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Met No

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

A4.7/5.0
Behavior4/5

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

Annotations already indicate idempotent and non-destructive behavior. The description adds valuable context: key-value storage scoped by identifier, persistence for authenticated users, 24-hour retention for anonymous sessions. This goes beyond annotations but stops short of explaining overwrite semantics.

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?

Three sentences, front-loaded with primary purpose, then use case, then technical details. No filler, every sentence contributes essential information. Structure is logical and efficient.

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 two-parameter memory tool with annotations and no output schema, the description covers the purpose, usage, persistence behavior, and relationships with recall/forget. It is complete and leaves no critical gaps.

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?

The schema already documents both parameters with examples and descriptions (100% coverage). The description adds semantic meaning by explaining the key-value concept and the scoping by identifier, enriching the understanding of how the parameters are used together.

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' and the resource 'data the agent will need to reuse later', with concrete examples like 'resolved ticker' and 'user preference'. It also distinguishes this from sibling tools by pairing with 'recall' and 'forget', making the purpose unambiguous.

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 'Use when you discover something worth carrying forward' and provides examples. It also names the companions 'recall' and 'forget' as alternatives, giving clear direction on when to use this tool versus related tools.

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

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, but there is some overlap among closely related ones (e.g., ask_pipeworx, ask_pipeworx_grounded, deep_research; multiple Polymarket tools). Descriptions are detailed enough to differentiate, but an agent might still misselect on subtle differences.

Naming Consistency4/5

Names consistently use lowercase with underscores, but no strong verb_noun pattern. Some are noun-based (airquality, nowcast), others verb-based (ask_pipeworx, compare_entities). This is readable but not perfectly predictable.

Tool Count4/5

35 tools is high but justified by the server's broad scope (data queries, betting analysis, weather, memory, subscriptions). The number feels appropriate given the comprehensive functionality described.

Completeness5/5

The tool set covers an impressively wide range of capabilities: data querying with multiple modes, entity profiling, comparisons, search, betting analysis, weather, memory, subscriptions, and feedback. Missing features (e.g., updating memories) are minor; the surface is remarkably complete.

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