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Glama

Commons Wikimedia

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

A4.5/5.0
Behavior4/5

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

Annotations declare idempotentHint=true and destructiveHint=false. Description adds key behavioral details: key-value pair scoped by identifier, persistence difference between auth and anonymous (24hr), and mentions storage lifetime. No contradictions.

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?

Four sentences, each adding essential information. Front-loaded with purpose, then usage, then behavioral detail. No wasted words.

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?

Given the tool's simplicity (2 params, no output schema), the description fully covers usage, behavior, lifetime, and pairing with sibling tools. No gaps for an agent to misuse.

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 clear descriptions. Description adds value with naming conventions and example keys like 'subject_property', 'target_ticker', and explains value as 'any text'. Provides useful context beyond 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?

Clearly states 'Save data the agent will need to reuse later', with specific verb 'save' and resource 'data'. Distinguishes from sibling tools 'recall' and 'forget' mentioned directly. Highly specific.

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

Usage Guidelines4/5

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

Explicitly describes when to use: 'when you discover something worth carrying forward' with concrete examples. Mentions pairing with recall/forget. Could be improved by noting when not to use (e.g., large data), but overall strong.

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

All Commons Wikimedia toolsInspect
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TDQS

C2.9/5.0
Disambiguation2/5

Multiple tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical routers, and the six polymarket_* tools plus bet_research all cover prediction-market analysis with blurry boundaries. The server name 'Commons Wikimedia' also clashes with 30+ Pipeworx tools, making the overall purpose ambiguous. Only the handful of Commons-specific tools (category_members, file_info, file_revisions, random_image, search) are clearly distinct.

Naming Consistency3/5

All names are lowercase snake_case and many follow a noun_phrase pattern (entity_profile, polymarket_edges, recent_changes), but verb styles are inconsistent: some are bare verbs (search, recall, subscribe), some are verb_noun (generate_llms_txt, resolve_entity, validate_claim), and several are noun-only (category_members, file_info, pipeworx_feedback). The style is readable but not predictable, mixing action-first and object-first conventions.

Tool Count2/5

36 tools is far too many for a server ostensibly named 'Commons Wikimedia' — the vast majority belong to the Pipeworx data platform, not Wikimedia Commons. The count exceeds the 25-tool threshold for 'too many,' and the scope mismatch between the server name and the actual toolset makes the abundance feel even more unjustified.

Completeness2/5

For 'Commons Wikimedia,' the surface is severely incomplete: there is no upload, no category tree navigation, no file download, and no structured search beyond full-text. For the Pipeworx domain, coverage is broad but indirect — most data access funnels through aggregate/meta tools (ask_pipeworx, entity_profile, deep_research) rather than direct per-source tools, leaving gaps for granular lookups and leaving the Commons tools stranded with no real integration.

Resources