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Glama

Digimon

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. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the annotations (readOnly, openWorld, idempotent, not destructive), the description discloses substantial behavior: it fans out across multiple government and private sources, soft-fails on certain feeds, reports sources_used/sources_failed, resolves names via SEC EDGAR, and returns resolved:false with notes for private companies. It adds meaningful context without contradicting the annotations.

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 every sentence carries functional information. It front-loads the core purpose and trigger phrases, then systematically covers sources, return shape, input variants, edge cases, and expected failures. For a tool of this complexity, the density is appropriate and there is no filler.

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?

No output schema exists, so the description must carry the full burden of explaining what comes back. It does: CIK, company_name, resolved_from/to, recent_filings URIs, fundamentals, sources_used/failed, and all source sections. It also covers input resolution and the private-company case. A agent has everything needed to invoke this 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 baseline is 3. The description adds value beyond the schema by clarifying that 'type' accepts 'company' and 'ticker' interchangeably, that 'value' can be a ticker, CIK, or company name regardless of 'type', and by giving concrete examples like 'AAPL' and '0000320193'. This is more than the schema alone provides.

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 states a specific verb and resource: it builds a 'full cross-source profile of a US public company in ONE parallel call.' It is clearly distinguished from generic research or chained single-source lookups, and the trigger examples ('tell me about X', 'brief me on Tesla') make the intended use unmistakable.

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?

The description gives explicit guidance: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also specifies the accepted input forms (ticker, CIK, or name), how private companies are handled, and that empty sections mean genuine absence of data rather than failure.

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

Multiple tools overlap significantly: the three ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) are near-identical routers, and the six polymarket_* tools plus bet_research cover overlapping prediction-market territory. The server name 'Digimon' adds confusion since almost all tools are unrelated to Digimon, making it hard for an agent to tell what this server is actually for.

Naming Consistency3/5

All names use snake_case, which is consistent, but the pattern is mixed: some tools start with verbs (get_digimon, search_digimon, list_subscriptions, validate_claim), others with nouns (entity_profile, polymarket_arbitrage, pipeworx_trending), and a few are bare verbs (remember, recall, forget). This irregularity makes the naming less predictable than a uniformly verb-first set.

Tool Count2/5

With 33 tools, the server exceeds the 'too many' threshold and feels bloated. The tools span Digimon data, Pipeworx research, Polymarket betting, memory, subscriptions, and even llms.txt generation—an incoherent grab-bag that doesn't form a focused, well-scoped toolkit.

Completeness4/5

For the broad data-research and prediction-market domain implied by the majority of the tools, the surface is impressively comprehensive: universal routing, grounded answers, deep research, entity resolution, company/drug profiles, comparisons, claim validation, memory, subscriptions, discovery, and multiple specialized Polymarket tools. Minor gaps exist (e.g., no direct order execution on Polymarket), but ask_pipeworx routes to thousands of sources, covering most needs.

Resources