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Glama

Twilio

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?

Even with readOnlyHint/openWorldHint/idempotentHint annotations, the description adds significant behavioral context: the fan-out is parallel, patents soft-fail after the USPTO API sunset, empty sections are real 'no data' not bugs, and private companies return resolved:false with notes. These disclosures go well beyond what the annotations alone provide.

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 appropriately dense for a complex fan-out tool. It front-loads examples and the ALWAYS PREFER directive, then systematically lists sources, return fields, and edge-case behavior. A few redundant repetitions exist, but nearly every sentence earns its place.

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?

Given that there is no output schema, the description fully compensates by enumerating the return shape (cik, company_name, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, sources_used/sources_failed) and explaining failure semantics. It also covers accepted input shapes, resolution behavior, and sibling differentiation. Nothing essential 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 the baseline is 3. The description adds meaningful nuance beyond the schema: it explains that names resolve via SEC EDGAR's company-name match, that resolved_from/resolved_to appear when a name was passed, and that a private company yields resolved:false rather than a bare failure. This is useful supplementary semantics.

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 phrasings and states the action explicitly: 'full cross-source profile of a US public company in ONE parallel call.' It clearly names the resources searched (SEC EDGAR, XBRL, USPTO, USAspending, Purple Book, DOL LCA, GDELT/GNews, GLEIF) and distinguishes itself from single-pack lookups.

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 gives explicit when-to-use guidance: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also tells the agent what to expect for edge cases like private companies and empty sections, making the decision to invoke this tool versus alternatives unambiguous.

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

B3.2/5.0
Disambiguation2/5

The server is named 'Twilio' but contains only 5 Twilio-specific tools mixed with 31 unrelated Pipeworx tools. An agent must distinguish between Twilio and Pipeworx functionality, and the tool descriptions are clear individually, but the overall set is confusing because the server name implies a focused Twilio service, not a general-purpose data platform with a few Twilio actions.

Naming Consistency2/5

The Twilio tools follow a consistent 'twilio_verb_noun' pattern (e.g., twilio_send_sms, twilio_make_call), while the Pipeworx tools use a separate snake_case convention (e.g., ask_pipeworx, entity_profile, deep_research). The two naming conventions are clearly distinct and do not mix, but the overall set is inconsistent because the server is named after one convention yet the majority of tools follow a different one.

Tool Count1/5

With 36 tools, the count is high, but the critical issue is that only 5 tools are relevant to the Twilio server name. The remaining 31 tools belong to Pipeworx, a completely different domain. This is an extreme mismatch between the claimed server purpose (Twilio) and the actual tool set, making the tool count inappropriate.

Completeness2/5

For a Twilio-focused server, the tool set is very incomplete: it covers only basic SMS sending, call initiation, and listing messages/calls. Missing are phone number management, media handling, conversation features, and other common Twilio operations. The Pipeworx tools are comprehensive for their own domain, but they are irrelevant to the Twilio server's stated purpose, leaving significant gaps.

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