Venture Atlas

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

No annotations are provided, so the description must carry behavioral information. It mentions that every field carries source URLs, which is useful, but it omits other traits like read-only nature, auth requirements, 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?

Two sentences, front-loaded with the core purpose, then a list of content, and a final note about source URLs. Every word adds value, 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?

Given no output schema, the description lists many returned fields, giving good context. Minor gaps: no mention of response structure or error handling, but the enumeration is thorough.

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 descriptions for both parameters. The description adds value by telling users to use 'search_companies' for the slug and noting that includeOverview is 'Large; off by default', which goes beyond schema definitions.

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 specifies 'Full Venture Atlas profile for one company' and enumerates all included components (summary, metrics, milestones, etc.). It implicitly distinguishes from siblings like 'search_companies' (search) and 'latest_news' (news only).

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 retrieving a comprehensive profile but does not explicitly state when to use this vs siblings like 'list_upcoming_milestones' or 'latest_news'. No when-not or alternative guidance is provided.

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 adequately discloses the behavior: it returns a digest of sourced summaries, newest first, and is read-only. No destructive or side effects are implied, and the input parameters for filtering are transparent.

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 three sentences, each serving a purpose: naming the tool, describing the content, and explaining filters. No unnecessary words; front-loaded with identity.

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 sufficiently explains what the tool returns (summaries with companies, dates). It covers filtering and ordering. Minor gap: no mention of pagination or how to handle multiple pages, but 'limit' parameter implies truncation.

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 descriptions for all parameters. The description adds context about the digest's content and ordering ('newest first'), which goes beyond the schema. This additional context helps the agent understand the tool's behavior.

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 identifies the tool as a news digest ('Venture Atlas daily news digest'), specifies ordering ('newest first'), and describes the content of each item. It is distinct from sibling tools like 'get_company' and 'list_upcoming_milestones', which serve different purposes.

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 how to filter by company or date, implying when to use the tool (to get news). It does not explicitly state when not to use it or mention alternatives, but the context is clear enough for typical use.

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 carries the burden of disclosing behavior. It explains that the tool returns milestones with target dates, source, and track record, sorted soonest first, and allows optional inclusion of undated milestones. This provides good insight into what the tool does and its output characteristics.

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 concise at four sentences, front-loaded with the core purpose. Every sentence adds value: defining the output, ordering, filter options, and an extra detail about included data (source, track record). 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?

Despite no output schema, the description adequately explains the return values (milestones with dates, source, track record, sorted) and filtering capabilities. It covers essential behavioral aspects like ordering and optional inclusion of undated milestones. The tool's complexity is low, and the description is 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 adds minor context by mentioning that company and industry are for filtering and that includeUndated sorts last, but it does not significantly enhance understanding beyond the schema's own parameter 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 the tool returns 'announced, still-upcoming milestones with target dates across all tracked companies, soonest first.' This distinguishes it from sibling tools like get_company (single company details) and latest_news (news), as it focuses specifically on forward-looking milestones across companies.

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: it's for viewing upcoming commitments sorted by target date. It explicitly mentions filtering by company or industry, giving direction on parameter use. However, it does not explicitly state when not to use this tool or compare it to alternatives like get_company for past milestones.

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; description discloses matching behavior and return type (slim records with trimmed brief), but omits details on pagination, rate limits, or read-only nature. Adequate for a search 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 sentences, no wasted words. Purpose is front-loaded, all information is relevant and efficiently conveyed.

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, description adequately explains return value (slim records with brief) and redirects for full data. Covers all three parameters and usage scenarios. Almost 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 coverage is 100%, so baseline 3. Description adds context for query (free-text, can omit) and industry, but adds little beyond schema for limit. Meets minimum expectation.

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 explicitly states the tool searches companies by free text and/or industry, listing specific fields matched. It clearly distinguishes from sibling tool get_company by noting slim records vs. full profile.

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 clear context: when to use (search by text/industry), omitting query to list all in industry, and directs to get_company for full profiles. Lacks explicit when-not-to-use but sufficient.

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