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Glama

Samgov

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?

The annotations already declare the tool read-only, idempotent, and non-destructive, and the description adds substantial behavioral context: patents soft-fail after API sunset, empty sections are real no-data conditions, private companies return resolved:false with a notes line, and sources_used/sources_failed report per-company outcomes. This goes well beyond the structured hints.

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 well organized and front-loaded with usage triggers and the preference directive before the detailed return sections. Each clause carries a distinct fact about a source or behavior, though some parameter guidance is redundant with the schema, preventing a perfect score.

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 documenting return values, and it does so thoroughly: it enumerates every returned section, the underlying data sources, fallback behavior, and failure semantics such as expected empty FDA sections and resolved:false for private companies. Nothing essential for correct invocation 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?

Schema coverage is 100%, and the schema already documents the type enum and the accepted value forms (ticker, zero-padded CIK, company name). The description repeats these forms and adds the EDGAR name-resolution behavior, but it does not meaningfully add beyond what the schema already states.

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 defines the tool as a 'full cross-source profile of a US public company in ONE parallel call' and opens with concrete user-phrase triggers ('Tell me about X', 'research Acme', 'brief me on Tesla'). It explicitly differentiates the tool from chaining single-pack SEC/XBRL/news lookups, which makes the purpose and scope unambiguous.

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 gives an explicit preference rule: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also clearly states acceptable inputs (ticker, CIK, or company name) and how the tool handles private companies, leaving no doubt about when to invoke it.

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

Three ask_pipeworx variants and a dense cluster of polymarket_* edge tools have heavily overlapping purposes, and ai_visibility_check vs scan_competitor_ai_presence further blurs boundaries. Only the sam_*, memory, and subscription tools form cleanly distinct families.

Naming Consistency3/5

All names are lowercase snake_case and readable, but the pattern is mixed: verb_noun names (compare_entities, resolve_entity), bare verbs (remember, recall, forget), noun phrases (entity_profile, polymarket_edges), and domain-prefix families (sam_*, polymarket_*) coexist. No camelCase chaos, but no consistent verb style either.

Tool Count2/5

36 tools is well beyond the ideal range, and many are near-duplicates or wrappers (ask_pipeworx variants, ai_visibility_check vs scan_competitor_ai_presence). The server is named Samgov, yet only 5 tools actually concern SAM.gov, making the count feel inflated and unfocused.

Completeness3/5

The SAM.gov subset covers entity search, opportunities, set-asides, opportunity details, and exclusions, but omits major datasets like contract awards. The broader Pipeworx research/memory/subscription surface is extensive, though it is muddled by redundant query modes and lacks a direct way to invoke individual pack tools.

Resources