suche

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

No annotations are provided, so the description carries the burden. It conveys a read-only browse behavior via the verb 'browse' and gives examples, but it doesn't disclose potential edge cases like empty results, error behavior, or whether the tool returns additional metadata. For a simple read operation this is acceptable but not rich.

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 action and resource, and no redundant fluff. Every clause earns its place.

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 tool is simple (2 params, no output schema), and the description covers purpose, parameter guidance, and a tag-discovery workflow. It could more explicitly state the return format, but the phrase 'browse Blu-ray movies' strongly implies a list of movies, making the description adequate for an 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 description coverage is 100%, with both tag and limit already described in the input schema. The description adds the pointer to list_tags and reiterates tag examples, but this isn't materially new parameter information beyond what the schema already 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 browses Blu-ray movies by category/tag, using specific examples like 'weihnachtsfilme' and 'action'. It distinguishes itself from sibling tools like browse_movies by specifying the tag-based filtering mechanism, and also names list_tags as a companion for tag discovery.

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 tells agents to use list_tags to discover available tags, which frames when to use this tool. However, it doesn't explicitly contrast with browse_movies or search_movies, though the name and scope imply the distinction.

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 the full transparency burden, but it only mentions that at least one filter is required. It does not describe return format, pagination, filter combination semantics, or error behavior, leaving significant 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 a single, front-loaded sentence that efficiently states purpose and the required condition. No redundant or vague phrasing exists.

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?

While purpose and filter constraint are clear, the lack of output schema means return values are not described. The 'and/or' combination semantics is ambiguous, but the schema covers all parameters, making the description minimally adequate.

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 a critical constraint not in the schema: at least one filter must be provided. It also clarifies that year can be exact or a range, which maps to yearFrom/yearTo.

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 (browse), resource (Blu-ray movies), and filtering criteria (release year and/or genre). It distinguishes from sibling tools like browse_by_tag (tag-based) and search_movies (likely keyword 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 for browsing by year or genre but does not explicitly state when to choose this tool over alternatives like search_movies or browse_by_tag. It lacks when-not-to-use guidance.

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 only says 'Get' without mentioning read-only nature, pagination, return format, or what 'featured' means operationally. The agent gets minimal behavioral context beyond the schema's limit parameter.

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, clear sentence that says exactly what the tool does without waste. It is appropriately concise and easy to parse.

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 tool with one optional parameter and no output schema, the description conveys the core purpose but omits return value details. Given the existence of sibling tools like get_movie_details, the agent might need to know whether this returns summaries or full details, which the description does not address.

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 fully documents the single 'limit' parameter with range and default values, so schema coverage is 100%. The description does not add any parameter-specific meaning, but the schema already handles the semantics, making the baseline 3 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 gets currently featured and recommended Blu-ray movies, using a specific verb 'get' and a clear resource. It does not explicitly differentiate from sibling tools like browse_movies or search_movies, but the focus on 'featured and recommended' provides a distinct purpose.

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 for retrieving featured movies, but provides no explicit when-to-use guidance or mention of alternatives. There are no siblings referenced or exclusions, so the usage is inferred from the purpose rather than clearly stated.

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 is the only source of behavioral information. It discloses what data the tool returns (cast, trailer, external links), but doesn't mention read-only nature, potential errors, or required authentication. It doesn't contradict anything, but lacks depth.

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?

One concise sentence that conveys the core purpose without redundancy. It is front-loaded with the action and 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 simple one-parameter get tool, the description is fairly complete: it states the scope (specific movie) and the content (cast, trailer, links). It doesn't mention error behavior or edge cases, but the lack of an output schema is partially compensated by listing returns. Overall, adequate but not exhaustive.

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 fully documents the 'slug' parameter with a clear description. The tool description adds the context that the movie is specific, but doesn't add detail beyond the schema, so a baseline 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 uses the specific verb 'get' with resource 'detailed information about a specific movie' and lists concrete content (cast, trailer, external links), distinguishing it from sibling tools like search_movies or browse_movies.

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 for looking up a single movie by its slug, but doesn't explicitly state when to prefer this over browse_movies or get_similar_movies, nor provide exclusion criteria. The 'specific movie' wording gives context but no explicit when-to-use or 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?

There are no annotations, so the description carries full burden. It states 'similar or related' with examples, but does not disclose any behavioral traits such as result ordering, pagination, or the exact criteria for similarity. The term 'similar' remains somewhat vague.

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, clear sentence with no unnecessary words. It effectively communicates the tool's purpose and includes useful examples, earning a high score for conciseness and structure.

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 list tool with a well-described schema, the description is minimally adequate. However, it lacks any mention of the return format or default behavior, and with no output schema, an agent may need to infer the response shape. This leaves a noticeable gap in 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?

Schema description coverage is 100% for both parameters (slug and limit). The description does not add any meaning beyond the schema; it only reinforces the need for a specific movie. Baseline 3 is appropriate because the schema already documents the parameters well.

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 uses the specific verb 'Get' and identifies the resource as movies similar/related to a specific movie, with concrete examples (same series, same theme). This clearly distinguishes it from sibling tools like search_movies (general search) and get_movie_details (single movie details).

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: when you have a specific movie and want related ones. However, it does not explicitly mention when not to use it or name alternative tools, so the guidance is only implied rather than explicit.

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 burden. It discloses that the output includes counts and slugs, which is useful, but it does not mention ordering, pagination, or whether empty categories are included. For a simple read-only list, this is adequate but not rich.

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 with no redundancy. It front-loads the primary action and adds a practical usage note, earning its place.

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 has no parameters and no output schema, the description provides the essential information: what it lists, the counts, and how to use the output. It is complete for practical purposes, though it could mention result ordering or pagination if applicable.

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 baseline is 4. The description adds no parameter info (as none are needed) but does explain the relevance of the returned slugs, which indirectly supports usage of a related tool's parameter.

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 all movie categories/tags with counts, and explicitly connects the output to browse_by_tag, distinguishing it from sibling tools. This is a specific verb+resource with clear 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?

The description provides clear usage context by telling the agent to use returned slugs with browse_by_tag, implying this tool is a prerequisite. However, it does not explicitly state when not to use it or mention alternatives, so it lacks full exclusion guidance.

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 discloses the search fields and the database scope, which is useful, but it does not mention result format, ordering, pagination, or explicitly confirm a non-mutating read operation. The word 'search' implies a read-only query, but deeper behavioral context is missing.

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 clearly states the verb, resource, and search fields. It contains no redundant filler or vague phrasing, making it appropriately concise.

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 fully described parameters, the description is mostly adequate. However, with no output schema and no annotations, it does not clarify what the returned results look like (e.g., movie details, IDs) or how the limit parameter affects output. This leaves some ambiguity for an agent, though the basic 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?

Schema description coverage is 100%, and the description repeats some of the query field's meaning but adds no new detail about the 'limit' parameter or value formatting. Thus, the description contributes minimal additional semantic value beyond the schema, warranting the baseline score for full 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 uses a specific verb ('search') and clearly identifies the resource ('Blu-ray movie database') and search fields (title, director, actor, keywords). This distinguishes it from sibling tools like browse_movies or get_movie_details by indicating a query-based lookup across multiple access points.

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 the tool should be used when searching by movie title, director, actor, or keyword. However, it does not explicitly state when not to use it or how it relates to alternatives like browse_by_tag or browse_movies, so only implied usage guidance is present.

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