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Glama

Tomtom

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 establish read-only, open-world, idempotent, non-destructive behavior. The description adds valuable behavioral context beyond that: the tool fans out in parallel, reports sources_used/sources_failed, treats empty sections as real 'no data' rather than bugs, and returns resolved:false for private companies. It also explains the fallback chain from GDELT to GNews and name resolution via SEC EDGAR.

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 dense and front-loaded with examples and the key 'ALWAYS PREFER' guidance. It contains a lot of detail about return sections and input forms, which is useful, but some content near the end (the type interchangeability note) repeats schema information. Overall it earns its length, though it is slightly over-stuffed.

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?

There is no output schema, so the description carries the full burden of explaining return values, and it does so thoroughly: it lists every returned section, mentions resolved_from/resolved_to, source success/failure reporting, and edge cases like private companies. An agent has enough context to call the tool correctly and interpret the result without guessing.

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, but the description adds meaning beyond the schema: it gives concrete examples ('AAPL', '0000320193', 'Moderna'), explains that 'company' and 'ticker' are interchangeable, and clarifies that a company name is resolved via SEC EDGAR. This enriches the parameter understanding without contradicting the schema.

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 states a precise purpose: build a full cross-source profile of a US public company in one parallel call, with concrete invocation examples ('Tell me about X', 'brief me on Tesla'). It distinguishes itself from single-source lookups by explicitly saying it fans out across SEC, XBRL, USPTO, USAspending, FDA, DOL, news, and GLEIF sources.

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 is explicit about when to use this tool: whenever the user asks for a holistic view of a company, and it instructs the agent to ALWAYS PREFER it over chaining single-pack SEC/XBRL/news lookups. It also specifies accepted input forms (ticker, CIK, company name) and clarifies the behavior for private companies, which is strong usage guidance.

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 tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta (currently identical behavior), and ask_pipeworx_grounded are variants of the same router, and the six polymarket_* tools plus bet_research all operate in the same prediction-market space. The extremely detailed descriptions help an agent differentiate, but misselection risk remains real.

Naming Consistency4/5

Snake_case is used consistently and most tools follow a verb_noun pattern (resolve_entity, validate_claim, discover_tools), with predictable polymarket_ and pipeworx_ family prefixes. Minor deviations exist — entity_profile and recent_alerts are noun/adjective phrases, generate_llms_txt embeds a file extension, and single-word verbs (remember, route, geocode) break the strict pattern — but overall naming is coherent.

Tool Count2/5

At 35 tools, the server exceeds the comfortable range and bundles many unrelated domains: data lookup, prediction markets, geocoding/navigation, memory, subscriptions, AI visibility, npm scanning, and llms.txt generation. While every tool has a distinct purpose, the surface is heavy and would benefit from splitting into focused servers.

Completeness4/5

Each major cluster has strong lifecycle coverage: data lookup (router, grounded mode, deep research, discovery), company research (resolve, profile, compare, changes), prediction markets (research, arb, edges, fill risk, cross-venue spread), memory (remember/recall/forget), and subscriptions (subscribe/list/unsubscribe/alerts). Minor gaps exist — no direct Polymarket order placement and no explicit tool for fetching pipeworx:// URIs (left to resources) — but agents can accomplish the stated purposes.

Resources