Clean SEC EDGAR company financials, ratios, filings and 10-K/10-Q sections as normalized JSON.
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Average 4.1/5 across 7 of 7 tools scored. Lowest: 3.5/5.
Each tool has a clearly distinct purpose: company info, events, filings metadata, financial statements, insider trades, ratios, and narrative sections. No two tools overlap in functionality, and descriptions make the differences explicit.
All tools follow a consistent 'get_' + noun pattern (get_company, get_events, get_filings, etc.), with predictable naming that makes it easy for an agent to infer tool purpose from the name.
With 7 tools covering identity, events, filings, fundamentals, insider trades, ratios, and narrative sections, the set is well-scoped for equity research on US-listed companies—not too sparse, not bloated.
The tool surface covers all major aspects of SEC EDGAR data for a ticker: basic info, material events, filing history, financial statements, insider trades, computed ratios, and narrative sections. There are no obvious gaps for the intended domain.
get_companyGet a company profileACIK, legal name, SIC industry, fiscal-year end, exchanges and website for a ticker, resolved from SEC EDGAR submissions.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | US stock ticker, e.g. 'AAPL'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and destructiveHint=false. Description adds source and output fields, but no additional behavioral traits like rate limits or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence front-loading key data fields; every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with good annotations and a single parameter, the description sufficiently covers output and source, though lacks output schema details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a well-described ticker parameter. Description does not add parameter-specific details beyond what schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description lists specific data fields (CIK, legal name, SIC industry, etc.) and source (SEC EDGAR), clearly distinguishing it from sibling tools like get_filings or get_events.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use vs alternatives; purpose is clear but excludes context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_eventsGet 8-K material eventsA8-K material events for a ticker as typed items (2.02 earnings, 5.02 executive change, 1.05 cybersecurity incident, 2.01 acquisition, etc.), each with a notable flag for the market-moving ones and a link to the filing.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of events, 1-100 (default 20). | |
| ticker | Yes | US stock ticker, e.g. 'AAPL'. | |
| notable | No | Only market-moving events (default false). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, openWorldHint, idempotentHint, destructiveHint. The description adds context about output items (typed, notable flag, filing link) but does not disclose additional behavioral traits beyond what annotations offer.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single well-constructed sentence that efficiently conveys purpose, resources, and key features without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only tool with clear annotations and schema, the description explains output features (typed items, notable flag, link). However, it omits details on pagination, ordering, or error conditions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions (ticker, limit, notable). The description does not add new parameter semantics but reinforces that 'notable' filters to market-moving events.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves 8-K material events for a ticker, specifying types (e.g., earnings, executive change) and features (notable flag, filing link). It distinguishes from siblings like 'get_filings' and 'get_sections' by focusing on material events.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for market-moving events via the 'notable' flag and mentions specific event types, but does not explicitly state when to use this tool over alternatives or provide exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_filingsGet recent SEC filingsARecent SEC filings for a ticker (10-K/10-Q/8-K) with filing/report dates and document links.
| Name | Required | Description | Default |
|---|---|---|---|
| form | No | Optional form filter, e.g. '10-K', '10-Q', '8-K'. | |
| limit | No | Number of filings to return, 1-100 (default 20). | |
| ticker | Yes | US stock ticker, e.g. 'AAPL'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, etc. The description adds context about what data is returned (dates and document links), which is useful beyond structured fields. No contradictions or missing behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a single sentence that is front-loaded with key information (verb, resource, scope, output). No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description explains the return content (dates and links). It covers the purpose and key parameters. Could mention sorting or default limit behavior, but overall sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the description does not need to add parameter details. It doesn't add extra meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns recent SEC filings for a ticker, listing common form types (10-K, 10-Q, 8-K) and specifying the output includes filing/report dates and document links. This distinguishes it from sibling tools like get_company or get_sections.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context for when to use the tool (to get recent filings for a ticker) and mentions form types as optional filters. However, it does not explicitly state when not to use it or compare to alternative tools for historical or different filing types.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_fundamentalsGet company financial statementsANormalized income statement, balance sheet, and cash flow for a US-listed ticker, parsed from SEC EDGAR XBRL. Counts as one request on the Edgrapi plan.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of periods to return, 1-20 (default 5). | |
| period | No | Reporting period (default annual). | |
| ticker | Yes | US stock ticker, e.g. 'AAPL'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly, idempotent, non-destructive. The description adds context that the data is parsed and normalized from XBRL, and mentions request counting, which provides additional behavioral detail beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first sentence delivers core functionality, the second adds usage context. No wasted words, and the key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool has no output schema, the description does not detail the structure or format of the returned data (e.g., which fields are included). It is adequate but leaves room for ambiguity about the exact output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add extra meaning beyond what the schema already provides for the parameters (limit, period, ticker).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns normalized income statement, balance sheet, and cash flow for a US-listed ticker from SEC EDGAR XBRL. It distinguishes itself from sibling tools by specifying the type of data (fundamentals) and source (XBRL).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes a usage hint about counting as one request on the Edgrapi plan. However, it does not explicitly compare to siblings like get_ratios or get_filings, leaving the agent to infer when to use this tool over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_insiderGet parsed insider transactionsAParsed SEC Form 4 insider trades for a ticker: owner, role, transaction code (P open-market purchase, S sale, A award, M exercise, F tax withholding), shares, price, dollar value, and a 10b5-1 plan flag. Code P is the only own-money buy signal; A/M/F are automatic compensation. Pass ticker='latest' for the market-wide feed of the biggest open-market buys, or ticker='clusters' for companies where several insiders bought at once (the cluster-buy signal).
