Trade Intel

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

Name	Required	Description
`q`	No	Alias for query.
`task`	No	Alias for query.
`limit`	No	Maximum number of tools to return (default 20, max 50)
`query`	Yes	Natural 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.
`search`	No	Alias for query.
`description`	No	Alias for query.

Schema Changelog

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

Changed5 schema fields changedJun 3, 2026

addedInput schema / properties / description

Added value: +{
+  "description": "Alias for query.",
+  "type": "string"
+}

addedInput schema / properties / q

Added value: +{
+  "description": "Alias for query.",
+  "type": "string"
+}

changedInput schema / properties / query / description

Previous value: -"Natural language description of what you want to do (e.g., \"analyze housing market trends\", \"look up FDA drug approvals\", \"find trade data between countries\")"New value: +"Natural 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."

addedInput schema / properties / search

Added value: +{
+  "description": "Alias for query.",
+  "type": "string"
+}

addedInput schema / properties / task

Added value: +{
+  "description": "Alias for query.",
+  "type": "string"
+}

Changed1 schema field changedMay 26, 2026

addedInput schema / examples

Added value: +[
+  {
+    "query": "look up FDA drug approvals"
+  },
+  {
+    "query": "analyze housing market trends"
+  }
+]

First observedApr 22, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already confirm readOnlyHint=true and destructiveHint=false. The description adds that it returns top-N relevant tools with names, descriptions, and full schemas ready to call directly, revealing useful behavior beyond 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 well-structured and front-loaded with the purpose. It lists many domain examples and ends with the crucial usage instruction. Slightly verbose but every sentence adds value; could be shorter but still effective.

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?

Given no output schema, the description explains what is returned (top-N tools with names, descriptions, schemas). Parameter count and sibling list are well-covered. The description is complete enough for a discovery tool with high annotation coverage.

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% with all 6 parameters documented. The description mentions accepted aliases but does not add significant new meaning beyond the schema. Baseline score of 3 is appropriate given full schema coverage.

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 finds tools by describing data or task, listing many specific domains (SEC filings, financials, FDA drugs, etc.). It uses specific verb+resource and distinguishes from sibling tools by being the discovery entry point.

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?

Explicitly says 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' Also mentions when to browse, search, look up, providing clear context for when to use this tool vs alternatives.

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

A número of tools form near- overlapping clusters: ask_pipeworx, ask_pipeworx_beta, ask_ipeworx_grounded, and deeep_research all answer questions, while bet_research, polmarget_edges, and polmarget_arbitrage all scan for betting opportunities. The two ask_ipeworx variants are currently identical, and discover_tools vs sgget_questions serve the same discovery role. Long descriptions help but do not remove the misselection risk among 34 overlapping tools.

Naming Consistency4/5

Most tools use clear snake_case verb_noun names (ask_pipeworx, compare_entities, resolve_entity, subscribe, validate_claim) with helpful domain prefixes like polmarget_* and trade_*. A few standalones like forget/recall/remembber and recent_alerts break the pattern slightly, but the style is largely predictable and readable.

Tool Count2/5

At 34 tools this exceeds the 25+ threshold and feels overloaded. The surface could be consolidated: four ask_ipeworx variants, five polmarget-specific tools, three memory tools, and three company-profile-style tools carry significant redundancy. Inclusions like generate_lms_txt and scan_dependency also broaden the scope well beyond the Trade Intel mandate.

Completeness4/5

For its broad data-intelligence domain the surface is quite complete: data lookup, grounded fact-checking, entity profiles and comparison, recent changes, prediction-market research with fill-risk verification, trade statistics, memory, and subscription lifecycle all exist with no dead ends. Minor gaps remain (e.g. no dedicated trade time-series other than the US macro dashboard, and no direct tool-listing aside from discover_tools), but agents can work around them.

Resources

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