bidclub

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

With no annotations provided, the description carries the burden. It discloses that the tool does not fetch anything (no side effects), that the generated URLs are for download, and that using one yields a complete transcript in one request. It stops short of detailing URL format, authentication, or expiration, but for a URL-builder tool, the core behavioral traits are clearly conveyed.

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, immediately front-loaded with the verb and resource. Every clause earns its place: the no-fetch note, the use-case contrast with bidclub_get_episode, and the required-parameter condition. No redundancy or filler.

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 3 simple parameters, no output schema, and no annotations, the description covers the essential context: what the tool does, when to use it, and the key constraint. It could have specified the output format (e.g., 'returns a JSON object of URLs'), but the absence is not critical since the purpose is clear.

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 documents all three parameters, so baseline is 3. The description adds value by clarifying the mutual exclusivity of slug and show ('Exactly one... required') and linking each to 'episode' vs 'whole show', which the schema does not explicitly state. This extra semantics raises the 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 clearly states the tool's action ('Build the download URLs'), the resource ('an episode or a whole show'), and the key property ('without fetching anything'). It also distinguishes itself from siblings by contrasting with bidclub_get_episode, making its purpose unmistakable.

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?

It provides explicit usage guidance: hand the URLs to the user, or fetch one to get a complete transcript in a single request instead of paging through bidclub_get_episode. It also states the required condition ('Exactly one of slug or show is required'), giving clear direction on when to use this tool.

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 transparency burden. It discloses important behaviors: large responses are truncated to the newest rows with a note, and mutually exclusive parameters cause an error. It also states 'metadata only', clarifying that full episode content is not returned. This is valuable beyond the schema.

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?

Three concise sentences with no wasted words. The purpose is front-loaded, and each sentence adds critical information: what it is, how to filter, and the truncation caveat.

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 description covers the tool's purpose, filtering, error condition, and truncation. Given the simple schema and no output schema, it leaves out only minor details like the exact metadata fields returned and sorting behavior, which are not essential for a basic index 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 coverage is 100% and both parameters have descriptions. The description adds extra semantics: the mutual exclusivity requirement and the truncation behavior that makes filtering important. This goes beyond the schema's basic parameter 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 identifies the tool as a feed index: a one-row-per-episode, metadata-only catalog. It differentiates itself from sibling tools like list_episodes or search_episodes by emphasizing 'slim' and 'metadata only', and mentions the ability to narrow by show or person. However, it does not explicitly contrast with any specific 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?

Provides explicit usage guidance: narrow with show or person, warns that passing both is an error, and advises filtering rather than paging due to truncation. This gives clear operational context, though it does not name alternative tools or state when not to use this tool.

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 full burden and excels: it discloses deterministic pagination (truncated: true, next_offset), instructs to concatenate content_md until next_offset is null, and explains lang is an output edition, not a filter, with lang_fallback behavior. This goes far beyond what a schema conveys.

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?

Three dense sentences, each earning its place: the first states the core action, the second explains the pagination protocol, and the third clarifies lang semantics and size warning. Front-loaded with 'Read one section', 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 tool with 5 parameters, no output schema, and pagination complexity, the description is remarkably complete. It explains the return fields (truncated, next_offset, content_md), paging mechanics, section size differences, and lang fallback, covering everything an agent needs to invoke and process results correctly.

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 solid per-parameter descriptions, so the baseline is 3. The description adds meaningful semantics beyond the schema: it explains the paging contract between offset, next_offset, and content_md, and clarifies the lang fallback behavior for transcripts, which the schema only hints at.

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 opens with 'Read one section of an episode', a specific verb+resource that clearly distinguishes this from sibling tools like lists, search, and download links. It also specifies the section types (tldr, digest, transcript) and the episode slug parameter, leaving no ambiguity about scope.

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?

It gives explicit guidance to 'Prefer tldr or digest' and warns that a transcript can exceed 100,000 characters and is rarely worth paging in full. While it doesn't directly contrast sibling tools, it clearly advises on section selection and warns against requesting a different lang for transcripts, providing practical when-to-use and when-not-to-use context.

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 full burden and does so well: it discloses 'metadata only — titles, deks, dates, durations, participant chips and source links — never the digest or transcript.' It also states the ordering ('newest first') and optional narrowing, giving a clear behavioral contract.

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 action and key output. Each sentence is informative without fluff, and the pointer to the sibling tool is efficiently integrated.

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 description covers what is returned and what is not, plus points to the content tool. Pagination is left to the schema's offset description, which is acceptable. For a listing tool with optional parameters, this is nearly complete, missing only explicit mention of pagination behavior in prose.

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 is 3. The description doesn't add new parameter details beyond the schema, but it reinforces the optional show filter. No extra semantics are needed given the schema's thorough 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's function: 'List episodes newest first, optionally narrowed to one show.' It specifies ordering, filtering scope, and explicitly differentiates from content retrieval by noting it returns metadata only and points to bidclub_get_episode for content.

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 an explicit alternative: 'Use bidclub_get_episode for content.' It implies this tool is for browsing metadata rather than retrieving full episodes. Though it doesn't explicitly contrast with search or list_shows, the guidance is clear enough for common use cases.

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 burden of disclosing behavior. It clearly states that the tool lists every show (i.e., no filtering) and specifies what data it returns. While it doesn't explicitly say 'read-only,' the verb 'List' strongly implies a non-mutating operation, which is sufficient for this simple listing 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?

The description is only two sentences. The first sentence delivers the core action and return fields, and the second sentence provides usage guidance. Every word earns its place; there is no 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?

Given the tool's simplicity (no parameters, no output schema, no complex behavior), the description fully covers what the tool does, what it returns, and when to use it. No additional context is necessary for an agent to select and invoke this tool correctly.

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 tool has zero parameters, so the schema is empty and the baseline is 4. The description adds value by indicating that no parameters are needed ('List every show') and by describing the output fields, which is meaningful context beyond the empty 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?

The description opens with a specific verb ('List') and resource ('every show in the BidClub library'), and enumerates the exact fields returned (id, display name, source language, hosts, source links). This clearly distinguishes it from sibling tools like list_episodes or search_episodes, which focus on episodes rather than shows.

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 explicitly states when to use this tool: 'Start here when you need a show id for the show parameter of the other tools.' This gives the agent a clear trigger condition and positions the tool as the preliminary lookup step before using siblings like bidclub_list_episodes or bidclub_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?

With no annotations, the description fully discloses behavior: it explains the substring sweep for Chinese, the 20-row metadata limit, and the partial: true response flag. This goes beyond standard expectations and gives the agent critical handling instructions.

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 well-structured sentences with no filler. The primary action is front-loaded, and every clause contributes functional detail, from search fields to return limits and partial-result handling.

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 having no output schema or annotations, the description covers the key aspects an agent needs: what is searched, what is returned, the result limit, and how to handle partial results. This is sufficient for correct invocation and result interpretation.

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 describes all six parameters with 100% coverage, so the description adds only marginal value for 'q' via 'substring sweep'. The extra context on substring handling is useful but does not substantially enhance parameter understanding beyond the 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?

The description opens with 'Full-text search across titles, deks, TL;DRs, digests and transcripts', clearly stating the verb ('search') and the resources. It differentiates itself from sibling tools like get_episode and list_episodes by specifying it returns metadata rows rather than content.

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 operational context, including how to interpret partial results ('say so rather than reporting an absence'). However, it does not explicitly contrast with sibling tools or state when not to use this tool, 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.