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Glama

Color Pizza

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)

TDQS

A4.5/5.0
Behavior4/5

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

Annotations indicate idempotentHint=true, readOnlyHint=false, destructiveHint=false. Description adds persistence scoping (authenticated vs anonymous) and that it's key-value based, providing useful behavioral context 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?

Two sentences, front-loaded with primary purpose, no filler, efficiently packs all needed information.

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 2-param tool with no output schema, the description covers purpose, persistence, pairing with siblings, and parameter usage completely.

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 type and description. Description adds naming conventions (e.g., 'subject_property') and that value can be any text, giving practical usage cues 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?

The description explicitly states the tool saves data for later reuse across conversations or sessions, with concrete examples like ticker, address, preference. It clearly distinguishes from sibling tools (recall, forget) by mentioning them.

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?

It advises using the tool when discovering something worth carrying forward, and pairs it with recall and forget for full lifecycle. No explicit when-not, but the context is clear.

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

A4.3/5.0
Disambiguation4/5

Most tools have distinct purposes, such as `entity_profile` for company profiles and `recent_changes` for updates. However, some overlap exists between `ask_pipeworx` and `ask_pipeworx_grounded` (both query data, one with hallucination resistance), and among Polymarket-related tools (`bet_research`, `polymarket_edges`, `polymarket_arbitrage`). Detailed descriptions help distinguish them.

Naming Consistency5/5

All tool names follow a consistent snake_case pattern (e.g., `ai_visibility_check`, `ask_pipeworx`, `bet_research`, `compare_entities`). No mixing of camelCase or other conventions. The names are descriptive and predictable.

Tool Count3/5

At 29 tools, the server is on the heavy side. While each tool serves a specific function, the broad scope (color naming, Polymarket betting, company research, etc.) makes the count feel slightly high for a single server, though still manageable.

Completeness4/5

The tool set covers color naming, company research, Polymarket, AI visibility, memory, subscriptions, and data queries comprehensively. Minor gaps exist (e.g., no direct SEC filing retrieval without compound tools), but overall it provides a well-rounded surface for its diverse domain.

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