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Arcgis Chapelhill

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

A4.5/5.0
Behavior5/5

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

The description discloses significant behavioral context beyond annotations: the OAuth account requirement, phone verification for SMS, 10/day SMS cap, and webhook auto-disable after 10 consecutive failures. It also clarifies that feed is always on. These details complement the annotations (idempotentHint true, readOnlyHint false) without contradiction, providing a rich operational picture.

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 a single dense paragraph but front-loaded with the core purpose. Each sentence contributes details on types, requirements, or delivery options. The length is justified by the tool's complexity, though it could be broken into bullets for easier scanning.

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 rich schema and annotations, the description covers the essential aspects: purpose, types, prerequisites, delivery channels, and limits. It omits webhook as a delivery channel in the main prose (though schema covers it extensively) and does not specify the full response shape beyond the subscription id, but this is acceptable since no output schema exists and the tool is relatively straightforward.

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%, but the description adds interpretative value, e.g., items:['5.02'] = officer change for sec_8k, and provides concrete parameter examples for each type (topic:'fed', series_id:'UNRATE'). While much of this overlaps with the schema's per-type params descriptions, the example meanings enhance semantic clarity.

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 action ('Create a proactive monitoring subscription') and resource ('live-data event stream'), with explicit mention of the return value ('Returns the new subscription id'). It distinguishes itself from siblings like list_subscriptions and unsubscribe by focusing on creation and enumerating supported subscription types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on when to use the tool, including prerequisites (requires OAuth account), supported subscription types with examples, and delivery channels. It implicitly differentiates from alternatives by noting how to pull the feed (via recent_alerts or GET registry.pipeworx.io/alerts.json), but it does not explicitly state when not to use this tool or name alternative tools for one-time queries.

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
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx and ask_pipeworx_beta are currently literally identical, and the polymarket_* family (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_kalshi_spread, polymarket_edge_tracker) all orbit the same prediction-market opportunity space. The descriptions are detailed and do help, but the sheer number of near-synonymous entry points makes misselection likely.

Naming Consistency4/5

The vast majority of tools follow a consistent snake_case, verb-first pattern: ask_pipeworx, compare_entities, query_layer, resolve_entity, search_datasets, validate_claim. Minor deviations exist — the polymarket_* tools are noun-phrase style and a few names like entity_profile, layer_info, and ai_visibility_check are noun-led — but the overall style is uniform enough to be predictable.

Tool Count2/5

34 tools is already in the overstuffed range, but the bigger problem is that only 3 of them (search_datasets, layer_info, query_layer) relate to the server's stated ArcGIS/Chapel Hill identity. The other 31 tools appear to be an unrelated Pipeworx data-research, prediction-market, memory, and subscription bundle merged into this server, making the count grossly disproportionate to the apparent purpose.

Completeness2/5

The three GIS tools form a usable read-only search → schema → query workflow, so the ArcGIS domain is not completely absent. However, as a whole the server has no coherent domain to be complete for, and the ArcGIS side lacks broader capabilities like layer enumeration, spatial filters/statistics, or any write/edit operations. For a server named Arcgis Chapelhill, having 31 out-of-scope tools constitutes a major completeness failure.

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