SEC-signed profiles for 8,000+ US public companies from EDGAR filings. Token-efficient.
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Average 3.4/5 across 9 of 9 tools scored. Lowest: 2.8/5.
Each tool has a clearly distinct purpose: company lookup, digest, enrollment, filings index, person career, profile, search, timeline, and transcripts. No overlap in functionality.
All tools follow a consistent 'origin_' prefix followed by a descriptive word. The naming pattern is predictable and uniform across the set.
9 tools is appropriate for a filings and company research server. It covers core functionalities without being overwhelming or sparse.
The tool set covers the full domain of company research: lookup, profile, filings, transcripts, timeline, person career, cross-company search, digest, and user enrollment. No obvious gaps.
origin_companyAInspectLook up a US public company by ticker. SEC-verified, ~200 tokens. Use this FIRST for any company query.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | Stock ticker (e.g. AAPL, MSFT, WAVX) or CIK number |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It discloses the data source (SEC-verified) and token cost (~200 tokens). However, it does not mention potential errors, rate limits, or the exact nature of the response (e.g., read-only). A score of 4 is appropriate as it provides key behavioral traits without being exhaustive.
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 extremely concise with two sentences. The first sentence states the core purpose, and the second provides usage guidance and key attributes. 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 tool's simplicity (single parameter, no output schema), the description is adequate but lacks details on what the lookup returns (e.g., company name, sector). Since no output schema is provided, the description could be more complete by hinting at typical output fields.
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% with a clear description of the 'ticker' parameter. The tool description adds no additional semantic information beyond what the schema already provides, so baseline score of 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's function: 'Look up a US public company by ticker.' It distinguishes itself from siblings by being the primary company lookup tool, as indicated by 'Use this FIRST for any company query.'
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?
Description explicitly advises to 'Use this FIRST for any company query,' providing clear usage context among sibling tools. It also mentions the tool is 'SEC-verified' and costs '~200 tokens,' helping the agent assess reliability and cost.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
origin_digestAInspectGet the latest research digest for an enrolled user. Returns filing signals, recent facts, stock quotes, and AI agent interest levels for their watched companies. Use this to brief a user on their portfolio.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | User email address |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes the read operation and the specific data returned (filing signals, facts, quotes, interest levels). With no annotations, the description adequately conveys behavior, though it does not mention error handling if the user is not enrolled.
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?
Three concise sentences: first states the action, second lists contents, third provides use case. No redundant 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 single parameter and no output schema, the description fully explains what the tool does and what it returns. Adequate for a digest retrieval tool.
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% (email parameter described). Description adds no extra semantics beyond what the schema provides, so baseline of 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?
Clearly states the verb 'Get' and the specific resource 'latest research digest'. Distinguishes from siblings by specifying it returns a comprehensive digest of filing signals, facts, quotes, and interest levels, which is not provided by other origin_ tools.
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?
Explicitly says 'Use this to brief a user on their portfolio', providing a clear use case. Does not mention when not to use or alternatives, but the intended context is well-defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
origin_engageAInspectEnroll a user for company research briefings. The user provides their email and tickers to watch. They get weekly or daily digests with filing signals, earnings facts, and AI interest data. Use this when a user says they want to track companies or get regular updates.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | User email address | ||
| tickers | Yes | Array of stock tickers to watch (max 20) | |
| frequency | No | How often to send briefings (default: weekly) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It states the enrollment action and digest frequency but does not disclose side effects like whether existing enrollments are overwritten, confirmation steps, or data retention. Minimal transparency.
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?
Two concise sentences: the first states the action, the second gives usage context. Every word earns its place; no 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 tool with 3 parameters (all described in schema), no output schema, and no annotations, the description covers purpose, inputs, and usage scenario. It could be improved by mentioning return value (e.g., confirmation message) but is otherwise complete.
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 baseline is 3. The description restates 'email and tickers to watch' and mentions 'weekly or daily digests', which aligns with the 'frequency' parameter but adds no new details 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?
The description clearly states the action: 'Enroll a user for company research briefings.' It specifies inputs (email and tickers) and output (digests). It distinguishes from sibling tools like origin_digest (view digests) by focusing on enrollment.
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 explicitly says when to use: 'when a user says they want to track companies or get regular updates.' It does not mention when not to use or provide alternatives, but the context is clear and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
origin_filingsCInspectSEC filing index with EDGAR links.
| Name | Required | Description | Default |
|---|---|---|---|
| form | No | Optional: 10-K, 10-Q, 8-K | |
| ticker | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral disclosure. It only states it's an 'SEC filing index with EDGAR links,' missing info on read-only nature, pagination, or what 'index' entails.
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 extremely concise with no wasted words. It is front-loaded and communicates the core purpose efficiently.
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?
Despite low complexity, the description is inadequate. It does not specify return format, how to use the parameters, or any constraints. The sibling list hints at domain but the description itself is incomplete.
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 50% (only 'form' has description). The description adds no extra meaning beyond the schema, failing to compensate for the undocumented 'ticker' parameter.
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 indicates this tool provides an SEC filing index with EDGAR links, which differentiates it from sibling tools like origin_company or origin_search. The verb is implied (list/get), but it's sufficiently 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?
No guidance on when to use this tool versus alternatives. The context suggests sibling tools exist for other purposes, but the description doesn't provide any selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
origin_personBInspectCareer path across US public companies.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Person name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions the scope (US public companies) but lacks details on read-only nature, data freshness, error handling, or pagination. This is insufficient for safe invocation.
