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Glama

Cnb Cz

by io.github.pipeworx-io

Remember

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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

A4.3/5.0
Behavior4/5

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

Annotations already indicate idempotentHint=true and destructiveHint=false. The description adds valuable context: persistence across sessions for authenticated users, 24-hour retention for anonymous, and scoping by agent identifier. No contradictions with 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?

The description is concise, front-loads the core purpose, then provides usage context and behavioral details. Every sentence adds value with no superfluous 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?

Given the tool's simplicity (2 required params, no output schema) and comprehensive annotations, the description covers all necessary aspects: purpose, when to use, behavioral persistence, and sibling relationships. It is complete for an agent to correctly invoke the tool.

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?

The input schema has 100% coverage with clear parameter descriptions. The description reiterates scoping and persistence but does not add significant new meaning beyond what the schema already provides. Baseline score 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 clearly states the verb 'save data' and resource 'key-value memory store'. It distinguishes itself from sibling tools like 'recall' and 'forget' by specifying the action of storing for later reuse. The purpose is specific and actionable.

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 provides explicit when-to-use guidance with examples (resolved ticker, target address, user preference) and mentions pairing with recall and forget. It explains scoping and persistence, but does not include explicit when-not-to-use scenarios, which would elevate to a 5.

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

A4.2/5.0
Disambiguation4/5

Tools have distinct purposes overall, but some pairs (e.g., ask_pipeworx vs ask_pipeworx_grounded, entity_profile vs recent_changes) could cause agent confusion without careful reading. Descriptions mitigate overlap, so only minor ambiguity.

Naming Consistency4/5

Most tools use snake_case with verb_noun or noun_verb patterns, but several single-word verbs (forget, recall, remember, subscribe) and a few inconsistent forms (czeonia, pribor) break uniformity. Still, the pattern is largely predictable.

Tool Count4/5

31 tools is high but justified for a multi-domain data gateway covering finance, economics, FDA, betting, and subscriptions. Each tool has a clear role, though the count pushes the upper bound for easy scanning.

Completeness5/5

The tool set comprehensively covers its stated domains: entity resolution, financial data, exchange rates, interest rates, SEC filings, FDA, Polymarket analysis, subscriptions, and utility memory. No obvious gaps given its purpose as a data retrieval and analysis server.

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