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Glama

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. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "key": "user_research_topic"
      +  },
      +  {}
      +]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

While annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, the description adds valuable context: the ability to list all keys when key is omitted, and that storage is scoped to the user's identifier (anonymous IP, BYO key hash, or account ID). This goes beyond the annotations without contradicting them.

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 three sentences long and front-loaded with the core function in the first sentence. The subsequent sentences add usage context, scope, and related tools without redundancy. Every sentence earns its place.

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 tool with one optional parameter and no output schema, the description covers the main behaviors, use cases, and scope. It could mention return value details or behavior on missing keys, but the description is sufficient for a tool of this complexity, especially given the strong annotations.

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 schema already describes the key parameter fully ('Memory key to retrieve (omit to list all keys)'). The description essentially restates this behavior in prose, so it does not add meaningful new meaning beyond the schema. Schema coverage is 100%, so the baseline of 3 applies.

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 previously saved via remember, or list all saved keys (omit the key argument).' This is specific with a verb (retrieve/list) and resource (saved memory), and it naturally distinguishes itself from sibling tools like remember 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 Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It says 'Use to look up context the agent stored earlier' and suggests pairing with remember to save and forget to delete, giving clear context and alternatives. However, it does not explicitly state when not to use this tool, so it stops short of a perfect 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

B3.1/5.0
Disambiguation2/5

Several tools occupy overlapping boundaries: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-duplicate query entry points (beta is currently identical), while ladder/standings, ai_visibility_check/scan_competitor_ai_presence, and polymarket_edges/polymarket_arbitrage also blur together. An agent would struggle to reliably pick the right tool without reading very long descriptions.

Naming Consistency4/5

The vast majority of names are snake_case and many follow a readable verb_noun shape, such as resolve_entity, validate_claim, and list_subscriptions. However, the Squiggle/AFL tools are bare nouns (games, ladder, sources, standings, teams, tips), and the polymarket_* / pipeworx_* prefixes do not use one consistent verb style, so it is not a fully uniform convention.

Tool Count2/5

37 tools is in the too-many band, and the sprawl is compounded by mixing unrelated domains under one server: AFL stats, a huge Pipeworx data-routing layer, prediction-market analytics, AI visibility checks, npm dependency review, and llms.txt generation. The set feels like several merged servers rather than one well-scoped MCP.

Completeness3/5

The query/research surface is broad and covers many subdomains, and the subscription lifecycle is reasonably complete with subscribe/list/unsubscribe/recent_alerts. However, pipeworx:// citation URIs are prominently returned but no tool fetches a cited record directly, the AFL side lacks player-level data, and subscriptions cannot be updated.