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Glama

Movies

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

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and no destructive behavior, and the description adds substantial context beyond that: it enumerates the many sources fanned out to, explains that empty sections mean real 'no data' via sources_used/sources_failed, documents USPTO patent data soft-failure after May 2025, and clarifies expected empty fda_products for non-biologic companies. This is rich, non-obvious behavior.

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 almost every clause carries required behavioral or edge-case information, and there is no output schema to carry that burden. It is front-loaded with trigger examples and the preference instruction. It could be more scannable with bullets, but it contains no filler or redundant restatements.

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 correctly takes on the burden of explaining the return envelope: it lists every major output section (filings, fundamentals, patents, contracts, fda_products, hiring, news, LEI), defines sources_used/sources_failed semantics, and covers edge cases like private companies, expected-empty FDA sections, and USPTO sunset. An agent has enough context to invoke and interpret this tool correctly.

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% and both parameters are already documented, so the baseline is 3. The description goes further by giving concrete examples ('AAPL', '0000320193', 'Moderna'), clarifying that type='company' and type='ticker' behave identically, and explaining name resolution plus resolved_from/resolved_to behavior, which adds real meaning beyond the schema.

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 trigger phrases and states a specific verb+resource: 'full cross-source profile of a US public company in ONE parallel call.' It distinguishes itself from likely alternatives like deep_research and resolve_entity by focusing on a single public company and explicitly naming the alternative pattern it replaces ('chaining single-pack SEC/XBRL/news lookups').

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 explicitly says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' giving a clear condition and alternative. It also covers input resolution behavior and private-company fallback. It does not, however, address potential overlaps with siblings like deep_research or compare_entities, so the guidance is strong but not fully comprehensive.

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

A3.5/5.0
Disambiguation2/5

Many tools have heavily overlapping purposes—ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are nearly identical, while entity_profile, compare_entities, and recent_changes all pull overlapping company data. The server is named 'Movies' but only 4 of 35 tools relate to movies, making it impossible to infer what the tool set is actually for.

Naming Consistency2/5

Naming is a mix of verb_noun (search_movies, get_tv_schedule), bare nouns (remember, recall), brand prefixes (pipeworx_*, polymarket_*), and ad-hoc verbs (ask_pipeworx vs validate_claim). There is no consistent convention; even the pipeworx family uses ask_ vs grounded vs beta suffixes that don't follow a predictable pattern.

Tool Count2/5

35 tools is heavy for a single server, and for a 'Movies' server it is extreme overkill since the vast majority have nothing to do with movies. Even if the intent was a general data/betting server, 35 tools exceed the upper bound of the well-scoped range and would be better split into focused servers.

Completeness2/5

As a movies/TV server it is severely incomplete: there is no get_movie, no reviews, no watchlist, no person/actor search—only search_movies, search_tv_shows, get_tv_show, and get_tv_schedule. If instead the domain is Pipeworx data, coverage is better but still lacks mutation tools (e.g., no create/update for subscriptions beyond subscribe/unsubscribe) and the movie tools become dead weight.

Resources