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Glama

Discogs

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

A4.6/5.0
Behavior5/5

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

The description discloses the full source fan-out, per-source failure behavior (USPTO sunset soft-fail), the expected empty fda_products case, and the meaning of empty sections via sources_used/sources_failed. This complements the readOnly/idempotent annotations and provides failure-mode context annotations cannot express.

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 long but front-loaded with user intents and the key routing directive before diving into source/results detail. Every sentence adds operational or failure-mode value for a multi-source tool, though the dense parenthetical style could be tightened.

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 must document return values, and it does comprehensively: result sections, URIs, sorting, expected empty cases, and sources_used/sources_failed are all covered. Input handling, edge cases, and failure modes are fully specified, so an agent can invoke confidently.

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?

Schema coverage is 100% and the schema already documents both `type` and `value`, including interchangeable behavior, accepted shapes, and EDGAR name resolution. The description mostly restates this, with minor additions like person/place coming soon and resolved_from/resolved_to notes; the schema carries the parameter-semantics burden.

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 intents ('Tell me about X', 'research Acme') and explicitly states the tool produces a full cross-source profile of a US public company in one parallel call. It clearly delimits scope to US public companies and distinguishes itself from chaining single-pack lookups.

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?

It gives explicit trigger phrasing and a direct routing rule: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also specifies accepted input shapes and how private companies are handled, so an agent knows when the tool applies.

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

A3.6/5.0
Disambiguation1/5

There is severe overlap among tools: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical variants, and deep_research, discover_tools, and suggest_questions all serve discovery/research purposes. The Discogs-specific tools are distinct, but the large number of redundant Pipeworx tools makes it impossible to tell which one to pick.

Naming Consistency2/5

The Discogs tools follow a clean verb_noun pattern (get_artist, get_label, get_master, get_release), but the majority of the set uses inconsistent, domain-specific names (deep_research, generate_llms_txt, polymarket_arbitrage, scan_competitor_ai_presence). No single naming convention is applied across the server.

Tool Count1/5

With 36 tools, the server is massively over-provisioned for a Discogs-focused API. Most tools (e.g., ask_pipeworx, polymarket_edges, SEC lookups) have nothing to do with Discogs and belong to a separate service. The Discogs surface alone could be served by ~6 tools (search, get_artist, get_label, get_master, get_release, search_within), so the count is wildly inappropriate.

Completeness3/5

For the Discogs domain, the core entities (artist, label, master, release) and full-text search are present, plus semantic search inside records. However, there are gaps like user collections, wantlists, marketplace, and discogs-specific filters beyond format/country. The presence of many unrelated tools does not directly hurt domain coverage, but the Discogs surface is not exhaustive.

Resources