SEC EDGAR

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

No annotations are provided, so the description must carry behavioral disclosure. It mentions classified event types but does not detail data freshness, rate limits, or potential empty results. Lacks full transparency for a read 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?

Two efficient sentences with no wasted words. Front-loaded with the tool's purpose, then example usage. Every part 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?

Given the tool has 4 parameters, no output schema, and no annotations, the description is adequate but not rich. It lacks details about return format, pagination, or how event types classify filings.

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 25% (only 'since' has a schema description). The description adds meaning by implying that 'cik' or 'ticker' identify the company, but it does not elaborate on 'limit' or 'since' beyond schema defaults. Moderate additional value.

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 it retrieves recent 8-K filings with classified event types for a company. The specific verb 'get' and resource '8-K' are clear, and the description distinguishes from sibling tools by focusing on material event filings.

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 provides a usage scenario: 'Use this when the user asks has anything material happened with <company>'. This gives clear context, though it doesn't explicitly contrast with when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries the burden. It describes what the tool returns (metadata) but does not explicitly state that it is read-only or non-destructive. For a simple lookup, this is adequate but could be more explicit.

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 purpose, then usage guidance. No wasted 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 no output schema, the description lists the expected fields (legal name, SIC, exchanges, fiscal year end), which is sufficient for a simple metadata query. Could mention if pagination or limits exist, but not critical.

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. The description only repeats the parameter semantics ('by ticker or CIK') without adding new information. 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 that the tool retrieves company metadata by ticker or CIK, listing specific fields (legal name, SIC, exchanges, fiscal year end). It also distinguishes from sibling tools by indicating usage before drilling into filings.

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 provides usage context: 'Use this when the user wants to know who/what a company is, before drilling into filings.' This gives clear guidance on when to use the tool versus alternatives (e.g., filing tools).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description discloses key behaviors: it accepts aliases or XBRL concepts, returns one row per fiscal period, and prefers latest-filed when amendments exist. This gives the agent a good sense of the tool's operation, though it omits details like authentication or rate limits.

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, front-loaded with the primary action, and each sentence adds essential information. No redundant or 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 no output schema, the description partially describes the output (one row per fiscal_year/fiscal_period) but does not specify the fields in the returned rows or handle error cases. It is adequate but could be more complete for a tool with 3 parameters and no output schema.

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 already covers all parameters (100% coverage), but the description adds value by explaining the concept parameter accepts common aliases (e.g., 'revenue') or XBRL concepts, and notes the output structure (one row per period). This enriches the schema alone.

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 XBRL-structured financial facts for a company, listing specific metrics like revenue, operating income, etc. It distinguishes itself from sibling tools (e.g., edgar_get_8k, edgar_read_filing) by focusing on structured financial data.

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 explains what the tool does and what inputs it accepts (common aliases or XBRL concepts), but it does not explicitly guide when to use this tool over alternatives or mention prerequisites or exclusions. Sibling tool names are provided but no direct comparison.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations, so description carries burden. Explicitly discloses truncation behavior. Could mention error handling or rate limits, but overall good.

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, no wasted words. Front-loaded with purpose and method. Highly efficient.

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?

Adequate for a simple read tool with no output schema. Discloses key limitation and usage tip. Could mention error cases but not critically missing.

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 100% with descriptions. Description adds context: 'truncates' implies no full text guarantee, and mentions CIK zero-padding. Adds value beyond 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?

Clearly states 'Fetch the full text of a specific filing by accession number', with specific use case for 10-K/8-K. Differentiates from siblings like edgar_search_filings.

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?

Specifies when to use (want to read content), limitation (truncation at ~80K), and suggests using search first. Lacks explicit comparison to siblings but provides actionable guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries full responsibility for disclosing behavioral traits. It only describes the basic read operation (search/filter) and does not mention any side effects, safety (e.g., being read-only), rate limits, or limitations. The agent is left without information on whether the tool is destructive or has any constraints beyond what is stated.

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: two sentences covering purpose, capabilities, and usage guidance. Every sentence adds value with no redundancy. It is front-loaded with the core action and then provides a usage example, making it easy to scan.

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 6 parameters and no output schema, so the description should compensate by describing the expected return value or behavior. It only vaguely says 'Returns recent filings...' without specifying the structure, count, or pagination. For a search tool, more detail on the output format is needed to ensure correct invocation and result handling.

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%, meaning each parameter already has a description in the schema. The tool description reiterates that it filters by ticker/CIK, form type, and date range, but does not add significant new meaning beyond the schema. According to the rubric, when schema_description_coverage is high, baseline is 3; the description does not exceed that.

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 action ('Search SEC EDGAR filings'), the resource ('for a US-listed company'), and the result ('Returns recent filings... filtered by ticker or CIK, form type, and date range'). It also provides a usage example ('when the user asks...'), which differentiates it from siblings that are more specific (e.g., edgar_get_8k). The purpose is unambiguous and well-articulated.

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 explicit guidance on when to use the tool: 'Use this when the user asks "what did <company> file" or needs to find a specific filing.' This provides clear context. However, it does not mention when not to use it or point to sibling tools as alternatives, so it lacks exclusions. Still, the context is strong enough to guide an agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.