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Funcheap

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

A4.9/5.0
Behavior5/5

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

Beyond readOnly/openWorld/idempotent annotations, the description discloses fan-out across multiple data sources, the semantics of sources_used/sources_failed, that empty sections are real 'no data', and that private companies return resolved:false with a notes line. These are nontrivial behaviors an agent needs to interpret results correctly.

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 densely informative, with a front-loaded purpose phrase, then a logically ordered fan-out/return/input/edge-case structure. Every sentence adds operational detail; the length is justified by the tool's complexity, and the interchangeability note prevents redundant confusion.

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 compensates by listing the main returned fields, source identifiers, and failure semantics. It also covers edge cases like private companies and name resolution, so an agent has enough context to invoke the tool and interpret its response.

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?

The input schema already covers both parameters at 100%, and the description adds concrete examples (AAPL, 0000320193, Moderna), explains that type is interchangeable, and clarifies name resolution through SEC EDGAR. This elevates the baseline 3 to a 4, though no parameter-level syntax is missing.

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 phrasings and a clear verb: full cross-source profile of a US public company in one parallel call. It distinguishes itself from single-pack SEC/XBRL/news lookups by name, so an agent can select it without opening schemas.

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?

It explicitly states ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. It also specifies accepted value forms and what happens for private companies, giving clear selection and execution criteria.

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

A4.1/5.0
Disambiguation4/5

Most tools are distinct (event search, subscriptions, memory, Polymarket arbitrage, data lookups), but ai_visibility_check, scan_competitor_ai_presence, bet_research, polymarket_edges, and polymarket_arbitrage have overlapping purposes around competitive research and prediction-market edge-finding. The detailed descriptions disambiguate them, though an agent could confuse polymarket_edges with polymarket_arbitrage.

Naming Consistency4/5

Tool names are mostly descriptive and consistent: search_events, event, categories, tags are aligned; ask_pipeworx, compare_entities, entity_profile follow a similar pattern. However, polymarket_* tools have an odd mix of `polymarket_arbitrage`, `polymarket_fill_risk`, and `polymarket_edge_tracker`, and discover_tools/recent_alerts/recent_changes are consistent, mostly. Naming is quite consistent overall with minor deviations.

Tool Count3/5

At 35 tools, the count is heavier than typical MCP servers, but it reflects a broad service (Funcheap data + Pipeworx data platform + pred markets). Still, plenty of tools serve the same primary purpose (polymarket_, ask_pipeworx variants) so some pruning would improve the surface.

Completeness4/5

The surface appears complete for its domain: search/retrieve events, category/tag navigation, memory, subscriptions (create/list/cancel/pull), data lookups, entity resolution, comparisons, profiles, edge scanning, and feedback. Minor gaps include no direct 'update' on events (but events are static), and no pricing fetch tool separate from event text, though body text covers it.

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