Skip to main content
Glama

superhero

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.

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already mark read-only/idempotent, and the description adds rich behavioral context: fan-out across multiple sources, sources_used/sources_failed semantics, empty sections meaning real no-data, USPTO soft-fail due to API sunset, FDA scope caveat, and resolved:false handling for private companies. No contradiction with 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.

Conciseness4/5

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

The description is long but well-structured and front-loaded with the core purpose and routing rule. Every output section earns its place for such a complex multi-source tool; however, the repeated example queries and restatement of type/value behavior could be trimmed.

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 does the full job: it enumerates returned sections (cik, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI) and their caveats. It also explains failure modes, empty-section semantics, and private-company behavior, so an agent has enough context to select and interpret the call.

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 already covers type and value (100% coverage), and the description reinforces and extends that: type is interchangeable, value can be ticker/name/zero-padded CIK, and names resolve through SEC EDGAR. It adds useful edge-case detail, though much of the extra value is about outputs rather than new parameter mechanics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool builds a full cross-source profile of a US public company in one call, with concrete example queries. It differentiates itself from chaining single-pack lookups, but it does not name sibling tools explicitly, so an agent still has to infer boundaries against deep_research/compare_entities.

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 gives an explicit routing rule: "ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view," plus accepted input forms and private-company behavior. It does not spell out when-not-to-use conditions or name alternatives by tool name, so it falls just short of a 5.

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

All superhero toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.3/5.0
Disambiguation1/5

The tool set is dominated by a huge number of unrelated tools for data lookup (Pipeworx, Polymarket, etc.), with only 4 superhero-specific tools. Many tools serve overlapping purposes (e.g., ask_pipeworx, deep_research, suggest_questions all handle general queries), making it very difficult for an agent to distinguish the right tool.

Naming Consistency2/5

Naming conventions are highly inconsistent: some tools use CamelCase (ask_pipeworx, discover_tools), others use snake_case (get_hero, list_all, compare_entities), and some use long descriptive phrases (polymarket_arbitrage, scan_competitor_ai_presence). This mixture makes it hard to predict tool names.

Tool Count1/5

With 34 tools, the count is far too large for a server named 'superhero'. Most tools are unrelated to superheroes, making the set seem bloated and misaligned with the server's stated purpose. A focused superhero server would need at most 10 tools.

Completeness1/5

For the superhero domain, the tool set is severely incomplete: only basic retrieval of heroes and powerstats, with no search, filtering, creation, comparison, or battle mechanisms. For the broader data access domain it is more complete, but that is not the server's name.

Resources