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Glama

Deezer

by io.github.pipeworx-io

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Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

The description adds significant behavioral context beyond annotations: key-value store scoped by identifier, persistence duration (24 hours for anonymous), and idempotent behavior (overwriting same key). No contradiction with 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?

The description is extremely concise—three sentences, no wasted words. It front-loads the core purpose and then provides specific usage guidance and behavioral details efficiently.

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?

For a simple tool with two string parameters and no output schema, the description covers all necessary context: purpose, usage, behavior, persistence, and relationship with siblings. Nothing is missing.

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 description coverage is 100%, so the baseline is 3. The description provides meaningful examples of keys (e.g., 'subject_property', 'target_ticker') that help the agent understand parameter usage, adding value beyond the schema.

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 identifies the tool's purpose: 'Save data the agent will need to reuse later.' It provides specific examples of when to use (resolved ticker, target address, user preference) and distinguishes from sibling tools like 'recall' 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 Guidelines5/5

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

Explicit usage guidance is given: 'Use when you discover something worth carrying forward.' It also explains when to pair with 'recall' and 'forget,' and clarifies persistence differences between authenticated and anonymous sessions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Deezer toolsInspect
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TDQS

B3.2/5.0
Disambiguation2/5

Many tools overlap in purpose (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research all route queries to structured data), and the set mixes Deezer music tools with an unrelated Pipeworx/Polymarket suite. An agent would struggle to pick the right tool for a given request.

Naming Consistency2/5

Naming is mixed: single-word nouns (album, artist, track, chart), verb_noun snake_case (list_subscriptions, resolve_entity), and verbose multi-concept names (scan_competitor_ai_presence, polymarket_kalshi_spread). No consistent pattern across the set.

Tool Count1/5

37 tools for a server named 'Deezer' is far beyond a music API scope; the overwhelming majority are unrelated data-research, prediction-market, and utility tools. This is an extreme mismatch between the server name and the tool surface.

Completeness2/5

For the Deezer music domain, the surface is incomplete (no playlists, user library, lyrics, or radio), while the many unrelated tools each cover only fragments of their domains. The overall set lacks coherent coverage of any single purpose.

Resources