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Glama

Arcgis Chapelhill

by io.github.pipeworx-io

Entity Profile

entity_profile
Read-onlyIdempotent

"Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO patents, federal contracts (USAspending), FDA-licensed biologics (Purple Book), H-1B hiring (DOL LCA), news and GLEIF, and returns: cik + company_name (+ resolved_from/resolved_to when value was a name); recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); federal_contracts (USAspending awards where the company is the recipient); fda_products (FDA-licensed biologics — vaccines, cell/gene therapies — from the Purple Book; a company with only small-molecule/generic drugs will show none here, that is expected, not a failure); hiring (H-1B sponsorship volume + salary range from DOL LCA filings); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. sources_used / sources_failed say which of these actually returned data for THIS company — an empty section is a real "no data", not a bug. Pass a ticker ("AAPL"), zero-padded CIK ("0000320193"), OR a company name ("Moderna") — names now resolve via SEC EDGAR's company-name match; a private company (no CIK/ticker) returns resolved:false with an explicit notes line, not a bare failure. type accepts "company" or "ticker" interchangeably — both take the same value shapes above.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYes"company" or "ticker" — both are accepted and behave identically; `value` can be a ticker, CIK, or company name either way. person/place coming soon.
valueYesTicker (e.g., "AAPL"), zero-padded CIK (e.g., "0000320193"), or company name (e.g., "Moderna") — names resolve via SEC EDGAR company-name match.

Schema Changelog

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

  1. Changed3 schema fields changed
    • changedInput schema / properties / type / description
      Previous value: -"Entity type. Only \"company\" supported today; person/place coming soon."New value: +"\"company\" or \"ticker\" — both are accepted and behave identically; `value` can be a ticker, CIK, or company name either way. person/place coming soon."
    • changedInput schema / properties / type / enum
      Previous value: -[
-  "company"
-]New value: +[
+  "company",
+  "ticker"
+]
    • changedInput schema / properties / value / description
      Previous value: -"Ticker (e.g., \"AAPL\") or zero-padded CIK (e.g., \"0000320193\"). Names not supported — use resolve_entity first if you only have a name."New value: +"Ticker (e.g., \"AAPL\"), zero-padded CIK (e.g., \"0000320193\"), or company name (e.g., \"Moderna\") — names resolve via SEC EDGAR company-name match."
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive hints, and the description adds substantial behavior beyond that: it lists all fanned-out sources, explains sources_used/sources_failed semantics, notes the USPTO soft-fail due to API sunset, and clarifies that a private company returns resolved:false with notes rather than failing.

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 dense and long, but appropriately so given the tool's complexity and absence of an output schema. It front-loads usage triggers and decision rules, and most clauses carry unique behavioral information; slight redundancy around the type/value parameter shapes is present but not wasteful.

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?

For a tool with no output schema and many data sources, the description sufficiently covers inputs, output sections, source-failure semantics, resolution behavior, expected empty results, and soft-fail handling. An agent has enough context to invoke it correctly and interpret its results.

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%, so the schema already fully documents type and value. The description adds value with concrete examples (AAPL, 0000320193, Moderna), clarifies that names resolve via SEC EDGAR company-name match, and exposes resolved_from/resolved_to behavior when a name is passed.

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 concrete user phrasings and immediately identifies the deliverable: a full cross-source profile of a US public company in one parallel call. It distinguishes the tool from chaining single-pack SEC/XBRL/news lookups, so an agent can tell it apart from simpler lookup siblings.

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 is explicit about when to prefer this tool: whenever the user asks for a holistic view ('tell me about X', 'research Acme', 'brief me on Tesla'). It also gives an explicit when-not via 'ALWAYS PREFER over chaining single-pack... lookups', and clarifies that empty sections are expected for companies without certain data types.

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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