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Glama

Data Pa

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

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint. The description adds valuable context about scoping (anonymous IP, BYO key hash, account ID) and pairing with siblings, going beyond annotations without contradiction.

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?

Two sentences, front-loaded with core purpose, no wasted words. Every sentence adds value.

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 (one optional parameter, read-only), with annotations covering safety, the description fully addresses what an agent needs: purpose, usage, scoping, and relationship to siblings.

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% for the single parameter 'key'. The description explains that omitting key lists all keys, adding semantic meaning not present in the schema's description.

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 it retrieves a value saved via remember or lists all keys when key is omitted. It distinguishes itself from siblings remember (save) and forget (delete) by explicitly pairing with them.

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?

Provides explicit when-to-use (look up context stored earlier) and when-not (omit key to list all). Mentions pairing with remember/forget and scoping by identifier, offering clear guidance on 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
Disambiguation2/5

Several clusters blur together: ask_pipeworx, ask_pipeworx_beta (explicitly identical today), and ask_pipeworx_grounded share routing, while discover_tools/suggest_questions and the Polymarket edge/arbitrage/fill-risk tools have overlapping discovery purposes. Rich descriptions reduce some confusion, but an agent must read carefully to avoid misselection.

Naming Consistency3/5

Most names are lowercase snake_case, but there is no consistent verb_noun pattern: ask_pipeworx/beta/grounded and polymarket_* are domain-prefixed, entity_profile/recent_changes are noun phrases, and query/metadata/remember are bare verbs or nouns. The naming is still readable and subfamilies share prefixes, so it is mixed rather than chaotic.

Tool Count2/5

34 tools is above the comfortable range for a single MCP server, and several could be folded together (the beta variant, visibility checks, and Polymarket scanners). The breadth reflects a large platform, but the surface feels heavy for an agent to select from confidently.

Completeness4/5

The query side is strong: PA Open Data has datasets/metadata/query coverage, and Pipeworx provides ask, deep_research, entity_profile, compare, recent_changes, validate_claim, plus subscriptions and memory with lifecycle coverage. Minor gaps: descriptions promise resolvable pipeworx:// citations but no resource/read tool is exposed, and there is no direct way to fetch an arbitrary record by citation.

Resources