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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. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the bar is lower. The description adds valuable context beyond annotations by explaining scoping to the agent's identifier (anonymous IP, BYO key hash, or account ID) and the relationship with remember/forget. It does not detail return format, but for a read-only lookup that is acceptable.

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, front-loaded with the core action, and adds usage context, scoping, and tool relationships without any fluff. Every sentence contributes meaning and no repetition of structured data exists.

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 is nearly complete. It covers purpose, usage, scoping, and tool relationships. It stops short of describing the exact return value format, but the examples make the expected output clear enough for an agent to select and invoke the tool correctly.

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?

Schema coverage is 100% and the parameter description already explains omitting the key to list all keys. The main description adds illustrative examples of what keys might contain, but this is supplemental rather than essential. The baseline of 3 is appropriate when the schema carries the parameter semantics.

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 uses specific verbs 'retrieve' and 'list' with a clear resource (previously saved values/keys) and distinguishes itself from sibling tools by referencing 'remember' and 'forget'. It also provides concrete examples of stored content (ticker, address, research notes), making the purpose unmistakable.

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 clearly states when to use the tool: to look up context the agent stored earlier 'without re-deriving it from scratch', which is an explicit usage context. It also relates to siblings (remember, forget) but does not explicitly state alternatives or when not to use it, leaving a small gap.

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

A3.6/5.0
Disambiguation2/5

Several tool clusters have blurred boundaries: ask_pipeworx_beta explicitly states it currently matches ask_pipeworx exactly, making them indistinguishable, and the five Polymarket tools (polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, bet_research, polymarket_kalshi_spread) all target prediction-market opportunities with overlapping concerns. The meta-tools (discover_tools, suggest_questions, pipeworx_trending) and entity tools (entity_profile, compare_entities, recent_changes) are better separated by their descriptions, but the identical beta/stable pair alone forces a low score.

Naming Consistency3/5

All tool names use snake_case, but the naming conventions are mixed: some follow verb_noun (describe_cron, next_runs, validate_claim), some are bare verbs (remember, recall, forget), and many are brand-prefixed noun phrases (ask_pipeworx, pipeworx_trending, polymarket_edges, bet_research). The pattern is readable and mostly predictable by prefix/domain, but there is no single consistent convention across the set.

Tool Count2/5

33 tools is above the reasonable threshold for a focused server, and the count is especially disproportionate for a server named 'Crontab': only 2 tools (describe_cron, next_runs) actually deal with cron, while roughly 24 tools are Pipeworx data-query, prediction-market, and memory utilities unrelated to the server's apparent purpose. The bulk of the tool surface feels like it belongs on a different server, making the count mismatched with the stated scope.

Completeness2/5

For a cron-focused server, the surface is incomplete: it can describe cron expressions and compute next runs, but has no tool to create, update, or delete a scheduled cron job — subscribe/unsubscribe manage data-event subscriptions, not cron schedules. The Pipeworx data side is broad (lookup, grounded verification, entity profiles, comparisons, research), but that completeness belongs to a different domain and does not rescue the cron purpose implied by the server name.