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Glama

Hilma

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?

Massively exceeds the readOnly/openWorld/idempotent annotations by disclosing failure modes and expected-empty semantics: 'an empty section is a real "no data", not a bug,' USPTO patents that 'soft-fail until reactivated,' and FDA behavior for small-molecule-only companies being 'expected, not a failure.' Also documents the private-company path ('resolved:false with an explicit notes line'), the GDELT→GNews fallback, and resolved_from/resolved_to name-mapping. 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.

Conciseness4/5

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

Front-loaded with trigger phrases and the core promise ('ONE parallel call') before a dense but organized catalog of sources, return fields, and edge cases. Given the tool's complexity, nearly every sentence earns its place; the deduction is for redundancy — the interchangeable-`type` note and input formats repeat schema content, and the single-paragraph wall-of-text structure could use section breaks.

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 full burden of explaining return values — and it delivers: cik, resolved_from/resolved_to, recent_filings (up to 5, with pipeworx:// URIs), LATEST 10-K fundamentals, per-source sections, and the sources_used/sources_failed diagnostic. Input variants, private-company behavior, source fallbacks, and 'no data' semantics are all covered; nothing needed to call this correctly is missing.

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 genuine value with concrete input examples ('AAPL', '0000320193', 'Moderna'), the resolved_from/resolved_to behavior for name inputs, and private-company resolution semantics. However, it partly restates the ticker/CIK/name formats already documented in the schema for both parameters, limiting the incremental gain.

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?

States a specific verb+resource+scope: 'full cross-source profile of a US public company in ONE parallel call,' backed by concrete trigger phrases ('Tell me about X', 'brief me on Tesla'). The 8 named sources, the return-shape summary, and the explicit contrast with 'chaining single-pack SEC/XBRL/news lookups' cleanly separate it from siblings like resolve_entity or deep_research.

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?

Provides explicit when-to-use signals via the example user queries and the directive 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' This is both a positive trigger and an explicit exclusion of the alternative approach; the only minor gap is not naming deep_research/compare_entities as competing siblings.

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

A3.9/5.0
Disambiguation3/5

Several natural-language query tools overlap heavily: ask_pipeworx, ask_pipeworx_beta (currently identical), ask_pipeworx_grounded, deep_research, and validate_claim all route questions to the same underlying Pipeworx catalog. The descriptions do clarify the differences eventually, but the boundaries are subtle enough that an agent could easily pick the wrong one, and discover_tools/suggest_questions also serve a similar onboarding role.

Naming Consistency3/5

Almost all names are snake_case and readable, but they mix verb-first names (ask_, compare_, discover_, validate_) with noun-first names (entity_profile, recent_changes, polymarket_arbitrage, pipeworx_trending). The domain prefixes like hilma_, polymarket_, and pipeworx_ help navigation, but there is no single predictable verb_noun convention across the set.

Tool Count2/5

At 34 tools, the surface is too large for the amount of genuine functional diversity. Several tools are near-duplicates (ask_pipeworx_beta vs ask_pipeworx, ai_visibility_check vs scan_competitor_ai_presence, suggest_questions vs discover_tools), and the set would be noticeably tighter around 20-25 tools without losing coverage.

Completeness4/5

The major workflow clusters are well covered: research/query modes, entity resolution and comparison, prediction-market analysis, memory, and subscription lifecycle management all have their key operations present. Minor gaps exist — such as Hilma notices returning only index metadata rather than full notice text — but there are no critical dead ends for the server's apparent multi-domain research purpose.

Resources