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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions retrieving a 'full transcript' but doesn't specify if this is a read-only operation, what format the transcript is in (e.g., text, JSON), or any potential limitations (e.g., availability, error handling). For a tool with no annotation coverage, this lacks critical details about how it behaves beyond the basic 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 concise and front-loaded, with the core purpose stated in the first sentence and usage guidance in the second. Both sentences are relevant and add value, avoiding redundancy. It could be slightly more structured by explicitly separating purpose from guidelines, but it's efficient overall.

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 low complexity (1 parameter, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and some usage context but lacks details on behavioral aspects (e.g., output format, error cases) that would help an agent use it effectively. Without annotations or output schema, more elaboration would improve 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?

The schema description coverage is 100%, with the single parameter 'guest' well-documented in the schema as 'The name of the guest (e.g., 'Shreyas Doshi', 'Julie Zhuo').' The description adds minimal value beyond this, only reiterating 'by guest name' without providing additional context like examples or constraints. This meets the baseline for high 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 clearly states the tool's purpose: 'Get the full transcript for a specific episode by guest name.' It specifies the verb ('Get'), resource ('full transcript'), and key constraint ('by guest name'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'list_episodes' or 'search_transcripts' beyond implying this is for a 'specific episode,' which is why it doesn't achieve a perfect score.

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 some usage guidance with 'Use this when you want to dive deeper into a specific conversation,' which implies this tool is for detailed exploration rather than listing or searching. However, it doesn't explicitly state when not to use it or name alternatives (e.g., 'list_episodes' for overviews or 'search_transcripts' for broader queries), leaving room for ambiguity in tool selection.

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 full burden. It mentions listing 'all available episodes/guests,' which implies a read-only operation, but doesn't disclose behavioral traits such as pagination, rate limits, authentication needs, or what 'available' means (e.g., published status). The description adds minimal context beyond the basic 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 two sentences, front-loaded with the core purpose and followed by a usage hint. Every sentence adds value: the first defines the action, and the second provides context. There is no wasted text, making it 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 is low (0 parameters, no output schema), the description is somewhat complete but lacks depth. It covers the basic purpose and a hint on usage, but without annotations or output schema, it doesn't fully address behavioral aspects like response format or limitations, leaving gaps for an AI agent.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here. A baseline of 4 is applied as it adequately handles the lack of parameters without introducing confusion.

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: 'List all available episodes/guests in Lenny's Podcast archive.' It specifies the verb ('List') and resource ('episodes/guests'), though it doesn't explicitly differentiate from sibling tools like 'get_episode' or 'search_transcripts' beyond mentioning 'to see what guests and topics are available to 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 implies usage context: 'Use this to see what guests and topics are available to search.' This suggests it's for initial exploration before more specific actions, but it doesn't explicitly state when to use this tool versus alternatives like 'search_transcripts' or 'get_episode,' nor does it provide exclusions or prerequisites.

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 the full burden of behavioral disclosure. It describes the search scope ('across all transcripts') and return format ('relevant excerpts from episodes with guest names'), but lacks details on permissions, rate limits, error handling, or pagination behavior. The description doesn't contradict any 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 efficiently structured in two sentences with zero waste. The first sentence states the purpose and return format, while the second provides usage context and examples. Every sentence earns its place by adding 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 the tool's moderate complexity (search functionality with 2 parameters), no annotations, and no output schema, the description does a good job covering purpose, usage, and return format. However, it could be more complete by addressing behavioral aspects like search algorithm characteristics or result ordering.

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 already documents both parameters thoroughly. The description adds marginal value by implying the query should be topic-based ('insights on a topic') and mentioning example topics, but doesn't provide additional syntax or format details beyond what the 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?

The description clearly states the tool's purpose with specific verbs ('search across transcripts') and resources ('Lenny's Podcast transcripts'), and distinguishes it from sibling tools by focusing on search functionality rather than retrieving specific episodes or listing them. It explicitly mentions returning 'relevant excerpts from episodes with guest names'.

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 ('to find what product leaders and experts have said about specific topics'), including example topics. However, it does not explicitly state when NOT to use it or mention alternatives like sibling tools (get_episode, list_episodes) for different use cases.

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