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Glama

Bamboohr

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

A4.9/5.0
Behavior5/5

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

Beyond the readOnly/openWorld/idempotent hints, the description discloses fan-out across many sources, soft-failure for the USPTO API sunset, expected empty sections (e.g., FDA products for small-molecule-only companies), and the meaning of sources_used/sources_failed. It also explains the private-company response shape. This is exceptional behavioral disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but front-loaded with trigger examples and a clear purpose, then systematically walks through return fields, failure semantics, and edge cases. Every sentence carries useful information; there is no filler or tautology despite the high level of complexity.

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 present, the description carries the full burden of explaining return shape, and it does: it enumerates cik, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, and LEI fields. It also covers failure modes, expected empty results, and input resolution behavior, making the tool safely invokable without additional lookup.

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?

The input schema already covers both parameters at 100%, so the baseline is 3. The description adds value with concrete examples (AAPL, 0000320193, Moderna), clarifies that type='company' and type='ticker' are interchangeable, and explains name resolution via SEC EDGAR. It mostly reinforces the schema but enriches it with usage-level clarity.

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 trigger phrases and clearly states the core action: producing a full cross-source profile of a US public company in one parallel call. It names the resource types (SEC EDGAR, XBRL, etc.) and differentiates itself from chaining single-pack lookups, so an agent can tell it apart from narrower tools.

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 single-pack SEC/XBRL/news lookups when the user wants a holistic view. It also gives the accepted input shapes (ticker, CIK, name), notes that private companies yield resolved:false rather than a failure, and implies people/places are out of scope with 'person/place coming soon.'

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
Disambiguation3/5

The five BambooHR tools are distinct, but the set is dominated by overlapping Pipeworx/Polymarket search and research tools: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all serve similar lookup purposes, and polymarket_edges/polymarket_edge_tracker/polymarket_arbitrage/polymarket_fill_risk/polymarket_kalshi_spread occupy closely related prediction-market territory. Descriptions help differentiate them, but an agent could easily select the wrong one.

Naming Consistency2/5

Naming conventions are heavily mixed: camelCase (ai_visibility_check, ask_pipeworx_grounded), snake_case with varying verb positions (bamboohr_get_directory, list_subscriptions, resolve_entity), and domain-prefixed families that do not share a consistent pattern. Some tools are named by action (bet_research, compare_entities) rather than resource-object style, and the Pipeworx meta-tools follow a different convention than the BambooHR tools.

Tool Count2/5

36 tools is excessive for a server ostensibly named Bamboohr, and the vast majority are unrelated to HR—they cover general data research, prediction markets, AI visibility, and memory storage. The BambooHR-specific surface is only 5 tools buried inside a much larger third-party platform, making the count disproportionate to the stated server purpose.

Completeness2/5

The BambooHR domain is severely under-covered: read operations exist for directory, employees, employee files, and time off, but there are no create/update/delete operations, no time-off request management, no org chart access, no payroll or benefits tools, and no employee lifecycle workflows. Meanwhile, the many non-HR tools are extensive for their own domains but do not fill the obvious HR gaps.

Resources