for cross-country metric comparison, list_facts for enumeration, lookup_fact for ID-based retrieval, search for fulltext search, and the three post tools target forum vs. blog with update restrictions. No two tools could be easily confused.
Most tools follow a verb_noun pattern (list_facts, lookup_fact, post_message, publish_post, update_post), but compare and search are single verbs, creating a minor stylistic inconsistency that is still readable and predictable.
Seven tools is well-scoped for a facts corpus server: four retrieval methods and three community interaction methods, each earning its place without bloat or sparsity.
The tool surface fully covers the expected domain: fact retrieval (search, list, lookup, compare) and community contribution (post forum messages, publish blog posts, update own posts). No obvious gaps or dead ends; deletion is intentionally absent and compensated by update.