Skip to main content
Glama

Gaming Feeds

by io.github.pipeworx-io

Discover Tools

discover_tools
Read-onlyIdempotent

Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for query.
taskNoAlias for query.
limitNoMaximum number of tools to return (default 20, max 50)
queryYesNatural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries"). Accepts task, q, description, search as aliases.
searchNoAlias for query.
descriptionNoAlias for query.

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already indicate safe, idempotent, non-destructive behavior. The description adds that it returns top-N relevant tools with full schemas and examples, ready to call without a second lookup. No contradictions 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single paragraph that front-loads the purpose and is fairly concise. It could be slightly tighter but contains no filler.

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?

Given the tool's complexity (6 params, no output schema), the description covers purpose, usage, return format (top-N tools with schemas and examples), and domain examples. It is fully complete for effective use.

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%, so the description adds minimal value beyond the schema. It repeats the alias info and mentions limit defaults, but these are already in the schema. The baseline 3 is appropriate.

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 purpose: 'Find tools by describing the data or task.' It lists many example domains and explicitly says to call this first when many tools are available, differentiating it from sibling tools that execute tasks rather than discover them.

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 says 'Use when you need to browse, search, look up, or discover what tools exist' and 'Call this FIRST when you have many tools available.' It provides clear context but does not explicitly state when not to use or name alternatives beyond implying the sibling tools are used after discovery.

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

All Gaming Feeds toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0
Disambiguation3/5

Most tools have distinct purposes, but there is notable overlap among ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research—all of which route questions to the same underlying catalog. The polymarket_* family also has several opportunity-scanning tools (edges, arbitrage, bet_research) that agents could confuse without reading the long descriptions carefully.

Naming Consistency5/5

All 34 tool names use lowercase snake_case with a clear verb-first or noun-descriptive pattern (list_feeds, read_feed, remember, resolve_entity, polymarket_arbitrage). Even compound names like ai_visibility_check and ask_pipeworx_grounded follow a predictable, consistent style. No mixed conventions or camelCase deviations.

Tool Count2/5

34 tools is far more than the apparent 'Gaming Feeds' scope suggests—only list_feeds, read_feed, and fetch_feed actually relate to gaming feeds. The rest form a sprawling data-research and prediction-market suite, creating a severe mismatch between the server name and its actual tool surface.

Completeness4/5

Viewed as a general Pipeworx data-access platform, the tool set is quite complete: question routing, grounded answers, entity resolution, profiles, comparisons, claim validation, memory, subscriptions, alerts, feed reading, and tool discovery are all covered. The only notable gaps are feed management (no create/update/delete for custom feeds) and a few odd add-ons like generate_llms_txt that feel outside the core domain.

Resources