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Arcgis Orovalley

by io.github.pipeworx-io

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Idempotent

Create a proactive monitoring subscription to a live-data event stream. Returns the new subscription id. Requires a Pipeworx OAuth account (anonymous + BYO cannot persist subscriptions). Supported types: "sec_8k" (8-K filings matching ticker + item codes — e.g. items:["5.02"] = officer change), "polymarket_edge" (Polymarket↔Kalshi cross-venue mispricings — params:{topic:"fed"}), "fred_series" (new FRED observations — params:{series_id:"UNRATE"}). Delivery channels: feed (always on — pull via recent_alerts or GET registry.pipeworx.io/alerts.json), and optionally email (set delivery:{email:"you@x.com"}) or sms (delivery:{sms:"+15551234567"} — phone must be verified at /account first; 10/day cap).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesSubscription type.
paramsYesType-specific filter. sec_8k: {ticker:"AAPL", items?:["5.02","1.01"]}. polymarket_edge: {topic:"fed", min_spread_bps?:500}. fred_series: {series_id:"UNRATE"}. patent_grant: {applicant:"Apple Inc."}. clinical_trial: {sponsor?:"Pfizer", condition?:"lung cancer", phase?:"PHASE3"} (sponsor or condition required).
deliveryNoOptional delivery channels in addition to the always-on persistent feed. {email:"you@x.com"} sends a templated alert per fired event. {sms:"+15551234567"} sends an SMS per event — must match the verified phone on the caller's account (verify at https://pipeworx.io/account first; 10/day cap). {webhook:"https://..."} POSTs each event JSON to your endpoint, HMAC-signed — the response includes delivery.webhook_secret (whsec_…) ONCE; verify X-Pipeworx-Signature = sha256 HMAC of "<X-Pipeworx-Timestamp>.<raw body>". Auto-disabled after 10 consecutive failing runs.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.2/5.0
Behavior1/5

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

The description contradicts the idempotentHint=true annotation. It says 'Returns the new subscription id,' implying each call creates a distinct subscription, which is not idempotent. This is a serious inconsistency. Although the description otherwise richly discloses behaviors (OAuth requirement, SMS cap, webhook auto-disable, secret returned once), the contradiction forces a score of 1.

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 dense but every sentence earns its place. It is front-loaded with the main action and return value, then systematically covers requirements, supported types, and delivery options. No fluff or redundancy.

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 complexity (nested objects, no output schema), the description is exceptionally complete. It covers prerequisites, return value, side effects (persistence), delivery constraints (SMS cap, webhook auto-disable), and even error-prone details like the one-time webhook signing secret. The only issue is the idempotency contradiction, which is a behavioral transparency problem, not a completeness gap.

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

Parameters5/5

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

While the schema covers 100% of parameters, the description adds substantial meaning: it gives concrete examples for each subscription type (e.g., items:["5.02"] = officer change), explains delivery channel requirements (verified phone, 10/day cap), and details webhook HMAC signing. This goes far beyond the schema's basic field descriptions.

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: 'Create a proactive monitoring subscription to a live-data event stream.' It specifies the verb (create), the resource (subscription), and the return value (new subscription id). This distinguishes it from sibling tools like list_subscriptions and unsubscribe.

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 provides explicit prerequisites (requires Pipeworx OAuth account), supported subscription types with examples, and delivery channel details. It also differentiates from pulling via recent_alerts or the public feed, guiding the user on when to subscribe vs. when to pull.

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

A3.9/5.0
Disambiguation3/5

The descriptions are extraordinarily detailed and genuinely differentiate most tools, but the set contains near-clones (ask_pipeworx, ask_pipeworx_beta which is explicitly 'identical' to it, and ask_pipeworx_grounded) plus five polymarket tools whose boundaries (arbitrage vs edges vs edge_tracker vs fill_risk vs kalshi_spread) overlap enough to cause misselection. An agent navigating this surface must read full descriptions to choose correctly, which defeats quick tool selection.

Naming Consistency3/5

Most tools follow a snake_case verb_noun pattern (ask_pipeworx, compare_entities, resolve_entity), but there are clear deviations: bare single-word verbs (remember, recall, forget, subscribe, unsubscribe), prefix-family names (pipeworx_feedback, pipeworx_trending; polymarket_edges, polymarket_fill_risk), and a disjoint ArcGIS trio (layer_info, query_layer, search_datasets) that breaks the dominant convention. It is readable but not predictable across the whole set.

Tool Count2/5

34 tools is far beyond what the 'Arcgis Orovalley' purpose warrants — only 3 tools (search_datasets, layer_info, query_layer) actually relate to GIS, with 31 unrelated tools bolted on covering financial data, prediction markets, memory, subscriptions, and AI visibility. This is a sprawling mega-server where an agent must hold an enormous option set in mind; the surface appears to be several platforms fused together rather than one well-scoped toolset.

Completeness3/5

The genuine ArcGIS surface (search datasets → layer_info → query_layer) is a complete read-only workflow with no dead ends, and the Pipeworx side is impressively comprehensive (routing, grounded answers, research, entity, compare, resolve, validate, memory, subscriptions, feedback). But the tool set as a whole serves no single coherent domain — the declared purpose (ArcGIS Oro Valley data) lacks any write/editing operations, while the majority of the surface addresses unrelated concerns, so 'complete' only applies to one small slice of the 34 tools.

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