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Glama

Spotify

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

A4.4/5.0
Behavior5/5

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

Beyond the readOnly/idempotent/openWorld annotations, the description discloses soft-failure behavior for the USPTO patents source, a GDELT-to-GNews fallback, per-source sources_used/sources_failed tracking, and the resolved:false behavior for private companies. It also clarifies that an empty FDA section is expected for companies without biologics. This greatly exceeds annotation coverage.

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 front-loaded with trigger phrases and the core 'one parallel call' concept, and each behavioral detail is useful given the tool's complexity and lack of an output schema. It is quite long and somewhat dense, and it repeats some schema-level parameter details, so it is not maximally concise, but it earns its length.

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 full responsibility for explaining return structure, and it does so thoroughly: CIK, filings, fundamentals, patents, contracts, FDA products, hiring, news, LEI, and source tracking. It also covers input variants, resolution behavior, private-company handling, and expected empty results. Nothing essential is missing.

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?

The input schema already provides 100% parameter coverage, including the interchangeable type enum and the ticker/CIK/company-name value formats. The description restates these forms and adds a small amount of output behavior context, but it does not meaningfully add net parameter meaning beyond what the schema already provides.

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 identifies the operation: producing a full cross-source profile of a US public company in one parallel call, with multiple trigger-phrase examples. However, it does not explicitly differentiate itself from named siblings such as resolve_entity, compare_entities, or deep_research, so the distinction from alternatives is implied rather than stated.

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 explicitly instructs the agent to ALWAYS PREFER this tool over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. It also provides important routing context: empty sections are expected and not failures, and private companies resolve to resolved:false with notes. This gives clear when-to-use and when-not-to-misinterpret guidance.

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

B3.1/5.0
Disambiguation1/5

The tool set is a chaotic mix of Spotify music tools and an extensive Pipeworx data querying system, with no clear separation. Tools like 'ask_pipeworx', 'ask_pipeworx_grounded', and 'deep_research' have overlapping querying purposes, while unrelated tools from prediction markets and company research further muddy the boundaries. An agent would struggle to distinguish which tool to use for a given task.

Naming Consistency2/5

Naming conventions are inconsistent: Spotify tools follow a verb_noun pattern (e.g., 'get_album', 'search'), while Pipeworx tools use descriptive phrases (e.g., 'ask_pipeworx', 'bet_research'). Additionally, some tools have vague names like 'process' or 'run' that could apply to anything. The lack of a unified naming scheme makes the set feel disjointed.

Tool Count2/5

With 36 tools, the count is high, but the server name 'Spotify' implies a focused music service. The majority of tools are unrelated to Spotify (e.g., Pipeworx queries, Polymarket bets, dependency scanning), making the tool count feel inflated and inappropriate for the stated domain. A more focused set would be far more coherent.

Completeness1/5

If this is a Spotify server, it is severely incomplete: it lacks playlist management, user actions, and recommendation features beyond top tracks. The inclusion of dozens of unrelated tools (financial data, prediction markets, package analysis) suggests the server has no clear purpose, leaving it neither complete for Spotify nor for any other single domain.

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