summaryFetch the Wiktionary REST page summary (title, extract, thumbnail) for a word on the specified language subdomain (default en).
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | ||
| word | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 (readOnlyHint, idempotentHint, destructiveHint false) already inform the agent of safe, idempotent behavior. The description adds that it fetches from the Wiktionary REST API with a default language subdomain, providing context beyond annotations. It doesn't mention rate limits or pagination, but given annotations, this is sufficient.
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 that front-loads the action ('Fetch the Wiktionary REST page summary') and includes parameters inline. Every word contributes meaning; there is no redundancy or filler.
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's simplicity (2 parameters, no enums, output schema present) and thorough annotations, the description covers purpose, parameters, and default behavior. It enables correct selection and invocation without gaps.
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 has 0% description coverage, so the description must explain parameters. It clearly defines 'word' as the term to look up and 'lang' as the language subdomain (default en), adding semantic meaning that the schema (only names and types) lacks. This fully compensates for the lack of schema 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 fetches a Wiktionary REST page summary (title, extract, thumbnail) for a word on a specified language subdomain, defaulting to English. This specificity distinguishes it from sibling tools like 'definition' or 'etymology' which likely provide more detailed or different 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 implies the tool is for fetching brief summaries from Wiktionary but does not explicitly state when to use it over alternatives like 'definition' or 'etymology'. There is no mention of when not to use it or any prerequisites.
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 five Wiktionary tools are distinct, but the set is dominated by Pipeworx/prediction-market/memory tools with heavy overlap: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and ask_pipeworx_grounded/deep_research/discover_tools all cover routed lookup. An agent would struggle to pick between these overlapping research entry points.
Most names use snake_case, but the style is inconsistent: noun-only names (definition, summary, etymology) sit alongside verb_phrase names (validate_claim, scan_dependency, ask_pipeworx) and compound names (recent_changes, polymarket_edges). No consistent verb_noun or resource_action convention is applied across the set.
36 tools is far too many for a Wiktionary server, and only 5 of them (definition, etymology, pronunciations, search, summary) actually serve Wiktionary. The remaining 31 are unrelated utilities (Pipeworx data routing, Polymarket betting, memory, subscriptions), making the count an extreme mismatch with the server's stated purpose.
For basic Wiktionary lookups the surface is usable: search, summary, parsed definitions, etymology, and pronunciations cover the core read path. However there are notable gaps for a dictionary server—no full-entry/wikitext fetch, translations, synonyms, usage examples, or random/word-of-the-day access—and the presence of dozens of unrelated tools does nothing to fill those gaps.