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uored

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)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

The description discloses key behavioral traits beyond annotations: key-value scoping by identifier, persistence differences for authenticated (persistent) vs anonymous (24 hours) users, and the relationship with recall/forget. It does not mention overwrite behavior or failure cases, but adds significant context to the idempotentHint and destructiveHint 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 four sentences, each earning its place: purpose, usage guidance, storage/persistence details, and sibling relationships. It is front-loaded with the core function and contains no unnecessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter tool with no output schema, the description covers what to store, when to use it, how persistence works, and how it relates to recall and forget. It lacks edge-case behavior like overwriting or error responses, but these are not critical for basic operation, making it nearly complete.

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 already provides full descriptions for both parameters (key and value) with examples. The description adds general usage context (e.g., value types like findings, addresses, preferences) but does not add significant parameter-level semantics beyond what schema provides. With 100% schema coverage, the baseline 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 tool's function with a specific verb ('Save') and resource ('data the agent will need to reuse later'). It distinguishes from sibling tools by explicitly naming recall and forget as complementary operations, and specifies the cross-session versus within-conversation scope.

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 usage guidance: 'Use when you discover something worth carrying forward' with concrete examples (resolved ticker, target address, user preference). It also explains how to pair with recall and forget. However, it lacks explicit 'when not to use' guidance or comparison with alternative memory strategies, stopping short of a full 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

A3.8/5.0
Disambiguation3/5

Several clusters overlap: the three random-activity tools are near-variants of the same action, ask_pipeworx_beta is currently identical to ask_pipeworx, and discover_tools/suggest_questions both serve capability discovery. The detailed descriptions help agents choose correctly, but the boundaries are not always crisp.

Naming Consistency3/5

All names are snake_case, but conventions are mixed: verb_noun (resolve_entity, discover_tools), bare verbs (remember, subscribe), adjective_noun (recent_alerts, deep_research), and noun compounds (polymarket_edge_tracker, entity_profile). Clusters are internally consistent, but there is no single pattern across the set.

Tool Count2/5

At 34 tools, this exceeds the 25+ threshold and feels bloated. The random-activity trio and the ask_pipeworx stable/beta/grounded trio add redundancy, and several meta-tools could be consolidated. The broad domain scope justifies some of the size, but not all of it.

Completeness3/5

The data query, memory, and Polymarket research surfaces are well covered, but the subscription lifecycle is incomplete: list_subscriptions invites cancellation yet there is no cancel/unsubscribe tool, creating a dead end. Other areas have minor workarounds but no other show-stopping gaps.

Resources