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Glama

Fac

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?

Annotations already indicate read-only, idempotent, non-destructive. The description adds scoping detail ('Scoped to your identifier') and clarifies that omitting the key lists all saved keys, going beyond bare 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?

Three sentences covering purpose, examples, scoping, and pairing with siblings. No redundant words; front-loaded with the main action.

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?

Lacks explicit return format description but adequately covers retrieval and listing behavior given no output schema. The use cases provide enough context for an agent to understand expected outputs.

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% and the description adds value by explaining behavior when the parameter is omitted (list all keys), which is not inferred 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's function: retrieve a value saved via remember, or list all keys when the argument is omitted. It uses specific verbs and distinguishes from sibling tools 'remember' and 'forget' by mentioning pairing.

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 explicit use cases (looking up stored context like ticker, address, notes) and explains when to omit the key argument. Does not explicitly exclude scenarios, but the context is clear enough for an agent to decide when to use it.

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 tools occupy the same "answer a factual question" niche: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, validate_claim, and bet_research all route to the same underlying catalog, so an agent must parse subtle differences to pick correctly. scan_competitor_ai_presence also wraps ai_visibility_check, adding another near-duplicate. The detailed descriptions help, but the boundaries are genuinely fuzzy.

Naming Consistency3/5

The set mixes several conventions: fac_*, polymarket_*, and pipeworx_* prefixes coexist with bare verbs (remember, recall, forget, subscribe, unsubscribe) and noun phrases (entity_profile, recent_changes, bet_research). ask_pipeworx_beta/grounded use a suffix pattern while pipeworx_feedback/trending use a prefix, so there is no single predictable scheme. Still, most names are readable and describe what they do.

Tool Count2/5

36 tools is well above the 25+ threshold and creates a heavy surface for any client to load and reason about. The broad data-platform scope explains some of the count, but many tools are meta-variants of the same query/research capability rather than genuinely distinct operations.

Completeness4/5

For the server's apparent purpose—authoritative data lookup, research, prediction-market analysis, and account/feed management—the surface covers the core lifecycle: query, entity resolution, profiles, comparisons, recent changes, claim verification, subscriptions, alerts, and memory. Minor gaps exist (no direct tool to fetch a pipeworx:// citation URI; no raw per-pack access), but most workflows are supported.

Resources