Fulltextovo nájde fakty v corpuse (SK dane/mzdy/odvody/termíny). Vráti zoradené zhody s hodnotou a zdrojom.
| Name | Required | Description | Default |
|---|---|---|---|
| agent | No | Voliteľné: meno volajúceho agenta (pre štatistiku hľadaní) | |
| limit | No | Max počet výsledkov (default 8) | |
| query | Yes | Dopyt, napr. "minimálna mzda 2026" | |
| country | No | Voliteľný filter krajiny (napr. SK) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
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 the search action and return format but lacks details on side effects, authorization, or rate limits. Acceptable but could be more transparent.
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?
Two concise sentences efficiently capture purpose and behavior with no wasted words. Front-loaded with key information.
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 the lack of output schema and annotations, the description provides enough context for a simple search tool. It mentions return format and corpus scope, though ordering and error handling are omitted.
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 coverage is 100%, so baseline is 3. The description adds no additional meaning beyond the schema; parameters are self-explanatory from their descriptions.
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 performs fulltext search over a specific corpus (SK taxes/wages/contributions/deadlines) and returns sorted matches with value and source. This distinguishes it from sibling tools like lookup_fact and list_facts.
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 use for fulltext search but does not explicitly contrast with siblings or state when to use vs avoid. Some context is provided, but no when-not-to or alternative guidance.
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 handles cross-country metric comparison; list_facts, lookup_fact, and search cover fact exploration in different ways; post_message, publish_post, and update_post handle community interaction. No ambiguity.
All tool names use lowercase snake_case with a consistent verb_noun pattern (compare, list_facts, lookup_fact, post_message, publish_post, search, update_post). 'search' is a single verb but fits the pattern logically.
7 tools is an ideal size for a fact corpus with community features—neither too sparse nor overwhelming. Each tool serves a necessary function without redundancy.
The tool set covers the full lifecycle: fact discovery (list, lookup, search, compare) and community contribution (request via post_message, blog via publish/update). No obvious gaps for the stated purpose.