AskNeedl

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, covering safety and scope. The description adds useful context by listing specific data sources (annual reports, earnings, filings, etc.) and mentioning the tool 'searches' through them, which clarifies behavior beyond annotations. However, it does not detail rate limits, authentication needs, or response format.

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 appropriately sized with two sentences: the first states purpose and scope, the second provides usage guidelines. It is front-loaded with the core function and avoids unnecessary details, though it could be slightly more concise by integrating the two sentences more tightly.

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 complexity (querying diverse financial data), annotations cover safety and scope, and an output schema exists, the description is reasonably complete. It specifies the types of data searched and use cases, but could benefit from mentioning response structure or limitations, though the output schema mitigates this gap.

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 schema fully documents both parameters. The description does not add meaning beyond the schema, as it does not explain parameter usage or constraints. Baseline 3 is appropriate since the schema handles parameter documentation adequately.

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 purpose: 'Query financial data and regulatory filings from Indian capital markets and exchanges.' It specifies the verb 'query' and resource 'financial data and regulatory filings' with geographic scope 'Indian.' It distinguishes from siblings by focusing on Indian markets versus US, NZ, or general web search.

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 clear context for when to use it: 'Use for questions about Indian company financials, governance, market performance, or regulatory compliance.' It implies usage for Indian-specific queries but does not explicitly state when NOT to use it or name alternatives among siblings, though geographic focus helps differentiate.

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?

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the agent knows this is a safe, read-only operation with open-world data. The description adds useful context about the types of sources accessed and the general use cases, but doesn't provide additional behavioral details like rate limits, authentication needs, or specific limitations beyond what annotations cover.

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 efficiently structured in two sentences with zero wasted words. The first sentence states the core functionality, and the second provides usage guidance. Every element serves a clear purpose 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?

Given the tool's moderate complexity, comprehensive annotations, complete schema coverage, and presence of an output schema, the description provides adequate context. It explains what the tool does and when to use it, though it could potentially mention more about limitations or result formats beyond what the structured data provides.

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?

With 100% schema description coverage, the input schema already fully documents both parameters. The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline expectation but doesn't provide extra value regarding parameter meaning or usage.

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 purpose with specific verbs ('search and analyze') and resources ('publicly available information from across the internet'), distinguishing it from sibling tools focused on specific capital markets. It explicitly mentions the types of sources accessed (news sites, blogs, websites, forums).

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 clear context for when to use this tool ('for current events, general research, market trends, industry analysis'), which differentiates it from the more specialized capital markets siblings. However, it doesn't explicitly state when NOT to use it or provide direct alternatives beyond the implied sibling 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?

Annotations already provide readOnlyHint=true, openWorldHint=true, and destructiveHint=false, indicating safe, open-ended, non-destructive operations. The description adds useful context by specifying the scope ('official NZX exchange documents only') and types of documents searched, which goes beyond annotations. However, it does not disclose additional behavioral traits like rate limits, authentication needs, or response format details, which could be helpful despite the 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 appropriately sized and front-loaded, starting with the core purpose and then adding usage guidelines and limitations. Every sentence adds value, such as specifying document types and use cases, with no redundant information. It could be slightly more concise by integrating some details, but overall it is efficient 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 tool's complexity (querying NZX filings), rich annotations (readOnlyHint, openWorldHint, destructiveHint), and the presence of an output schema, the description is complete enough. It covers purpose, scope, usage context, and limitations, which complements the structured data. The output schema likely handles return values, so the description does not need to explain them, making it adequately comprehensive.

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 schema fully documents the two parameters ('question' and 'citations'). The description does not add any parameter-specific information beyond what the schema provides, such as examples or constraints not in the schema. With high schema coverage, the baseline score of 3 is appropriate, as the description does not compensate but also does not need to given the schema's completeness.

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 purpose with specific verbs ('Query', 'searches') and resources ('NZX filings and announcements', 'annual reports, interim reports, continuous disclosure notices, substantial security holder notices, and other NZX regulatory filings'). It distinguishes from sibling tools by specifying 'New Zealand Exchange (NZX)' and 'NZ capital markets and exchanges', differentiating it from tools for other regions like India or the US.

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 clear context for when to use this tool: 'Use for questions about New Zealand company performance, governance, market announcements, or compliance with NZX listing rules.' It also specifies limitations: 'Access is limited to official NZX exchange documents only.' However, it does not explicitly mention when not to use it or name alternatives among the sibling tools, such as when queries involve other regions.

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?

The description adds valuable behavioral context beyond annotations: it specifies the document types searched (10-K, 10-Q, 8-K, etc.), clarifies the scope is limited to SEC filings, and mentions the types of questions it handles. While annotations already indicate read-only, open-world, and non-destructive behavior, the description enriches understanding of what 'open-world' means in this context. No contradiction with annotations exists.

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 efficiently structured with three sentences: the first states the core function, the second enumerates document types, and the third provides usage guidelines and limitations. Every sentence adds value without redundancy, and 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?

Given the tool's complexity (searching multiple document types), rich annotations (readOnlyHint, openWorldHint, destructiveHint), and existence of an output schema, the description provides complete contextual understanding. It covers purpose, scope, usage guidelines, and limitations without needing to explain return values or safety aspects already covered by structured data.

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?

With 100% schema description coverage, the baseline is 3. The description adds meaningful context about parameter usage by specifying that questions should be 'focused' and providing examples of appropriate question types, which helps guide proper tool invocation beyond the schema's technical specifications.

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 purpose with specific verbs ('Query', 'searches through') and resources (SEC filings, financial documents, specific report types). It explicitly distinguishes this tool from siblings by specifying 'US capital markets and exchanges' and 'Limited to official SEC filings and related documents only', making the scope unambiguous.

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 ('Use for questions about US company financials, executive compensation, business operations, or regulatory disclosures') and when not to use it ('Limited to official SEC filings and related documents only'). It implicitly distinguishes from sibling tools by focusing on US markets versus India/NZ markets or general web search.

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