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

No annotations are provided, but the description implies a read-only operation by using 'report'. While it doesn't explicitly state non-destructiveness, the benign nature of a stats tool is conveyed. Slightly lacking full disclosure but acceptable.

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 no wasted words. Front-loaded with the primary output (episodes count and date range) followed by usage guidance. Efficient and readable.

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 simplicity (zero parameters, no output schema), the description adequately conveys purpose and usage. It could mention the return format, but not necessary for basic 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 tool has zero parameters, and schema coverage is 100%. The description does not need to add parameter meaning. Baseline 4 for no 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 clearly states it reports the number of episodes and date range in the local indexed archive, using specific verb 'report' and resource 'local indexed archive'. It distinguishes from sibling tools like search and retrieval by focusing on archive status.

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?

Explicitly states 'Use to check whether the archive is built and how complete it is', providing clear context and purpose. No ambiguity about when to 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, description discloses stem matching, coverage scope, and output components (total, segments/episodes, breakdowns). Missing details on rate limits or idempotency, but sufficient for safe invocation.

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 efficiently convey purpose, use cases, behavior, and limitations. Some repetition ('real occurrence count' vs 'not just how many episodes match') could be tightened, but overall 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?

Despite no output schema, description details return values (total, segments/episodes, breakdowns by year/speaker/top episodes). Covers input, behavior, and output fully for a simple tool with two params.

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 covers both parameters (term, top_episodes) with descriptions. Description adds context: stem/inflection matching for term, default of 10 for top_episodes. Adds value beyond 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 clearly states the tool counts occurrences of a word or phrase across the archive, distinguishing it from sibling tools that return matching episodes or segments. It emphasizes 'real occurrence count' not just episode matches.

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 example queries and clarifies the tool counts occurrences per speaker and year. Mentions coverage limitation (transcribed episodes). Could be improved by noting when not to use (e.g., for exact phrase matching without stemming).

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 description discloses internal data sources and behavior: 'Combines the RSS feed (recent metadata + audio) with the transcript wiki (segments + details).' This is fully transparent despite no annotations, and there is no contradiction.

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 no waste: first sentence defines purpose and contents, second sentence explains data sources and provides guidance on an alternative tool. Front-loaded and efficient.

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 single-parameter tool with no output schema, the description is fully complete: it specifies input, output contents, internal behavior, and when to use a sibling. No gaps.

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 only parameter, episode_number, is already described in the schema (100% coverage). The description adds 'by number' but no additional meaning beyond schema. Baseline 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 starts with a specific verb+resource 'Get a structured overview of one episode by number' and lists the included fields, clearly distinguishing the tool from its siblings, such as get_transcript.

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?

Explicitly states when to use this tool vs. an alternative: 'Use get_transcript for the full text.' This provides clear guidance on which tool to choose based on desired output.

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, and the description does not disclose behavioral traits such as read-only nature, required permissions, or performance implications. Listing contents is not sufficient for transparency.

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 convey all necessary information with no waste. First sentence defines the output; second sentence lists contents and gives a usage hint.

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 (one parameter, no output schema), the description adequately describes the return format (Markdown with frontmatter and transcript). It could be more detailed about the transcript format but is sufficient for its role.

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 has 100% coverage, with a clear description of the single parameter (episode_number). The description adds no additional parameter guidance beyond the schema, meeting the baseline.

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 action (return Markdown document) and the resource (episode from archive). It specifies the contents (YAML frontmatter + clean transcript) and distinguishes itself from siblings like get_episode and get_transcript.

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 explicitly advises 'Use after search_episodes to read the full text,' providing clear when-to-use context. It does not list when not to use, but the sibling list implies alternatives.

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 must disclose behavior. It reveals that the tool reads from an RSS feed (non-destructive), lists recent episodes, and notes that transcripts lag. No permissions or side effects are mentioned, but for a simple read operation, this is adequate.

