searchWiktionary title + fulltext search.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | ||
| limit | No | 1-50 (default 10) | |
| query | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| count | Yes | Number of items returned. | |
| items | Yes | Wiktionary search results from MediaWiki Action API |
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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds context that the search is over Wiktionary titles and fulltext, which is useful but does not disclose additional behavioral traits (e.g., pagination, rate limits). It adds some value beyond annotations.
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 sentence with no wasted words. It is front-loaded and conveys the core functionality efficiently. However, it could be slightly more verbose to improve completeness.
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 tool has 3 parameters and an output schema, the description is too minimal. It does not explain the nature of results, any required prerequisites, or how to interpret inputs. The agent may struggle to use the tool correctly without additional context.
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 only 33% (only 'limit' described). The description does not clarify the meaning of 'query' or 'lang' beyond what the schema provides. With low coverage, the description fails to compensate, leaving parameter semantics unclear.
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 tool description clearly specifies the verb (search), resource (Wiktionary), and scope (title + fulltext). This differentiates it from sibling tools like 'definition', 'etymology', or 'pronunciations', which target specific aspects of Wiktionary content.
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 provides no guidance on when to use this tool versus alternatives. With many sibling tools (e.g., 'deep_research', 'bet_research'), the agent receives no context for selection. No exclusions or usage scenarios are mentioned.
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.
The toolset is overwhelmingly fragmented: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical entry points; polymarket_edges, polymarket_arbitrage, and polymarket_fill_risk heavily overlap; and ai_visibility_check vs scan_competitor_ai_presence cover the same task. The five actual Wiktionary tools are distinct but are lost among dozens of unrelated research and prediction-market tools, making selection highly ambiguous.
All names use snake_case and several logical prefixes (ask_pipeworx, polymarket_, pipeworx_) create local patterns. However, the naming mixes noun-style commands (definition, etymology, pronunciations, summary) with verb-style commands (search, remember, forget, validate_claim), and no consistent verb_noun convention carries across the whole set.
36 tools is already heavy, but the deeper problem is that only 5 tools actually belong to a Wiktionary server while 31 tools serve unrelated Pipeworx, Polymarket, memory, and marketing-audit functions. The count is wildly inappropriate for the declared server purpose.
The Wiktionary-relevant tools cover basic word lookup—search, summary, definition, etymology, pronunciations—but omit common dictionary operations like translations, usage examples, inflected forms, or random entries. The non-Wiktionary majority does not fill these gaps; it just makes the surface area incoherent and hard to reason about.