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Glama

Climatiq

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

A4.4/5.0
Behavior4/5

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

Annotations provide idempotentHint=true, destructiveHint=false. Description adds valuable context about scoping, persistence (24-hour vs persistent), and being readonly-safe. 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single paragraph, well-structured with clear purpose first. Covers key points without redundancy. Could be slightly more concise but effective.

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 simple tool (2 string params, no output schema), the description fully explains behavior, use cases, and pairing with related tools. No gaps.

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 provides full descriptions for both key and value parameters (100% coverage). Description does not add new semantic detail beyond the existing schema 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?

Description clearly states the tool saves data for reuse across conversations/sessions, with specific verb 'Save' and resource 'data'. It also distinguishes from sibling tools 'recall' and 'forget'.

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 says when to use: 'when you discover something worth carrying forward' and provides examples. Mentions pairing with recall and forget for retrieval/deletion.

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

All Climatiq toolsInspect
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TDQS

A4/5.0
Disambiguation3/5

Most tools have distinct jobs and the descriptions are unusually detailed with cross-references, but there is real overlap in the ask_pipeworx family (ask_pipeworx_beta is explicitly identical to ask_pipeworx right now), the Polymarket edge/arbitrage cluster, and some company-research tools. An agent can usually pick correctly, but only after reading long descriptions carefully.

Naming Consistency3/5

All names are snake_case and many are clear verb_noun forms like estimate_emissions or list_subscriptions, but the set also contains descriptive noun phrases (entity_profile, recent_changes, ai_visibility_check), brand-prefixed names (pipeworx_feedback, polymarket_edges), and bare memory verbs (remember, recall, forget). This is a readable but mixed convention rather than one predictable pattern.

Tool Count2/5

34 tools is well above the comfortable ceiling, and the set bundles several unrelated domains: Climatiq emissions, Pipeworx data research, prediction-market analytics, memory, subscriptions, AI visibility, llms.txt generation, and npm dependency checks. It feels heavy and redundant, with ask_pipeworx_beta and the AI-visibility pair as candidates for removal or merging.

Completeness4/5

The core query workflows are well covered: emission factors lead into estimation, general lookups have plain/grounded/deep variants, claim validation and entity profiles exist, and subscriptions/memory have full lifecycles. The main gaps are minor—no batch emissions endpoint or direct order execution—so agents can work around them.

Resources