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Arcgis Maricopa

by io.github.pipeworx-io

Send Pipeworx Feedback

pipeworx_feedback

Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a claim_token; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNobug = something broke or returned wrong data. feature = a new tool or capability you wish existed. data_gap = data Pipeworx does not currently expose. praise = positive note. other = anything else.
contextNoOptional structured context: which tool, pack, or vertical this relates to.
messageNoYour feedback in plain text. Be specific (which tool, what error, what data was missing). 1-2 sentences typical, 2000 chars max.
claim_tokenNoRead the reply to a report you filed earlier: pass the `pwfb_…` token that filing returned, with no other arguments. Returns the status and, once resolved, what actually changed.

TDQS

A4.7/5.0
Behavior5/5

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

Discloses rate limiting (5 per identifier per day), cost (free, no quota), the claim_token workflow for anonymous reporting, and the scope restriction to Pipeworx-served tools. Since annotations are all false and provide no behavioral hints, the description fully carries the burden and does so thoroughly.

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?

Every sentence adds value: purpose, use cases, exclusions, formatting guidance, claim_token workflow, rate limit, and cost. The description is dense but appropriately sized for the tool's complexity, with the main purpose front-loaded.

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?

Covers when to use, when not to use, what to provide, what to expect (claim_token and follow-up), and operational limits. With no output schema, the description sufficiently explains the return token mechanism. The tool's complexity is well handled.

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?

The input schema already covers all 4 parameters with detailed descriptions (100% coverage). The description mentions the claim_token workflow but adds little beyond the schema's own explanation, so it does not significantly augment parameter understanding beyond the baseline.

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 imperative ('Tell the Pipeworx team something is broken, missing, or needs to exist') and enumerates the feedback categories (bug, feature/data_gap, praise). It explicitly scopes the tool to this Pipeworx connection, distinguishing it from sibling tools and other MCP servers.

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 'Use when' triggers are provided for bugs, features/data gaps, and praise. The description also gives a clear exclusion: tools from other MCP servers should be reported elsewhere. Additional guidance covers how to frame feedback (in terms of Pipeworx tools/packs) and how to follow up with claim_token.

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
Disambiguation3/5

Many tools have distinct purposes, but there is overlap within the Pipeworx family (ask_pipeworx vs ask_pipeworx_grounded) and Polymarket tools (bet_research, polymarket_edges, etc.). Descriptions are detailed and help differentiate, but the sheer number of tools from different domains can cause an agent to select the wrong one for a given task.

Naming Consistency2/5

Naming is highly inconsistent: some tools follow verb_noun (ask_pipeworx, compare_entities), others are nouns (layer_info, entity_profile), and some have prefixes (pipeworx_trending, polymarket_arbitrage). There is no uniform pattern, making the set feel chaotic.

Tool Count2/5

33 tools is far too many for a server named 'Arcgis Maricopa', which only has 3 GIS-specific tools. The remaining tools are from unrelated domains (polymarket betting, general Pipeworx queries, utilities), making the tool set bloated and unfocused for its stated purpose.

Completeness3/5

For the ArcGIS domain, the set is minimal (only search, schema, and query) and lacks management or analysis tools. However, the broader toolset covers many data domains (finance, drugs, prediction markets), but with gaps like no update/delete operations for the GIS data. The overall coverage is mixed.

Resources