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Glama

radio

by io.github.pipeworx-io

Remember

remember
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. Added

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the annotations (which indicate a non-read-only, idempotent, non-destructive write), the description adds valuable behavioral context: memory is scoped by the agent's identifier, authenticated users get persistent memory while anonymous sessions retain data for 24 hours, and it positions the tool as part of a store/retrieve/delete workflow. These details are not in annotations and significantly enhance transparency.

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 four sentences, front-loaded with the core purpose, then usage context, storage details, and related tools. Every sentence adds essential information without redundancy or excessive length, making it highly scannable and efficient.

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 key-value store with no output schema, the description covers all necessary context: what it does, when to use it, how it's stored (key-value, scoped), persistence behavior, and related tools for retrieval/deletion. Combined with annotations and rich schema, it is fully complete for an agent to invoke 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 description coverage is 100%: both 'key' and 'value' already have clear descriptions in the input schema. The tool description does not add new parameter-level details, merely restating 'key-value pair' and giving usage examples, which aligns with the baseline of relying on schema for parameter info.

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 with a specific verb and resource: 'Save data the agent will need to reuse later'. It distinguishes itself from sibling tools by naming recall and forget as counterparts, and gives concrete examples of keys (resolved ticker, target address, user preference), leaving no ambiguity about its purpose.

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?

The description provides explicit guidance on when to use: 'Use when you discover something worth carrying forward' and lists example scenarios. It also mentions alternatives by pairing with recall for retrieval and forget for deletion, giving clear context without needing to reference sibling descriptions.

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

A3.8/5.0
Disambiguation2/5

Several tools are nearly interchangeable: ask_pipeworx_beta is explicitly identical to ask_pipeworx right now, bet_research overlaps heavily with polymarket_edges and polymarket_arbitrage, and ai_visibility_check vs scan_competitor_ai_presence blur together. Despite detailed descriptions, an agent can easily misselect among these overlapping purpose boundaries.

Naming Consistency3/5

Most names follow a readable verb_noun snake_case pattern (list_countries, search_stations, resolve_entity), but bare verbs like remember/recall/forget and inconsistent prefixes (pipeworx_feedback vs ask_pipeworx, bet_research outside the polymarket_* family) break the pattern. The naming is mixed but still navigable.

Tool Count2/5

35 tools is well into the heavy range, and only 4 of them (get_top_stations, list_countries, list_tags, search_stations) pertain to the server's stated 'radio' purpose. The rest form a sprawling research/prediction-market toolkit, making the server feel like multiple unrelated products fused into one.

Completeness3/5

The radio subset covers basic discovery but misses station detail, genre filtering, and stream URLs, an obvious gap for the named domain. The broader Pipeworx/Polymarket suite is expansive with discovery and grounding tools, but remains uneven with no direct per-source browsing and only read-only prediction-market access.

Resources