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Glama

Gistemp

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?

Beyond annotations (idempotentHint=true, destructiveHint=false), the description adds behavioral details: key-value storage, scoping by identifier, persistence (24hr vs permanent for authenticated users), and pairing with recall/forget. It does not contradict annotations. Could clarify overwrite behavior, but idempotent hint implies safe repetition.

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?

The description is concise—three sentences—and front-loaded with purpose. Every sentence adds value: purpose, usage trigger, storage details, and pairing with siblings. No redundancy or filler.

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) and the presence of related sibling tools, the description is complete. It covers what, when, how (scope, persistence), and how it relates to recall and forget. No critical information is missing.

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%, so baseline is 3. The description adds value by providing example keys (e.g., 'subject_property', 'target_ticker') and clarifying that value is 'any text' including findings, addresses, etc. This enriches understanding beyond the schema's brief descriptions.

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's purpose: saving data for reuse across conversations or sessions. It provides concrete examples (resolved ticker, target address) and distinguishes from sibling tools recall and forget, which are explicitly mentioned. The verb 'Save' combined with resource 'data' makes the action unambiguous.

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?

The description gives explicit guidance on when to use: 'when you discover something worth carrying forward' and lists example scenarios. It also notes scope by identifier and persistence differences. However, it does not explicitly state when not to use this tool or directly compare with alternatives beyond pairing with recall/forget, missing a slight opportunity for exclusion guidance.

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

A3.5/5.0
Disambiguation3/5

Many tools have distinct purposes, but there are overlapping functions (e.g., ask_pipeworx vs ask_pipeworx_grounded, entity_profile vs compare_entities vs recent_changes) that could confuse an agent. However, detailed descriptions help mitigate ambiguity.

Naming Consistency2/5

Tool names follow no consistent pattern: snake_case (ai_visibility_check), camelCase (none here but inconsistent), and mixed verb/noun styles (subscribe vs entity_profile). The naming is chaotic and does not follow a predictable convention.

Tool Count2/5

With 33 tools, the server is bloated for its claimed Gistemp focus (only 3 tools directly about Gistemp). Most tools belong to a broader Pipeworx platform, making the scope too broad and unfocused.

Completeness1/5

For a server named 'Gistemp,' the tool set is severely incomplete—only 3 tools cover temperature anomalies. The majority of tools address unrelated domains (Polymarket, SEC filings, memory, etc.), leaving obvious gaps for the stated purpose.

Resources