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Glama

Meteors

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

A4.3/5.0
Behavior5/5

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

The annotations already mark the tool read-only, open-world, and idempotent, and the description adds substantial behavioral detail beyond that: it lists all fanned-out external sources, discloses the USPTO API sunset soft-fail, explains that empty sections mean real 'no data,' and clarifies the resolved:false behavior for private companies. This is exemplary transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

The description is front-loaded with examples and core purpose, which is good, but it is very long and dense, with parentheticals and inline lists that are hard to scan. It also repeats parameter semantics already covered by the schema, so a bulleted structure would preserve completeness while improving conciseness.

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 to lean on, the description thoroughly enumerates every return section, from cik and recent_filings to fda_products and sources_used/sources_failed. It also covers expected failures and edge cases, so an agent has nearly everything needed to invoke the tool correctly.

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%, so a baseline of 3 is appropriate. The description restates nearly the same parameter facts already in the schema (ticker/CIK/name values, 'company' and 'ticker' accepted interchangeably), adding only marginal extra context such as SEC EDGAR name resolution and zero-padded CIK formatting.

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?

It names a specific capability—'full cross-source profile of a US public company'—and opens with multiple concrete user intents ('Tell me about X', 'research Acme'). It also draws a boundary against chaining single-pack lookups, giving enough shape to distinguish it from narrower sibling tools.

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?

It explicitly says to prefer this tool 'over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' which is clear when-to-use guidance. It doesn't spell out when to choose a narrower sibling like compare_entities, but the preference and acceptable input forms are well defined.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Meteors toolsInspect
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TDQS

A3.5/5.0
Disambiguation2/5

Several tools serve nearly identical purposes: ask_pipeworx and ask_pipeworx_beta are explicitly functionally identical right now, and ask_pipeworx, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all overlap as query/discovery entry points. The six prediction-market tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) also blur together for agents looking to find or size a trade.

Naming Consistency2/5

Naming is inconsistent: some tools use get_/list_/scan_ prefixes while others are bare nouns (polymarket_edges, entity_profile, recent_alerts), and the Pipeworx prefix appears only on some tools (pipeworx_feedback, pipeworx_trending) while equivalent tools are named ask_pipeworx or deep_research. Verb styles vary between imperative (validate_claim, resolve_entity) and descriptive (bet_research, polymarket_arbitrage).

Tool Count2/5

34 tools is heavy for a server whose name (Meteors) covers only 3 of them. The bulk belongs to unrelated domains — Pipeworx data access, prediction markets, memory, npm scanning, llms.txt generation — making the surface feel like an unfocused grab bag rather than a deliberate product. Many of the 34 tools could be consolidated (e.g., the three near-identical ask_pipeworx variants).

Completeness2/5

The server has no coherent domain to assess completeness against: meteor data is limited to three lookups with no management/CRUD, memory tools have save/recall/delete but no update, and the Pipeworx surface lacks obvious editing or administrative operations beyond subscriptions. The prediction-market toolset is thorough, but it sits awkwardly beside unrelated utilities, leaving the overall tool surface feeling incomplete for any single stated purpose.

Resources