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Public Suffix List

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

A4.3/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint, idempotentHint, and destructiveHint. The description adds value by stating that results are 'ready to call directly, no second schema lookup needed,' and that it returns top-N tools. No contradictions. Could mention rate limits or pagination, but not needed for this tool.

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 front-loaded with purpose and usage, then return details. It is slightly verbose with a long list of domains, but every sentence adds value. Could be trimmed slightly without loss, but overall well-structured.

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 the complexity (6 parameters, 100% schema coverage, no output schema), the description covers purpose, usage, and return format. It explains that results include names, descriptions, and schemas. Complete enough for an agent to understand when and how to use it.

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%, so baseline is 3. The description mentions 'query' as a natural language description and provides examples, but does not add significant meaning beyond the schema's parameter descriptions (which already define aliases and limit). The examples in the schema enhance understanding.

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 numerous domains and explains that it returns top-N relevant tools with full schemas. This distinguishes it from sibling tools like 'deep_research' or 'search_within' which focus on data rather than tool discovery.

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 guidance: 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' This tells the agent when to use the tool and implies it should be used before narrowing down to specific tools. No alternatives are listed, but the scope is clear.

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

All Public Suffix List toolsInspect
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TDQS

C2.9/5.0
Disambiguation2/5

Multiple tools serve overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all query data in similar ways. Prediction market tools (bet_research, polymarket_arbitrage, polymarket_edges, etc.) are numerous and confusingly similar. Agents will struggle to choose the right tool.

Naming Consistency2/5

Tool names follow no consistent pattern. Some use snake_case like ai_visibility_check, others are generic single words (parse, remember, forget). There is no uniform verb_noun structure, mixing descriptive names (entity_profile) with vague ones (list_version).

Tool Count3/5

35 tools is a large set for a server named 'Public Suffix List', but the actual domain (comprehensive data platform) may justify many tools. However, the count feels heavy for the apparent scope of the server, with many niche prediction market tools.

Completeness4/5

The tool surface covers a wide range: data query, comparison, subscription, memory management, and claim verification. However, there are gaps in data modification (no update/delete for records) and some prediction market features have no direct counterparts. Overall, the set is fairly complete for its data-fetching purpose.

Resources