Skip to main content
Glama

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.

TDQS

A4.8/5.0
Behavior5/5

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

With annotations already declaring read-only, the description adds extensive behavioral detail: fans out across multiple sources in parallel, returns specific data fields with limits (up to 5 filings), notes USPTO API sunset with soft-fail, and GDELT→GNews fallback. No contradictions with annotations.

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 densely packed with valuable information: examples, sources, return fields, and limitations. While long, every sentence earns its place; it could be slightly better structured with bullets, but the current form is efficient for an agent.

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 the tool's complexity (multi-source, 2 params, no output schema), the description fully enumerates return data and edge cases: recent_filings URIs, fundamentals sorting, patent soft-fail, news fallback, and LEI. It even explains the parallel execution and the need for CIK zero-padding.

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 parameter meaning with concrete formats: 'AAPL' or zero-padded CIK '0000320193', plus the restriction that names are not supported and resolve_entity should be used. This adds value beyond the schema's existing descriptions.

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 states it creates a 'full cross-source profile of a US public company in ONE parallel call' with specific verb and resource. It distinguishes itself from chaining single-pack lookups by explicitly saying 'ALWAYS PREFER' this over alternatives.

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?

Provides explicit when-to-use guidance: 'when the user asks for a holistic view' and 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups'. It also gives a clear exclusion: 'names not supported (use resolve_entity first if you only have a name)'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation2/5

Several tool clusters have significantly overlapping scopes. ask_pipeworx and ask_pipeworx_beta are currently identical, and ask_pipeworx_grounded, deep_research, and validate_claim all return grounded answers with different levels of verification. The Polymarket family (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk) also has fuzzy boundaries that could cause misselection.

Naming Consistency4/5

The vast majority of tools follow a verb_noun snake_case pattern (ask_pipeworx, compare_entities, scan_dependency). A few nouns like entity_profile and recent_alerts deviate slightly, and the memory trio (remember, recall, forget) are single-word verbs, but the overall style is consistent and readable.

Tool Count2/5

34 tools is excessive for a server whose name suggests a focused Edmonton open-data scope; only 3 tools actually relate to Edmonton data. Even as a general data platform, the count exceeds the 25-tool threshold and includes many meta-tools (discover_tools, suggest_questions, pipeworx_feedback) that could be consolidated.

Completeness4/5

For the Edmonton open-data subset, search, query, and recent-records cover the core lifecycle well. The broader Pipeworx toolset is comprehensive (entity profiles, comparisons, claims, subscriptions, memory), with only minor gaps like a direct catalog-browsing tool for the 1393 sources.