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Glama

Rawg

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. First observed

TDQS

A5/5.0
Behavior5/5

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

Adds context beyond annotations: scoped by identifier, persistent vs 24-hour retention. Annotations already indicate idempotentHint=true and destructiveHint=false, and the description aligns without contradiction.

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, front-loaded with main purpose, no unnecessary words. Each sentence adds distinct information (what, when, scope, pairing).

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?

Complete for a simple 2-parameter tool: covers purpose, usage context, pairing, scoping, and persistence. No gaps given the tool's simplicity.

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

Parameters5/5

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

Schema coverage is 100% with descriptions. The description adds value by giving example key formats and clarifying that value can be any text, reinforcing practical usage.

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 'Save data the agent will need to reuse later' with specific examples like resolved ticker, target address, user preference. It distinguishes from sibling tools (recall, forget) by describing its function as storing key-value pairs.

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?

Explicitly tells when to use: 'when you discover something worth carrying forward'. Provides guidance on pairing with recall and forget, and differentiates between authenticated and anonymous sessions.

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

A3.6/5.0
Disambiguation2/5

Multiple tools have unclear boundaries: ask_pipeworx_beta is explicitly identical to ask_pipeworx, bet_research overlaps heavily with polymarket_edges, and entity_profile/recent_changes/compare_entities/validate_claim all pull from the same SEC/news fundamentals space. The memory trio and game lookup tools are distinct, but too many other tools could be confused for one another.

Naming Consistency3/5

The surface is uniformly snake_case and has some strong families (list_*, polymarket_*, ask_pipeworx_*), but it mixes verb-led names (search_games, remember, validate_claim) with noun-led names (entity_profile, polymarket_arbitrage, pipeworx_trending) and brand-style names like ask_pipeworx. There is a pattern, but it is not a single consistent one.

Tool Count2/5

35 tools is a heavy surface, and the set feels sprawling rather than focused: a four-tool RAWG game submodule sits alongside a general-purpose research platform, Polymarket edge tooling, memory helpers, subscriptions, feedback, and meta-utilities. Many of these could have been consolidated or split into separate servers.

Completeness3/5

As a general data-research and prediction-market platform the coverage is strong, with lookup, grounded verification, entity resolution, research fan-out, and subscription flows. But for a server named Rawg, the game domain is thinly covered with only search/get/list tools and no game-detail enrichment or broader browsing surface, leaving the core domain feeling like an afterthought.

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