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Glama

radio

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. Added

TDQS

A4.2/5.0
Behavior5/5

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

The description adds substantial behavioral context beyond the readOnly/openWorld/idempotent annotations: multi-source fan-out, soft-fail behavior for the USPTO API, expected empty FDA sections for non-biologic companies, resolved:false handling for private companies, and the meaning of sources_used/sources_failed. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is information-dense but excessively long and delivered as one continuous wall of text with many redundant query examples and parenthetical asides. Front-loading is decent, but it would be more effective with bullets or tighter organization.

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?

With no output schema, the description carries the burden of explaining return values and does so thoroughly: it enumerates output sections, example URIs, failure modes, and expected empty data conditions. An agent has enough context to invoke the tool correctly and interpret 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 baseline is 3. The description adds value by giving concrete examples ('AAPL', '0000320193', 'Moderna'), clarifying that type is interchangeable, and explaining how names resolve via SEC EDGAR. This goes beyond the schema's own descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: produce a full cross-source profile of a US public company in one call, with example queries like 'company profile for Microsoft'. It contrasts with chained single-pack SEC/XBRL/news lookups, but it does not name or explicitly differentiate from sibling tools such as compare_entities or resolve_entity.

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?

It gives explicit guidance: prefer this tool over chaining single-pack lookups when the user asks for a holistic view, and it covers acceptable input forms (ticker, CIK, company name). It does not state specific exclusions or alternative tools for comparison or entity-resolution tasks, so it stops short of a full when-not guide.

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 are nearly interchangeable: ask_pipeworx_beta is explicitly identical to ask_pipeworx right now, bet_research overlaps heavily with polymarket_edges and polymarket_arbitrage, and ai_visibility_check vs scan_competitor_ai_presence blur together. Despite detailed descriptions, an agent can easily misselect among these overlapping purpose boundaries.

Naming Consistency3/5

Most names follow a readable verb_noun snake_case pattern (list_countries, search_stations, resolve_entity), but bare verbs like remember/recall/forget and inconsistent prefixes (pipeworx_feedback vs ask_pipeworx, bet_research outside the polymarket_* family) break the pattern. The naming is mixed but still navigable.

Tool Count2/5

35 tools is well into the heavy range, and only 4 of them (get_top_stations, list_countries, list_tags, search_stations) pertain to the server's stated 'radio' purpose. The rest form a sprawling research/prediction-market toolkit, making the server feel like multiple unrelated products fused into one.

Completeness3/5

The radio subset covers basic discovery but misses station detail, genre filtering, and stream URLs, an obvious gap for the named domain. The broader Pipeworx/Polymarket suite is expansive with discovery and grounding tools, but remains uneven with no direct per-source browsing and only read-only prediction-market access.

Resources