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Nyc Parks

by io.github.pipeworx-io

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Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

TDQS

A4.9/5.0
Behavior5/5

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

Discloses behavioral traits beyond annotations: scoped by identifier, persistence differences (authenticated vs anonymous), and retention period (24 hours). Annotations give idempotentHint=true, and description adds that repeated saves are safe, with no contradiction.

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?

Three sentences, no fluff. First sentence states purpose, second gives usage context, third explains behavioral details. Every sentence earns its place.

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?

Despite no output schema, description is complete: covers purpose, usage, behavioral details (scoping, persistence, retention), and pairing with siblings. No gaps for this write-only 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 coverage is 100% with clear parameter descriptions. Description adds extra context by calling it a 'key-value pair' and mentioning scoping, justifying an above-baseline score.

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?

Description uses specific verb 'Save' and resource 'data' and clearly states purpose: 'data the agent will need to reuse later'. It distinguishes from sibling tools like 'recall' and 'forget' by mentioning them explicitly.

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?

Provides explicit when-to-use guidance: 'when you discover something worth carrying forward' and lists examples. Also tells when not to use by mentioning alternatives: 'Pair with recall to retrieve later, forget to delete.'

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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