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Alchemy Eth

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

A4.6/5.0
Behavior5/5

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

Annotations already cover read-only and non-destructive behavior. The description goes further by disclosing that patents 'soft-fails until reactivated' due to an upstream API sunset, and that names are unsupported inputs. These are behavioral traits an agent needs.

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 dense; every clause adds either usage examples, data source context, return structure, or a limitation. It could be tightened slightly but is well-structured.

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?

For a read-only research tool with no output schema, the description thoroughly covers inputs, behavior, return fields, and known failure modes. It gives an agent everything needed to decide and invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% coverage; both parameters are fully described in the schema with examples and the name limitation. The description repeats this information but adds no new parameter-specific semantics beyond the schema, hence baseline 3.

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 query examples and clearly states it produces a 'full cross-source profile' via a single parallel call. It distinguishes itself from siblings by explicitly saying to prefer it over chained single-purpose lookups and lists exact return fields (CIK, filings, fundamentals, patents, news, LEI).

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?

Explicitly states when to use: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also gives a conditional: if only a name is given, use resolve_entity first. This is strong when-to-use guidance.

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

C2.7/5.0
Disambiguation2/5

Several tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta (currently described as identical), ask_pipeworx_grounded, and deep_research all serve question-answering/research, and the six Polymarket tools heavily overlap in finding and evaluating trading edges. Individual descriptions are detailed, but an agent could easily route to the wrong variant.

Naming Consistency2/5

The set mixes conventions: Pipeworx tools mostly use verb_noun (ask_pipeworx, compare_entities, resolve_entity), but memory tools are bare verbs (remember, recall, forget), and the Ethereum tools are inconsistent (nft_metadata vs nfts_owned vs nft_owners, token_balances vs token_allowance). The lack of a uniform pattern makes the surface harder to predict.

Tool Count2/5

At 40 tools, the server is oversized for the apparent core purpose of an Alchemy Ethereum interface. There is also significant redundancy: multiple ask/deep-research entry points and a dense suite of Polymarket analysis tools add bulk that could be consolidated.

Completeness2/5

The Ethereum side is mostly read-only convenience wrappers (NFTs, tokens, asset transfers) plus a generic eth_call catch-all, but lacks dedicated transaction sending, block/transaction detail, logs, or ENS conveniences. The rest of the tool surface is a sprawling collection of unrelated data-research, memory, and subscription features, making the overall implied domain incoherent and likely to leave obvious gaps for users expecting a focused Ethereum server.

Resources