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Un Sdg

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

A4.6/5.0
Behavior5/5

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

The description adds significant behavioral context beyond annotations: key-value scoping by identifier, persistent memory for authenticated users, 24-hour retention for anonymous sessions. No contradictions with annotations (idempotentHint=true, destructiveHint=false).

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?

Five sentences, each adding value. Purpose is front-loaded, followed by usage and behavioral details. Could be slightly more concise, but all content is relevant and well-structured.

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 memory tool with 2 parameters, no output schema, and clear annotations, the description covers purpose, usage, behavior, and sibling relationships completely.

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 coverage is 100% with clear descriptions for key and value. The description reinforces the key-value pair concept and provides examples, but does not add substantial new semantics beyond the 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 clearly states the tool's purpose: 'Save data the agent will need to reuse later.' It specifies concrete use cases (resolved ticker, target address, user preference, research subject) and distinguishes from siblings by naming 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 tells when to use: 'when you discover something worth carrying forward.' It also explains that storing avoids re-lookup and mentions pairing with recall and forget, providing clear context and alternatives.

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
Disambiguation3/5

Several tools occupy overlapping territory: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research are all query routers, and the six Polymarket tools have closely related purposes. The descriptions are unusually detailed and do help, but an agent could still easily pick the wrong entry point.

Naming Consistency4/5

Almost all tools follow a clean lower_snake_case convention with recognizable prefixes like list_, ask_pipeworx, and polymarket_. A few names like entity_profile, recent_changes, and recent_alerts are noun phrases rather than verb-first, but the overall pattern is predictable and readable.

Tool Count2/5

36 tools is well above the threshold where a server starts to feel bloated, and many are variants of the same underlying query/research capability. This appears to be a full platform surface rather than a focused server, which creates a heavy and confusing toolset for agents to navigate.

Completeness4/5

The SDG-specific portion is reasonably complete: goals, indicators, series, geographic areas, and data retrieval are all covered. The broader Pipeworx layer also covers querying, grounded answers, deep research, entity comparisons, prediction markets, subscriptions, and memory, with only minor gaps such as no batch SDG data fetch or full-text indicator search.

Resources