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Glama

tarot

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?

Annotations already mark this read-only, idempotent, and non-destructive, and the description adds substantial beyond-annotation behavior: it fans out across SEC EDGAR, XBRL, USPTO, USAspending, FDA, DOL, GDELT/GNews, and GLEIF; lists exactly which fields are returned; notes the USPTO API sunset soft-fail; and clarifies that empty sections are real 'no data,' not bugs. This is far more behavioral transparency than typical.

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 dense and front-loaded with usage examples and the core 'ONE parallel call' value proposition. It earns its length by covering many failure modes and source details, but it is structured as one very long run-on paragraph and repeats some schema information, so it loses a point on scannability.

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, the description carries the full burden of explaining returns, and it does: `cik`, `company_name`, `resolved_from/resolved_to`, `recent_filings`, `fundamentals`, `patents`, `federal_contracts`, `fda_products`, `hiring`, `recent news`, `LEI`, and `sources_used`/`sources_failed`. It also covers input variants, private-company behavior, and source-specific caveats, making it complete for an agent invoking this tool.

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 `type` and `value`. The description adds valuable context beyond that: concrete examples ('AAPL', '0000320193', 'Moderna'), the fact that both `type` values behave identically, and that names resolve via SEC EDGAR's company-name match. It could go further on edge cases, but it meaningfully supplements the schema.

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 intents ('Tell me about X', 'brief me on Tesla') and names the deliverable: 'full cross-source profile of a US public company in ONE parallel call.' It clearly differentiates itself from single-pack SEC/XBRL/news lookups, which is exactly the sibling confusion an agent would face.

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?

The description explicitly says to 'ALWAYS PREFER' this tool over chaining single-pack lookups when a holistic view is requested, and it explains the input resolution behavior plus the private-company fallback. However, it does not directly contrast itself with sibling tools like deep_research or compare_entities, leaving some routing ambiguity for those cases.

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

A3.8/5.0
Disambiguation2/5

Several tools overlap in purpose, notably the ask_pipeworx family (stable, beta, grounded all route identically) and random_card vs draw_cards for straightforward draws. The polymarket and research tools also share fuzzy boundaries that an agent could easily misroute.

Naming Consistency3/5

All names use snake_case and readable English, but the set mixes verb-led (ask_pipeworx, recall), noun-led (random_card, recent_alerts), and prefix-family names (polymarket_*, entity_*) with no single structural pattern. Readable but not cohesive.

Tool Count2/5

35 tools is well above the typical well-scoped range and far more than a tarot-focused server would justify. The excess is externally provided Pipeworx functionality that dominates the tarot tools it sits over.

Completeness4/5

For the tarot domain, the set covers the full usage loop: getting, drawing, and searching cards are all present. The surrounding data/research/memory tools also cover their own domains exhaustively, with no obvious dead ends.

Resources