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ABWerks
by ABWerks

get_etf_holdings

Retrieve complete holdings for any US-registered ETF using SEC EDGAR N-PORT filings. Each holding includes ticker, ISIN, FIGI, shares, value, and more.

Instructions

Get the complete holdings of any US-registered ETF via SEC EDGAR.

Uses Form N-PORT filings (filed monthly by all US ETFs) as the single, consistent primary source. Each holding includes name, ticker, ISIN, FIGI, LEI, shares, USD value, percent of net assets, country, and currency. (CUSIPs are deliberately not included in output.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cikNoOptional 10-digit SEC CIK (from lookup_cik). Skips the ticker→CIK lookup if provided.
tickerYesThe ETF ticker symbol (e.g. 'QQQ', 'SPY', 'SCHD', 'IHDG').

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description takes on full disclosure responsibility. It specifies the data source (monthly N-PORT filings), the exact fields returned, and deliberately notes that CUSIPs are excluded. This adds meaningful behavioral context beyond the schema, though it does not mention potential limitations like filing delays.

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 two concise paragraphs, front-loaded with the core action in the first sentence, followed by essential context and output details. Every sentence provides value; there is no redundancy or 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?

Despite moderate complexity, the description covers the tool's purpose, data source, returned fields, and an explicit exclusion (no CUSIPs). With an output schema present, detailed return structure is unnecessary, making this description complete for an AI agent.

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 description coverage is 100%, with both parameters well-documented: ticker has examples and cik explains its optional role and the lookup-cik shortcut. The description itself adds no further parameter-level semantics, so the baseline score of 3 is appropriate.

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 'Get the complete holdings of any US-registered ETF via SEC EDGAR,' clearly stating the tool's specific action, resource, and scope. It distinguishes itself from sibling tools (lookup_cik, resolve_ticker, etc.) which are identifier-resolution utilities rather than data-retrieval tools.

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 provides clear context about when the tool applies (any US-registered ETF, using Form N-PORT filings) but does not explicitly state when-not-to-use or compare with alternatives. It references lookup_cik only in the schema, not the description, so the guidance is contextually clear but lacks explicit exclusions.

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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