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 and a note, efficiently front-loading the key information (what the tool does and the returned fields) with no unnecessary 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 list tool with one parameter and no output schema, the description covers the purpose, returned fields, and a practical caveat (transcript lag). It is sufficient for an agent to invoke correctly without additional context.

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 only parameter (limit) is fully documented in the schema with description, min, and max. The description adds no additional semantic value beyond what the schema provides, so the baseline score of 3 applies.

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 it lists recent episodes from the RSS feed and specifies the returned fields (number, title, date, summary, audio URL). This distinguishes it from siblings that retrieve specific episodes or search, making the tool's purpose 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 provides a clear use case ('Use to find the newest episode or recent ones') and includes a note about transcript lag. However, it does not explicitly mention when not to use this tool or suggest alternative tools like search_episodes for query-based searches.

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 behavioral traits: it explains the conditional return of structured answer vs. transcript based on answerKnown, and mentions source links for items. This is transparent for a read-only 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 two concise sentences, front-loaded with the tool's purpose, and every sentence adds value. No redundant or vague wording.

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 (one parameter, no output schema), the description thoroughly explains what is returned and how it varies. It covers all necessary behavioral context for the agent to use it 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%, and the schema already describes episode_number as 'Episode number, e.g. 1075'. The description does not add significant parameter-specific semantics beyond reinforcing the purpose, so baseline 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 retrieves the Science or Fiction segment for an episode, specifying the return content: theme, items with source links, and the fiction item (when available) or transcript. This is specific and distinguishes it from siblings like get_episode or get_transcript.

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 implicit guidance on when to use this tool (for Science or Fiction segments) and explains conditional behavior based on answerKnown. However, it does not explicitly compare to sibling tools or state when not to use it.

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?

Describes the 'cleaned' nature and length warning. Explains section behavior (case-insensitive substring). No annotations, so burden is higher. Missing details on return format or potential errors.

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 concise sentences. First states purpose, second details optional parameter and prerequisite. 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?

Covers main functionality and parameter use. Lacks output schema description (no mention of return format). For a simple tool without output schema, mostly complete but could include what the response looks like.

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%, baseline 3. Description adds meaningful context: full transcript can be long, section is case-insensitive substring. Adds value beyond schema but not extensive.

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?

Clearly states it retrieves cleaned transcript text for an episode. Specifies optional section filter. Distinguishes from siblings by noting to use get_episode first for segment outline.

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 context on when to use the section parameter and recommends using get_episode first. However, does not explicitly mention when not to use this tool or compare with search_transcripts.

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 provided, but description discloses return of 'highlighted snippets with episode metadata', offline nature, and fallback if index missing. No contradictory or missing behavioral info.

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 dense sentences: front-loaded with key purpose and comparison, then details on parameters and fallback. No extraneous 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?

Given no output schema, description adequately covers return type (snippets, metadata). Explains parameters, fallback behavior, and differentiation from sibling. Complete for a search 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 covers all parameters, but description adds value by explaining query syntax (MediaWiki/SQLite FTS), default scope, and purpose of 'field' enum values. Extra detail beyond 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 clearly states it performs 'bm25-ranked full-text search' over the 'LOCAL archive of episode transcripts'. It distinguishes from the sibling 'search_transcripts' by noting it's 'instant, offline, and ranked'.

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?

Explicitly advises to 'Prefer this over search_transcripts for general questions' and explains why. Does not enumerate all exclusions but provides clear context on when to 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?

No annotations provided, but description adequately discloses read-only search behavior, return format, and that each news item is linked to an episode. Does not mention pagination or sorting, but these are minor gaps given the simplicity. No contradictions.

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 efficient sentences plus a concise return fields note. No unnecessary words. Front-loaded with action and scope.

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 search tool with two parameters, the description provides complete information: purpose, usage, and return fields. No output schema, but return fields are listed. Fully adequate for agent invocation.

