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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

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and the description is consistent. Beyond that, the description discloses useful behavioral traits: it returns top-N relevant tools with 'names, descriptions, and full input schemas (with curated examples)' and notes 'each result is ready to call directly, no second schema lookup needed.' This adds meaningful context about return format and latency savings.

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 concise yet comprehensive, covering purpose, domain scope, return format, and usage timing in three sentences. It front-loads the core verb and object while avoiding redundant filler. Every sentence serves a distinct function: what it does, what it returns, when to call it.

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 moderate complexity and absence of output schema, the description fully covers what an agent needs: it explains the return payload (top-N tools with schemas/examples) and the 'ready to call directly' benefit. Annotations cover safety, and the alias system is documented in the schema, so the description is complete for effective selection and invocation.

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% with detailed parameter descriptions and examples, so the baseline is 3. The description adds minimal parameter-level detail beyond the schema, though 'top-N' hints at the limit parameter. Since all parameters (including aliases) are already well documented, no additional compensation is needed.

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 opens with a clear verb+resource statement: 'Find tools by describing the data or task.' It lists many specific domains (SEC filings, FDA drugs, etc.), making the scope explicit. This clearly distinguishes it from sibling data-specific tools by positioning it as the discovery/search tool for the option set.

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 states exactly when to use this tool: 'Use when you need to browse, search, look up, or discover what tools exist.' It also gives explicit prioritization: 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' This provides strong guidance without naming specific alternatives, which is appropriate given the broad sibling list.

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

A3.5/5.0
Disambiguation2/5

Several tool groups overlap heavily: the three ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) differ mainly in guarantees, and six Polymarket tools (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) all target the same trading-concept space with fuzzy boundaries. While ArcGIS, memory, and subscription tools are distinct, an agent will frequently struggle to pick the right research or analysis tool.

Naming Consistency2/5

All names are snake_case, but the structural pattern is inconsistent. Some are verb-first (query_layer, search_datasets, validate_claim), others are noun-first or domain-prefixed (entity_profile, layer_info, polymarket_edges, recent_alerts, pipeworx_feedback). There is no predictable verb_noun convention across the set, making it hard to guess a tool's name from its function.

Tool Count2/5

At 34 tools, the set is well above the typical focused-server range, and the server name 'Arcgis Eagan' suggests a narrow GIS purpose while only 3–4 tools are actually ArcGIS-related. The remaining ~30 tools form a broad, unrelated utility collection (Pipeworx data, memory, subscriptions, trending, npm scanning), making the count feel bloated and unfocused.

Completeness2/5

For the primary ArcGIS domain, only search, layer inspection, and querying are supported — there are no create, update, delete, or editing tools, leaving obvious lifecycle gaps. Meanwhile, the Pipeworx side is over-stocked with redundant analysis tools, and the overall mix lacks a coherent coverage story for any single stated purpose.