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Glama

videogames

by io.github.pipeworx-io

Remember

remember
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. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover read-only (false), idempotent (true), destructive (false). The description adds valuable context beyond annotations: scoping by identifier, persistence differences between authenticated (persistent) and anonymous (24 hours) sessions, and that data spans conversations/sessions. It does not contradict 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 concise sentences, each serving a distinct purpose: purpose, usage context, and operational details. No filler or redundant content. Highly efficient and well-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 two-parameter tool with no output schema, the description covers all critical aspects: what it does, when to use, storage lifetime, scoping, and relationship to sibling tools. No meaningful gaps for the agent to misuse it.

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

Parameters3/5

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

Schema description coverage is 100%, with both key and value already explained via examples. The description adds minimal extra semantic value by reinforcing that these are 'key-value pairs' and giving conceptual examples of keys, but this mostly overlaps with schema. Baseline of 3 is appropriate.

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 uses a specific verb ('Save') and clearly names the resource ('data the agent will need to reuse later') and mechanism ('key-value pair'). It explicitly distinguishes from sibling tools by naming recall and forget, making the purpose unambiguous.

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?

Provides explicit when to use ('Use when you discover something worth carrying forward') with concrete examples. It also states what not to use it for indirectly via pairing: 'Pair with recall to retrieve later, forget to delete.' This directly guides tool selection relative to siblings.

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

All videogames toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Heavy overlap within the ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta which is currently identical, ask_pipeworx_grounded, deep_research) and among prediction market tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) makes selection genuinely ambiguous. Some tools are distinct (remember/recall/forget), but the clustering blurs boundaries.

Naming Consistency2/5

Conventions are mixed: some tools use verb_noun (list_games, get_game, filter_games, subscribe, unsubscribe, recall, remember) while others use ad-hoc noun phrases or brand-style names (polymarket_arbitrage, entity_profile, deep_research, ask_pipeworx, bet_research). No single pattern dominates, making it harder to predict tool names.

Tool Count1/5

34 tools is heavy, and the mismatch is severe: the server is named 'videogames' but only 3 of 34 tools (list_games, get_game, filter_games) have any relation to video games. The bulk are Pipeworx data/prediction-market/memory utilities that do not belong under this server's apparent purpose. This is a fundamental scope failure.

Completeness2/5

As a video game server, the surface is extremely thin: only list/get/filter by tags and platform, with no search by name, no CRUD, no reviews, no categories beyond the fixed filter set. The other 31 tools are irrelevant to the videogames domain, so the stated purpose is largely uncovered. The mismatch makes coverage assessment nearly impossible for the actual server name.

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