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Glama

Wiktionary

by io.github.pipeworx-io

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Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide idempotentHint=true, indicating repeated calls have the same effect. The description adds valuable behavioral context such as persistence duration (24 hours for anonymous, persistent for authenticated) and scoping by identifier, which goes 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tightly packed sentences with no wasted words. The first sentence states the core purpose, the second provides usage guidance, and the third adds behavioral details. Perfectly front-loaded and structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with only two required parameters and no output schema or nested objects, the description covers all essential aspects: purpose, usage, pairing, scoping, and retention. No gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for both parameters. The description adds usage examples for the key ('subject_property', 'target_ticker') and clarifies that value is any text, enhancing the meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool saves data for later reuse, using specific verbs like 'save' and 'store', and distinguishes itself from the related tools 'recall' and 'forget' that are listed as siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use ('when you discover something worth carrying forward'), provides context on scoping and retention (authenticated vs anonymous), and mentions the complementary tools 'recall' and 'forget'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.2/5.0
Disambiguation2/5

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.

Naming Consistency2/5

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.

Tool Count1/5

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.

Completeness3/5

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.

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