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Glama

Feodotracker

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

A4.9/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description reveals significant runtime behavior: parallel fanout across SEC EDGAR, XBRL, USPTO, USAspending, FDA Purple Book, DOL, news, and GLEIF; soft-failure of the patent source; resolved_to/resolved_from mapping when a name is passed; and the meaning of sources_used/sources_failed. No annotation contradiction exists.

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 earns its place by conveying behavior an agent cannot infer from schema or annotations. The user-intent examples are front-loaded, and the source/result details are organized in a scan-friendly list. It loses one point for being somewhat verbose and repeating details already present in the schema.

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 shape and semantics. It enumerates all returned sections, explains soft-failure and empty-section behavior, and tells the caller exactly how to interpret resolved:false. This is complete enough for an agent to invoke it and correctly interpret the result without additional tool discovery.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although the schema already documents both parameters at 100% coverage, the description adds materially: accepted input shapes (ticker, zero-padded CIK, or company name), the fact that names resolve via SEC EDGAR match, and the behavior when resolution fails. It also clarifies that 'company' and 'ticker' are interchangeable, which is not obvious from the enum alone.

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 user-phrase examples and pins the operation to a specific resource: a cross-source profile of a US public company in one parallel call. It also contrasts itself with chaining single-pack SEC/XBRL/news lookups, immediately separating it from sibling tools that do narrower or deeper work.

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 exactly when to use the tool ('when the user asks for a holistic view') and explicitly tells agents to ALWAYS PREFER it over chaining single-pack lookups. It also covers edge cases like private companies and empty data sections, which prevents the agent from treating legitimate 'no data' as an error.

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

Multiple near-duplicate clusters exist: ask_pipeworx, ask_pipeworx_beta (explicitly identical to the stable router right now), and ask_pipeworx_grounded all route through the same 5,767-tool catalog, and six polymarket_* tools overlap heavily in surfacing bet/edge opportunities. The blocklist tools (list, recent, aggressive) are only weakly distinguished by time window and confidence, requiring careful reading to select correctly.

Naming Consistency2/5

Naming mixes several incompatible conventions: bare adjectives/nouns for blocklist tools (aggressive, list, recent), brand-prefixed compounds (polymarket_arbitrage, pipeworx_feedback), verb_noun pairs (check_ip, resolve_entity), and noun phrases (entity_profile, bet_research). The server name 'Feodotracker' appears nowhere in the tool names, and the blocklist cluster uses a completely different style from the data cluster.

Tool Count2/5

At 35 tools, the count exceeds the 25-tool threshold for 'too many', but the deeper issue is that roughly 31 tools serve a general data-lookup/prediction-market platform while only 4 serve the server's stated Feodotracker blocklist purpose. The count reflects two unrelated products merged into one MCP server rather than a well-scoped tool surface.

Completeness2/5

For the named Feodotracker domain, the surface is thin: list/check/recent cover basic blocklist access but miss historical lookups, per-entry threat intel, or export formats that a botnet tracker would need. For the data-lookup domain the 31-tool suite is impressively complete, but the two domains don't form a coherent whole—each leaves the other's lifecycle half-served.

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