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 full burden and discloses important behavioral traits: output shape ('one row each, metadata only'), an error condition ('passing both is an error'), and truncation of large responses to newest rows with a note. It stops short of stating read-only safety or auth requirements, but covers the main operational behaviors an agent needs.

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 usage constraints and truncation behavior. Every sentence earns its place with zero filler or 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 absence of an output schema and annotations, the description adequately explains the result format (rows, metadata only) and the truncation caveat. It might specify the metadata fields or note contents, but it is sufficient for an agent to understand and invoke the 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?

Schema description coverage is 100%, so the baseline is 3. The description adds the mutual exclusivity of show/person and the 'filter rather than page' tip, but these are already present or implied in the schema descriptions. It does not meaningfully enhance understanding of individual parameters 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?

Description states a clear verb+resource: a 'slim catalogue of every episode — one row each, metadata only.' It distinguishes itself through 'slim' and 'metadata only' from likely sibling tools like get_episode or search_episodes, but does not explicitly name alternatives, so it misses the full sibling differentiation that would merit a 5.

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 concrete usage context: how to narrow by show or person, that passing both is an error, and the truncation behavior advising to filter rather than page. This offers clear context for calling the tool, though it does not explicitly route the agent to/away from 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 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 provided, the description carries the full burden. It discloses that the tool returns metadata only (titles, deks, dates, durations, participant chips, source links) and never the digest or transcript, which is a key behavioral trait. It also states ordering (newest first). However, it does not mention pagination details or other side effects, though such details exist in the schema. This disclosure is substantial but not exhaustive.

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 two-sentence composition: the first sentence front-loads the purpose and optional filter, the second specifies output scope and routes to the alternative. Every word serves a purpose, with no repetition or fluff, making it highly concise and structurally effective.

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 7 parameters fully described in the schema and the absence of an output schema, the description adequately covers what is returned (metadata fields) and what is not (content). It does not explicitly mention pagination via next_offset, but that is documented in the offset parameter. The facet filtering (asset, focus, sector) is not described in the description, but the schema covers it. Overall, the description is nearly complete for effective tool invocation, with minor gaps that the schema fills.

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% for all 7 parameters. The description adds minimal parameter-specific meaning beyond the schema; it only reinforces the 'show' filter with 'optionally narrowed to one show,' which is already present in the parameter description. Per the baseline rule for high schema coverage, a score of 3 is appropriate.

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 lists episodes newest first, with an optional filter for a single show. It explicitly defines the resource (episodes), the ordering (newest first), and contrasts with bidclub_get_episode for content, making the purpose distinctive and 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 explicitly says 'Use bidclub_get_episode for content,' directly routing the agent when content (digest/transcript) is needed. It also notes 'optionally narrowed to one show,' giving a clear filter context. This is explicit guidance on when to use this tool versus an alternative.

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 provided, the description carries the full burden and delivers: a 20-row cap, a firm 'never content' boundary, the substring-sweep workaround for Chinese tokenization failures, and the partial: true semantics with concrete caller guidance. The partial-coverage disclosure is exactly the kind of behavioral trait an agent cannot infer from the schema, and it prevents a plausible false-negative report.

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 sentences, every one load-bearing: what it searches, the result cap and content boundary, and the partial-coverage caveat. Core function is front-loaded and nothing is repeated from the schema.

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 9-parameter tool with no output schema and no annotations, the description covers the essential operational facts: search scope, row cap, content exclusion, and the partial: true failure mode. The remaining gaps are the shape of the metadata rows (no output schema to fall back on) and the undefined 'searched_recent' window behind partial coverage, but these are minor given how much the 100% schema coverage and the behavioral notes already provide.

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 of 3 applies; every parameter already carries a meaningful schema description (including the crucial source_lang warning about not setting ZH merely for Chinese output). The description's only added semantic is the 'substring sweep' mechanism behind q and Chinese handling, which lightly reinforces but does not substantively extend 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?

Description states a specific verb and resource: 'Full-text search across titles, deks, TL;DRs, digests and transcripts.' The field list and 'never content' boundary clearly distinguish it from siblings like bidclub_list_episodes (filtered listing), bidclub_get_episode (single retrieval), and bidclub_list_shows (show catalog). An agent can tell this is the search tool without opening a schema.

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?

Context is clear: use this when you need full-text search over content-derived fields, and it warns the caller to surface partial: true coverage rather than report an absence. It also implies via 'never content' that content retrieval belongs elsewhere. However, it never explicitly names alternatives or states when not to use it versus bidclub_list_episodes, so it falls short of a 5.

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