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Glama

Gmail

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

A4.8/5.0
Behavior5/5

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

The description goes far beyond the readOnly/idempotent/openWorld annotations by detailing the fan-out sources, the USPTO PatentsView sunset soft-fail, expected empty results for FDA products, and the sources_used/sources_failed fields. It also reveals resolution behavior and the private-company resolved:false response, giving the agent a reliable model of tool behavior.

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 information-dense, with the core purpose front-loaded and followed by a well-organized breakdown of return sections. While it could be tightened, most sentences earn their place by preempting common agent misjudgments, such as empty sections being expected or patents temporarily unavailable.

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. It enumerates each returned section — cik, company_name, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, and sources_used/sources_failed — including caveats and expected-empty cases. This is sufficient for an agent to call and interpret the tool correctly.

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. The description adds useful nuance by stating that 'company' and 'ticker' are interchangeable and accept the same value shapes, which is not obvious from the enum alone. It reinforces the zero-padded CIK requirement and name resolution behavior.

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 specific verb and resource: build a full cross-source profile of a US public company. It opens with concrete query examples and distinguishes the tool from chained single-pack lookups, making its unique role clear.

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 explicitly says to prefer this tool over chaining separate SEC/XBRL/news lookups when a holistic view is requested. It also explains expected behavior for private companies and empty sections, guiding the agent on when results indicate a real 'no data' condition rather than a failure.

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

B3.4/5.0
Disambiguation2/5

There is significant overlap among tools, particularly within the Pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and the Polymarket family (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread). These tools have similar purposes, making it hard for an agent to distinguish them at a glance. The Gmail tools are a small, distinct cluster, but the overall set is confusing.

Naming Consistency3/5

All tool names use snake_case, but the verb_noun pattern is inconsistent. Many start with verbs (ask_pipeworx, compare_entities, discover_tools, etc.), but some use noun_verb (bet_research), noun_noun (entity_profile), or adjective_noun (deep_research). This mixed pattern reduces predictability.

Tool Count2/5

With 36 tools, the count is high, but the server name 'Gmail' suggests a focused email service. Only 5 tools are Gmail-related, while the rest cover a vast, unrelated domain (Pipeworx, Polymarket, etc.). This mismatch makes the tool count inappropriate for the server's apparent purpose.

Completeness2/5

For the Gmail domain, the tool surface is incomplete (e.g., missing delete, archive, modify labels). For the broader Pipeworx/Polymarket domain, the tools are extensive but lack clarity in coverage. The server attempts to cover too many domains without sufficient depth in any, leading to notable gaps.

Resources