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by io.github.pipeworx-io

Recall

recall
Read-onlyIdempotent

Retrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous IP, BYO key hash, or account ID). Pair with remember to save, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyNoMemory key to retrieve (omit to list all keys)

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?

Description reinforces read-only nature beyond annotations (readOnlyHint, idempotentHint) by emphasizing retrieval and listing. Adds scoping and pairing details, 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.

Conciseness5/5

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

Three sentences, no wasted words. Front-loaded with primary action, then usage context, then scoping. Highly efficient.

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?

Covers purpose, usage, scoping, and sibling pairing. No output schema but return value is implied. Could mention return format but not essential given simplicity.

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?

Schema coverage is 100%, description adds meaning by clarifying that omitting the key lists all saved keys, which is not obvious from the schema alone.

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 retrieves a saved value or lists all keys, with specific verb and resource. It distinguishes from siblings 'remember' and 'forget' explicitly.

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?

Provides context on when to use (look up stored context like ticker or notes) and pairs with remember/forget. Lacks explicit when-not-to-use but sufficient for most agents.

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

Most tools have distinct, well-scoped purposes, but several question-answering/research tools sit close together: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim can all be selected for factual questions. The descriptions are detailed enough to reduce ambiguity, but ask_pipeworx_beta is currently identical to ask_pipeworx, and discovery helpers like discover_tools, suggest_questions, and pipeworx_trending also overlap somewhat.

Naming Consistency4/5

Names are uniformly snake_case and mostly follow a verb_noun pattern such as build_url, list_subscriptions, resolve_entity, and validate_claim. The polymarket_* and pipeworx_* prefixes form a readable convention, though a few names like pipeworx_feedback and polymarket_arbitrage are noun-phrases rather than verb-first actions.

Tool Count2/5

34 tools is well past the 25+ threshold where even a broad platform starts to feel bloated. The set mixes data research, prediction-market tooling, URL utilities, memory, subscriptions, feedback, and npm scanning, which would be more coherently split across focused servers.

Completeness3/5

The core research workflows are thoroughly covered: routing, grounded answers, deep research, entity resolution, comparisons, claim validation, discovery, alerts, and memory all exist. However, the URL utility and dependency-scanning side domains feel tacked on and incomplete, and there is no dedicated tool to fetch an arbitrary pipeworx:// citation record even though such URIs are returned throughout.

Resources