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 clear parameter descriptions. Description adds no additional detail beyond schema, so baseline score of 3 is appropriate. The parameter semantics are fully captured in 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?

Clearly states it searches science news items, each a topic page tagged with episode number. Distinguishes from sibling tools like search_episodes and search_transcripts by specifying the resource type and return fields (topic title, episode number, link).

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?

Explicitly provides usage scenarios: 'find which episode covered a topic' and 'survey coverage of a subject.' Implicitly distinguishes from alternatives by focusing on news items. Could be improved by explicitly stating when not to use it (e.g., for episode search).

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 describes a read-only search operation but does not explicitly state it is non-destructive or safe. It lacks disclosure about result ordering, pagination, or performance implications, which are typical for search tools.

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 four sentences, front-loaded with purpose, then contrast, use cases, and optional filters. Every sentence adds value without redundancy. 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 5-parameter, 1-required tool with no output schema, the description is nearly complete. It explains the function, return fields, and filters. Missing are details about result sorting, default behavior, or any limitations, but overall sufficient for effective use.

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 the schema already documents parameters well. The description adds minor context (e.g., speaker examples 'Steve', 'Cara') but does not significantly enhance understanding beyond the schema. Baseline 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 this is a fine-grained full-text search over individual speaker turns, contrasting with search_episodes which returns whole episodes. It lists specific return fields (episode, date, segment, timestamp, speaker, snippet), making the tool's purpose and output 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 tells when to use this tool ('find the moment when…', quoting, narrowing within an episode) and contrasts it with search_episodes. It mentions optional filters but does not specify when not to use or other alternatives among the 12 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?

No annotations provided, so description carries full burden. It discloses return format (pages with snippets, episode number, wiki URL) and source (transcripts and topic pages). Does not mention potential side effects or limitations, but read-only nature is clear.

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 front-loaded sentences: first defines scope, second provides examples and output structure. Every sentence adds value with 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 missing output schema, description fully explains return fields (pages with snippets, episode number, wiki URL). For a simple search tool with two parameters, this is complete and avoids ambiguity.

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?

Input schema covers both parameters with descriptions; description adds context that query supports MediaWiki syntax and that limit defaults to 10, which exceeds schema info. Baseline 3 due to 100% coverage, but value added justifies 4.

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 'Full-text search across all SGU episode transcripts and topic pages' with specific verb and resource. It gives example queries and output details, clearly distinguishing from siblings like search_episodes or semantic_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?

Provides example use cases ('every time they discussed CRISPR'), implying appropriate queries, but lacks explicit guidance on when not to use or how it differs from similar siblings like search_episodes or search_segments.

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?

Without annotations, the description carries full burden. It explains the hybrid ranking approach (vector + keyword via RRF), the requirement of an embedding index, and the default provider. However, it does not detail failure modes (e.g., if index missing) or edge cases, leaving some behavioral gaps.

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 (5 sentences) with the key purpose front-loaded. Every sentence adds distinct value: purpose, usage alternatives, algorithm overview, prerequisites, and configuration. No redundancy or fluff.

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 (hybrid search with 3 parameters and a prerequisite index), the description covers purpose, usage, parameters, and prerequisites adequately. It mentions return fields (title, date, theme, score) but lacks detailed return structure or error handling. Still, it is complete enough for an experienced 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?

Schema coverage is 100%, so baseline is 3. The description adds value by providing natural language examples for 'query', explaining default 'limit' (10), and describing 'mode' options with clear interpretations. This goes beyond the schema's basic 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 it performs concept-level semantic search on episodes, using natural language queries. It explicitly distinguishes itself from sibling tools that search for exact words (search_episodes/search_segments), making its purpose 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 provides explicit guidance on when to use this tool ('for fuzzy, conceptual questions') and when to prefer alternatives ('prefer search_episodes/search_segments for exact words'). It also mentions a prerequisite (embedding index) and configuration (EMBED_PROVIDER), aiding correct invocation.

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