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | For 'clusters': lookback window in days (default 15). | |
| limit | No | Number of results, 1-100 (default 20). | |
| ticker | Yes | US stock ticker (e.g. 'AAPL'), 'latest' for market-wide buys, or 'clusters' for cluster buys. | |
| min_insiders | No | For 'clusters': min distinct insiders (default 3). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint, openWorldHint, idempotentHint, and no destructiveness. The description adds context beyond annotations by explaining the data fields, transaction code semantics, and special ticker behaviors. It does not contradict annotations and provides sufficient behavioral insight for a read-only tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph, but it is densely packed with essential information without fluff. It starts with a clear statement of purpose, then elaborates on transaction codes and special ticker values. Every sentence adds value, making it both concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, the description adequately explains the return fields (owner, role, transaction code, etc.) and covers special behaviors for 'latest' and 'clusters'. All four parameters are described with semantic context. The description is complete for the tool's complexity and annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds value by explaining the significance of transaction codes (e.g., P as buy signal) and the meaning of special ticker values ('latest', 'clusters') and parameters like days and min_insiders for clusters. This goes beyond the basic schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns parsed SEC Form 4 insider trades for a ticker, listing specific fields like owner, role, transaction code, etc. It distinguishes from sibling tools (e.g., get_filings, get_fundamentals) by specializing in insider transactions and includes special ticker values ('latest', 'clusters') for advanced use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool (for insider trading data) and explains the meaning of transaction codes, emphasizing that code P is the only own-money buy signal. It also describes special ticker values for market-wide feed and cluster buys. While it does not explicitly exclude alternative tools, the context is clear and no exclusions are needed given the sibling tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_ratiosGet computed financial ratiosAMargins, returns (ROE/ROA), leverage and liquidity ratios for a ticker, derived from SEC EDGAR fundamentals. Price-based ratios (P/E, P/B) excluded.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | US stock ticker, e.g. 'AAPL'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint, idempotentHint, and nondestructive behavior. The description adds context about data source (SEC EDGAR) and excluded ratio types, which is helpful but does not provide additional behavioral traits beyond annotations. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense sentence that covers key ratios, source, and exclusion. Every part serves a purpose with no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple input schema (1 parameter) and no output schema, the description adequately explains what the tool returns, its scope, and its source. It is complete for an agent to decide invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description for the single parameter 'ticker'. The description mentions 'for a ticker' but adds no extra semantic meaning beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves margins, returns, leverage, and liquidity ratios derived from SEC EDGAR fundamentals. It explicitly excludes price-based ratios, distinguishing it from siblings like get_fundamentals. The verb 'get' and resource 'ratios' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for non-price-based financial ratios and mentions exclusion of price ratios, suggesting an alternative tool might handle those. However, it lacks explicit when-to-use or when-not-to-use statements and does not name specific sibling tools for contrast.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_sectionsGet 10-K/10-Q narrative sectionsANarrative sections from the latest 10-K/10-Q as clean text — Risk Factors (item 1A), MD&A (item 7), Business (item 1), etc. Built for LLM/RAG equity research. Omit 'item' to list the available sections first.
| Name | Required | Description | Default |
|---|---|---|---|
| form | No | Filing type: '10-K' (default) or '10-Q'. | |
| item | No | Section to fetch, e.g. '1A' (Risk Factors) or '7' (MD&A). Omit to list available sections. | |
| ticker | Yes | US stock ticker, e.g. 'AAPL'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds that output is 'clean text' and 'Built for LLM/RAG equity research', but does not disclose additional behavioral traits like rate limits, caching, or what 'latest' means. With good annotations, a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is two sentences, front-loaded with the core purpose. Every sentence adds value: first explains what it does, second gives usage tip. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, but the description says it returns 'clean text'. It describes the scope (latest 10-K/10-Q) and intended use. It could clarify what 'latest' means or potential for multiple filings, but overall sufficiently complete for its niche.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the schema descriptions already explain the parameters (e.g., item: 'Omit to list available sections'). The tool description repeats that note and adds examples ('Risk Factors (item 1A), MD&A (item 7)'), which provides some extra context but does not significantly enhance understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool retrieves narrative sections from latest 10-K/10-Q filings, lists specific items (Risk Factors, MD&A, Business) and states its purpose for LLM/RAG equity research. It distinguishes from sibling tools like get_filings which return filing metadata, not sections.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance: 'Omit item to list the available sections first' tells when to use the tool without that parameter. It implies usage for fetching specific sections or listing available ones, but does not explicitly state when not to use or provide alternatives.
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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