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Nyc Parks

by io.github.pipeworx-io

What Can I Ask Pipeworx?

suggest_questions
Read-onlyIdempotent

What can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed example questions (company financials, drugs & clinical trials, economics, real estate, prediction markets, weather, government & patents, science & academia, news) — each with the exact tool + argument shape that answers it, drawn from the live catalog of thousands of tools. Call with no arguments for the full spread, or pass topic (e.g. "finance", "pharma", "betting") to focus. Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools (ask_pipeworx, entity_profile, compare_entities, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoOptional focus area: finance | pharma | economics | real-estate | betting | weather | government | science | news. Omit for a cross-category spread.

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint. Description adds context: it's non-destructive, returns example questions with tool shapes, and lists topics. Adds value 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?

Description is slightly long but well-structured: starts with synonyms, then explains output, then usage. Front-loaded with purpose. No wasted sentences, but could be slightly more concise.

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 1 optional param and no output schema, description covers purpose, parameters, usage, and output nature (category-bucketed examples with tool calls). Annotations provide safety profile. Complete for a discovery tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 1 optional param with description. Description adds meaning by listing possible topic values (finance, pharma, etc.) and explaining default behavior. Schema coverage is 100%, but description enhances 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 returns example questions categorized by topics, with specific verbs like 'suggest' and 'returns'. It distinguishes from siblings by being the onboarding entry point, and provides a list of topics.

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 'Use this FIRST when you do not yet know what Pipeworx can do for you', and explains when to pass topic vs. no arguments. Provides clear context for when to use this tool.

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

All Nyc Parks toolsInspect
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TDQS

A3.8/5.0
Disambiguation2/5

The ask_pipeworx/ask_pipeworx_beta/ask_pipeworx_grounded trio are functionally near-identical to an agent (the beta is explicitly described as currently identical to stable), and the five polymarket_* tools (edges, arbitrage, edge_tracker, fill_risk, kalshi_spread) have heavily overlapping concerns around finding and validating prediction-market edges. The descriptions are detailed, but the boundaries require careful reading to pick correctly.

Naming Consistency4/5

All tools use snake_case and mostly follow a verb-first or noun-phrase convention, with recognizable family prefixes (ask_pipeworx_*, polymarket_*, pipeworx_*) that aid navigation. Minor deviations exist — bare nouns like categories and events, and the inconsistent verb placement in bet_research vs. validate_claim — but the overall pattern is predictable.

Tool Count1/5

33 tools is already heavy, but the fatal problem is that the server is named 'Nyc Parks' while ~31 of 33 tools are a generic Pipeworx data-retrieval/prediction-market toolkit. The count is egregiously mismatched to the stated purpose; only 2 tools relate to NYC Parks at all.

Completeness2/5

For the server's literal name, the surface is severely incomplete: categories and events exist, but there is no way to look up parks, facilities, permits, or event details, and no CRUD-lifecycle coverage. Viewed as a Pipeworx data toolkit the surface is quite thorough, but that is not what the server claims to be, so the stated NYC Parks domain is barely covered and creates dead ends.

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