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Glama

Science Feeds

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?

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description goes beyond that by explaining the parallel fan-out across many sources, the soft-fail behavior of the USPTO patents source, the expected absence of FDA products for companies with only small-molecule drugs, and the explicit 'no data, not a bug' semantics for empty sections.

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 and dense, but almost every sentence carries operational value: example queries, routing guidance, source enumeration, return-field semantics, and failure interpretation. It is front-loaded with the core purpose and preference rule, though a bit of internal repetition (input shape details appearing twice) keeps it from 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?

For a complex tool with no output schema and 2 params, the description covers all key aspects an agent needs: accepted input shapes, multi-source behavior, specific return sections, fallback mechanisms, source status fields, and expected edge cases like private companies and empty FDA data. Nothing critical for correct invocation 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 baseline is 3, but the description adds meaningful semantics: it explains that 'type' accepts 'company' or 'ticker' interchangeably, gives concrete example values for 'value', and clarifies name resolution via SEC EDGAR plus the resolved_from/resolved_to behavior. This enriches what the schema alone provides.

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 names a specific verb and resource: produce a full cross-source profile of a US public company in one parallel call. It gives concrete example queries ('Tell me about X', 'brief me on Tesla') and explicitly contrasts itself with chaining single-pack lookups, making sibling differentiation immediate.

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?

It states 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' giving an explicit selection rule versus alternatives. It also defines acceptable input shapes (ticker, CIK, name), what happens for private companies, and how to interpret empty sections as real 'no data' rather than failures.

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

A3.7/5.0
Disambiguation2/5

Several tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta (currently identical), ask_pipeworx_grounded, deep_research, and validate_claim all route questions to data, while the six polymarket_* tools blur edge-finding, arbitrage, and fill-risk. ai_visibility_check and scan_competitor_ai_presence also overlap, with the latter wrapping the former.

Naming Consistency3/5

All names are snake_case and readable, with clear families like polymarket_*, ask_pipeworx*, and list_*. However, conventions mix verb-first names (resolve_entity, read_feed) with noun-first names (entity_profile, pipeworx_trending, recent_alerts, deep_research), so no single pattern dominates.

Tool Count2/5

34 tools is heavy for any server, but the real issue is scope sprawl: science feeds, a universal data router, prediction-market analysis, memory, subscriptions, AI-visibility checks, and npm scanning each form a mini-server. The count is not defensible for the 'Science Feeds' purpose and would be better split into several focused servers.

Completeness2/5

There is no coherent domain to assess completeness against—'Science Feeds' describes only 3 of 34 tools. Individual clusters are partially complete (subscriptions have subscribe/list/unsubscribe/recent_alerts, memory has remember/recall/forget), but the overall surface is a grab-bag of features from unrelated products, with obvious gaps in each (e.g., no way to update a subscription, no direct access to specific data packs except through the router).

Resources