PodLexicon

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

There are no annotations, so the description must carry behavioral transparency. It only says 'List', implying a read-only operation, but it does not describe pagination, result ordering, filtering semantics, or what happens when no entries match. This is thin for a tool with no annotation support.

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 short and front-loads the core purpose before the parameter semantics. Every sentence earns its place, though the opening phrase could be slightly more specific about the catalogue resource.

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 no output schema and no annotations, the description should explain limit behavior, return shape, and likely usage boundaries relative to siblings. It only covers `kind` and `query`, leaving important context for an agent deciding how to call the 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 0%, so the description must compensate. It adds meaning by enumerating allowed `kind` values and explaining that `query` filters by name, which is helpful. However, it omits `limit` entirely, leaving that parameter to inference from its name and default.

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 names a clear action ('List') and a resource ('what PodLexicon covers'), and clarifies the kinds of items included ('podcasts', 'topics', 'guests'). This distinguishes it from the episode-focused siblings, though it does not explicitly name an alternative tool.

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 gives no guidance on when to use browse_catalogue versus the sibling tools. It implies a browsing use case but does not state exclusions or point to alternatives like search_episodes or get_episode.

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?

Since no annotations are provided, the description carries the full transparency burden. It does disclose a useful behavioral trait — nearest-neighbour matching over summary embeddings — which implies ranking by similarity and differentiates the tool from search. However, it does not mention return ordering, whether the query episode is excluded, or how missing/invalid episode IDs are handled.

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 concise sentences, each carrying distinct information: the purpose first, then the algorithmic mechanism. There is no wasted wording, and the embedding detail is relevant and informative.

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 no output schema and no annotations, the description is adequate but not fully complete. It gives enough to attempt a call, but omits what exactly is returned, how results are ordered, and any constraints around the episode_id.

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 0%, so the description needed to compensate for the parameters. It only indirectly maps episode_id to 'a given one' and never explains limit or its behavior. The schema default provides some help, but the description adds minimal semantic value for the parameters.

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 names a specific operation ('Find episodes covering similar ground to a given one') and a resource ('episodes'), with the mechanism 'nearest-neighbour over summary embeddings' distinguishing it from keyword search or catalog browsing. This clearly differentiates it from siblings like search_episodes and get_episodes_by even without naming them.

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 gives no explicit guidance on when to prefer this tool over alternatives such as search_episodes or get_episodes_by, and it states no exclusions or prerequisites. An agent must infer the intended use case from the title and the embedding mention.

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 behavioral disclosure burden. It discloses the returned metadata fields and implies a read-only operation, but it does not mention error behavior, missing episodes, authentication needs, or response structure beyond the field list.

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 that names the action, resource, and key output fields with 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?

For a simple single-parameter getter, the description is minimally adequate and lists return fields. It lacks guidance on choosing this tool over siblings, handling missing IDs, and specifying the ID format, so it is not fully 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 0%, so the description must compensate for parameter meaning. It does not explain how to obtain episode_id, what format it expects, or any constraints, leaving the agent to infer everything from the parameter name.

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 states a specific action ('Get') and resource ('an episode's metadata'), and lists concrete fields returned. It is clear enough to distinguish from get_episode_summary, but it does not explicitly name or contrast sibling 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?

The description implies this tool is for retrieving full episode metadata, which indirectly separates it from search or summary tools. However, it gives no explicit when-to-use guidance, conditions, or exclusions relative to the listed siblings.

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 must carry behavioral disclosure itself. 'List' clearly indicates a read-only retrieval operation with no destructive side effects, which is good. However, it does not mention pagination, ordering, how `limit` behaves, or what the response contains, leaving some behavioral ambiguity.

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 compact and front-loaded: the first sentence states the tool's purpose, and the second resolves the key parameter ambiguities. There is no filler, repetition, or unnecessary detail.

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 simple filtered-list tool, the description covers the essential invocation knowledge: what the tool lists and what values the main parameters expect. It also points to `browse_catalogue` for obtaining a valid slug. The absence of any guidance on `limit`, pagination, or return format leaves minor gaps, but the core usage 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?

The input schema provides no descriptions, so the description carries the full burden. It compensates well by enumerating the accepted values for `kind` and explaining that `slug` comes from `browse_catalogue`. The `limit` parameter, however, is never mentioned or explained, which prevents a perfect score.

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 begins with a specific verb and resource: 'List the episodes belonging to one podcast, topic, or guest.' This clearly scopes the tool to fetching episodes by a single entity and distinguishes it from broader search or single-episode tools like search_episodes and get_episode.

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 makes the intended use case clear: retrieve episodes for one podcast, topic, or guest. It also provides the key prerequisite that `slug` comes from `browse_catalogue`, which orients the agent on the correct workflow. It stops short of explicitly naming alternatives or exclusions, so it earns a 4 rather than a 5.

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 word 'Read' conveys a read-only operation, and the token estimates communicate response scale. With no annotations provided, the description carries the full burden, but it does not disclose output structure, error behavior, or what happens when no summary 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 compact and front-loaded, with the purpose stated first and the parameter clarification placed immediately after. Every sentence earns its place without fluff or repetition.

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 two-parameter read tool, the description covers the basics, but with no output schema and no annotations it leaves some context unstated, such as what exactly is returned, especially for the 'topics' detail level. It is adequate but not fully 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?

The description adds meaningful value by explaining the `detail` parameter's allowed values ('brief', 'detailed', 'topics') and approximate token sizes, which the schema does not provide. The required `episode_id` is left to its self-explanatory name, but the most ambiguous parameter is well covered.

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 verb ('Read') and the resource ('an AI-generated summary of one episode'). It distinguishes itself from siblings like get_episode and search_episodes by focusing on the summary, though it does not explicitly name any sibling.

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: use this tool when you want an AI-generated summary of a single episode rather than the episode itself or search results. However, it gives no explicit when-to-use guidance, preconditions, or direct comparison with 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?

With no annotations, the description carries the burden and does reveal the key behavior: it returns a ranked shortlist with one-line hooks, not full content, and directs to get_episode_summary for full reads. It does not specify ranking criteria or pagination, but for a read-only search that is a minor gap.

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 the core purpose front-loaded and a clear follow-up instruction; no filler or repetition of schema details.

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 simple two-parameter search tool with no output schema, the description covers the return shape and next step well. It is only slightly incomplete in not explaining the limit parameter or ranking basis and not contrasting with sibling search 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?

Schema coverage is 0%, and the description adds meaning to query by equating it to a topic. However, limit is left entirely to the schema's name/default, so not all parameter semantics are compensated in the description.

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?

States a specific verb and resource: search/find podcast episodes by topic, and clarifies the return is a ranked shortlist with one-line hooks. It doesn't explicitly name sibling tools like find_similar_episodes or get_episodes_by, so differentiation is implied rather than stated.

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 gives clear context for a topic-based search and routes follow-up to get_episode_summary, but it does not say when to prefer this over find_similar_episodes or browse_catalogue. No exclusions or explicit alternative-selection guidance is provided.

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