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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.

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. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses the parallel fan-out behavior, that sources_used/sources_failed indicate which sources actually returned data, that an empty section means real no-data rather than a bug, and that private companies return resolved:false with an explicit notes line. This is rich, useful behavioral context.

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

Conciseness2/5

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

The description is front-loaded with examples and the core promise, but it quickly becomes a dense run-on paragraph with corrupted-looking fragments in the return-field list. It would benefit from a structured list and significant trimming to make the valuable content easier to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

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 covers the essential invocation context: supported input shapes, name resolution, private-company failure semantics, return-field highlights, source-status reporting, and limit details like 'up to 5' filings. The garbled return list prevents a perfect score, but an agent still has enough to select and invoke 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 schema already documents both parameters; the baseline is 3. The description adds concrete examples ('AAPL', '0000320193', 'Moderna'), clarifies that type accepts 'company' and 'ticker' interchangeably, and explains SEC EDGAR name resolution, which is meaningful added guidance.

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 is explicit: it produces a 'full cross-source profile of a US public company in ONE parallel call,' backed by concrete trigger examples like 'Tell me about X' and 'brief me on Tesla.' It also distinguishes itself from single-source lookups, so an agent can tell when this tool is the right one.

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 clearly says to 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' which is an explicit when-to-use rule. It would be a 5 if it named specific sibling alternatives and gave a crisp contrast like 'use X for a single filing lookup.'

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

A3.9/5.0
Disambiguation2/5

Several clusters blur together: ask_pipeworx, ask_pipeworx_beta (explicitly identical today), and ask_pipeworx_grounded share routing, while discover_tools/suggest_questions and the Polymarket edge/arbitrage/fill-risk tools have overlapping discovery purposes. Rich descriptions reduce some confusion, but an agent must read carefully to avoid misselection.

Naming Consistency3/5

Most names are lowercase snake_case, but there is no consistent verb_noun pattern: ask_pipeworx/beta/grounded and polymarket_* are domain-prefixed, entity_profile/recent_changes are noun phrases, and query/metadata/remember are bare verbs or nouns. The naming is still readable and subfamilies share prefixes, so it is mixed rather than chaotic.

Tool Count2/5

34 tools is above the comfortable range for a single MCP server, and several could be folded together (the beta variant, visibility checks, and Polymarket scanners). The breadth reflects a large platform, but the surface feels heavy for an agent to select from confidently.

Completeness4/5

The query side is strong: PA Open Data has datasets/metadata/query coverage, and Pipeworx provides ask, deep_research, entity_profile, compare, recent_changes, validate_claim, plus subscriptions and memory with lifecycle coverage. Minor gaps: descriptions promise resolvable pipeworx:// citations but no resource/read tool is exposed, and there is no direct way to fetch an arbitrary record by citation.