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Glama

Hibp

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

A4.6/5.0
Behavior5/5

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

Beyond the annotations, the description discloses important runtime behavior: parallel fan-out across many sources, soft-failure of patents, empty sections meaning real absence of data, private-company fallback behavior, and sources_used/sources_failed output. This is substantial additional operational context that an agent could not infer from annotations alone.

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, front-loading usage examples and the core instruction before enumerating output sections. Some redundancy exists between the prose and the schema (e.g., accepted value forms), but every sentence contributes operational detail that aids correct invocation.

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, the description thoroughly covers input resolution, expected output sections, failure semantics, source coverage, and behavioral fallbacks. An agent has enough information to invoke the tool confidently and correctly interpret results.

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% and the description reinforces and extends it by explaining that 'type' values are interchangeable and that 'value' can be a ticker, zero-padded CIK, or company name with name resolution via SEC EDGAR. This adds practical nuance beyond the schema while the schema still carries the baseline documentation.

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 clearly defines the tool as producing a 'full cross-source profile of a US public company in ONE parallel call', with concrete user-phrase examples that signal intent. It distinguishes itself from chaining single-pack SEC/XBRL/news lookups by explicitly stating it should be preferred for holistic requests.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

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 says to prefer it over chaining single-pack lookups. However, it does not mention when not to use it relative to siblings like deep_research, compare_entities, or resolve_entity, so exclusions are implicit rather than explicit.

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

A4.2/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, and the long, detailed descriptions make it easy for an agent to pick the right one. However, there is some functional overlap between research-oriented tools (e.g., ask_pipeworx vs deep_research vs bet_research) and between visibility-checking tools (ai_visibility_check vs scan_competitor_ai_presence), which could potentially confuse an agent without careful reading.

Naming Consistency4/5

Tool names are uniformly lowercase with underscores, and related tools share consistent prefixes (e.g., polymarket_*, ask_pipeworx, check_*). While most follow a verb_noun pattern, some are noun-first (entity_profile, polymarket_arbitrage) or compound (scan_competitor_ai_presence), creating minor inconsistency, but overall the naming is readable and not chaotic.

Tool Count4/5

With 37 tools, the count is on the higher end but appropriate for a broad data/research platform that covers HIBP breaches, multiple data-pull/research modes, Polymarket analytics, memory, subscriptions, and meta-tools. The number is justified by the diversity of capabilities, though it exceeds the typical 3-15 range for a narrowly-scoped server.

Completeness5/5

The tool set appears thorough for its intended scope: HIBP breach lookup is fully covered (check_account, check_password, get_breach, list_breaches, list_data_classes), research and entity resolution are extensive (entity_profile, compare_entities, deep_research, validate_claim, etc.), Polymarket has dedicated arbitrage/edge/fill-risk tools, and memory/subscription/meta capabilities are present. No obvious gaps for the stated functionality.

Resources