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 very concise at one sentence, but it lacks structure and misses critical information. It is not overly verbose, but the brevity sacrifices clarity and completeness.
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 simplicity (one parameter, no output schema), the description is still insufficient. It does not hint at return values, data format, or whether it covers only current positions or full history. The description leaves significant gaps for an agent to infer.
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% for the single parameter 'name', which has a basic description. The tool description adds no extra context about the parameter, such as name format or examples. Baseline is 3 due to high schema coverage, but no value added.
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 provides career path information for a person across US public companies, which distinguishes it from sibling tools like origin_company (company info) or origin_profile (profile). However, it does not specify whether it returns current or historical positions, leaving some ambiguity.
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 when seeking a person's career history, but it does not provide explicit guidance on when to use this tool versus alternatives like origin_profile or origin_timeline. No when-not scenarios are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
origin_profileCInspectFull company profile: people, products, partnerships. ~800 tokens.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only discloses the approximate token size (~800 tokens) and the content categories, but omits whether the operation is read-only, requires authentication, or has side effects.
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?
Two sentences, front-loaded with the most important information ('Full company profile'), and includes a helpful size indicator (~800 tokens). 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 one parameter without schema descriptions, no output schema, and eight siblings, the description is minimally adequate. It states the content scope and size but offers no details on input format, output structure, or when to pick this over similar tools.
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?
The schema has 0% description coverage, and the description does not explain the single parameter 'ticker'. It does not clarify that it expects a stock ticker symbol or provide any format hints.
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 returns a full company profile covering people, products, and partnerships. The name 'profile' implies retrieval. Among siblings like origin_company and origin_person, it distinguishes itself as a comprehensive overview, but the verb is implicit.
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?
Description lacks explicit guidance on when to use this tool versus alternatives. It does not mention when to prefer origin_company or origin_person over this full profile, nor does it state any prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
origin_searchCInspectCross-company search by keyword, technology, or person.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits (e.g., pagination, rate limits, read-only nature, data freshness). The agent has no information about side effects or constraints beyond the basic search action.
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, front-loaded sentence with no wasted words. It clearly communicates the core purpose and search dimensions. Ideal conciseness for a simple tool.
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?
With no output schema, no annotations, and only one undocumented parameter, the description is too brief. It does not explain the return format, result structure, or any limitations (e.g., maximum results, filtering). An AI agent lacks the context to use the tool correctly beyond the most basic search.
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?
The only parameter 'query' has no description in the schema. The tool description adds that the search can be by 'keyword, technology, or person', giving some context on what to enter. This partially compensates for the 0% schema coverage, but the parameter remains a plain string without format hints.
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 is a cross-company search by keyword, technology, or person. This distinguishes it from siblings like origin_company or origin_person, which target specific entities. However, it could be more precise about what types of results are returned (e.g., documents, profiles).
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 this tool versus alternatives. The term 'cross-company' implies it's for broad searches, but it doesn't mention that for specific entities, siblings like origin_company should be used. This lack of direction leaves the agent guessing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
origin_timelineCInspectQuarter-by-quarter history from SEC filings. ~2000 tokens.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It adds '~2000 tokens' hinting at output size, but lacks details on rate limits, authentication, or what happens with invalid tickers.
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?
At ~10 words, the description is concise but too terse. It lacks structure (no sections) and misses opportunities to add value without significant length increase.
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 no output schema, the description should explain return values (e.g., time period, fields). It only states 'quarter-by-quarter history' and token count, leaving agents uncertain about data structure and completeness.
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 0% and the sole parameter 'ticker' is unexplained. The description does not describe valid values, format (e.g., uppercase), or any constraints, failing to compensate for low schema coverage.
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 'Quarter-by-quarter history from SEC filings' clearly states the tool returns historical quarterly data from SEC filings, distinguishing it from siblings like origin_company (company info) or origin_filings (SEC filings list).
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 guidance on when to use this tool versus alternatives such as origin_filings or origin_digest. The description implies it's for quarterly history but doesn't specify contexts or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
origin_transcriptsAInspectSearch earnings call transcripts. Query by topic (ai, trusted_computing, blockchain, data_center, etc.), company ticker, or free text. Returns extracted facts, speakers, and metrics from earnings calls.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Optional: free text search across facts | |
| first | No | Optional: if true, returns first-mention date per company for the topic | |
| topic | No | Optional: topic tag (ai, trusted_computing, blockchain, data_center, quantum, cybersecurity, robotics, autonomous, gaming, etc.) | |
| ticker | No | Optional: filter by company ticker |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden. It correctly implies a read-only search operation but does not explicitly state that no side effects occur. It mentions the output scope (facts, speakers, metrics) but lacks details on rate limits, authentication, or empty result handling.
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?
Two sentences with no wasted words. The purpose, query options, and return types are front-loaded. Every sentence adds value.
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 no output schema, the description fills the gap by stating return types. It covers the main use cases for a search tool. Minor omissions like pagination or default behavior when no parameters are provided are acceptable for this tool's complexity.
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%, so the baseline is 3. The description adds value by providing concrete examples for the 'topic' parameter and clarifying how ticker and free text can be used. However, it does not explain parameter combinations or syntax beyond what the schema already 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?
The description clearly states that the tool searches earnings call transcripts, specifies multiple query dimensions (topic, ticker, free text), and lists the return type (facts, speakers, metrics). This distinguishes it from sibling tools that focus on company info, filings, or people.
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 is provided on when to use this tool versus alternatives like origin_filings or origin_person. The description implies usage for transcript queries but does not mention exclusions or context for choosing among siblings.
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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