leadership-agent

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

Annotations are absent, so the description must carry the full burden. It states the tool explains the BANI model but does not disclose any behavioral traits such as whether it is read-only, requires authentication, or has side effects. The agent cannot infer safety or resource impact.

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, well-structured sentence that immediately conveys the tool's purpose. Every word is necessary; there is no redundancy or extraneous content. It is appropriately sized for a simple informational tool.

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, the description could provide more context about the return format or level of detail. It mentions four dimensions, leadership consequences, and chapter references, but does not specify whether the output is a paragraph, list, or structured text. This is adequate but not complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and schema coverage is vacuously 100%. Per rubric, baseline for 0 parameters is 4. The description adds no parameter info but none is needed. This score reflects adequate handling of the parameterless case.

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 purpose: 'Erklärt das BANI-Modell und seine vier Dimensionen mit Führungskonsequenzen und Kapitelverweisen.' It uses a specific verb ('erklärt') and identifies the resource uniquely. Among siblings like 'glossar' (glossary) or 'kapitel_these', this tool stands out as a focused explanation of the BANI model.

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?

No guidance is given on when to use this tool versus alternatives. There is no mention of context, prerequisites, or when not to use it. The description describes what it does but does not help the agent decide between this and 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. It only says 'current status' without disclosing what the status entails, whether it's read-only, or any other behavioral traits. This is minimally transparent.

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, concise sentence. It is appropriately front-loaded and efficient, though it could benefit from additional context without becoming overly verbose.

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 parameters, no output schema, and no annotations, the description is minimal. It does not explain what the status response looks like or any other details, leaving the agent with insufficient information to fully understand the tool's behavior.

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 description does not need to add parameter semantics. Baseline is 4 per the guidelines.

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 that the tool returns the current status of a public AI marketing experiment. It uses a specific verb-noun combination, making the purpose clear. However, it does not differentiate from sibling tools because no sibling descriptions are provided.

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?

No guidance is given on when to use this tool versus alternatives. The sibling tools are listed but not described, so the agent cannot determine appropriate usage 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?

No annotations are provided, so the description alone must convey behavioral traits. It discloses the output (definition, origin, chapter) but does not mention read-only nature, required permissions, or any side effects. The description is adequate but not comprehensive.

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, 17-word sentence that is front-loaded with the core purpose. It contains no redundancy and is appropriately sized for the tool's simplicity.

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 optional parameter, no output schema), the description provides sufficient context: it explains the domain, the input parameter, and the output components. It could be slightly improved by mentioning the output format (e.g., language) but is mostly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage with a description for the single parameter 'begriff', which includes examples and default behavior. The tool description adds context by specifying the source ('Zukunft führen') and the components of the output, enriching the parameter semantics beyond the schema alone.

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 that the tool provides a definition of a leadership term from 'Zukunft führen', including definition, origin, and chapter reference. The verb 'Gibt' is specific, and the resource is distinct from sibling tools like 'bani_einordnung' or 'experiment_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?

The description implies that the tool is used for retrieving glossary definitions, but it does not explicitly state when to use it over siblings or when not to use it. No exclusions or alternatives are mentioned, relying solely on the implied 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?

No annotations provided, and the description does not disclose behavioral traits such as side effects, authorization needs, or error handling. It only states it returns an overview, leaving agents unaware of read-only nature or potential issues.

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, efficient sentence conveying core functionality. It is front-loaded with key information, though slightly ambiguous for non-German speakers. 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 tool with one optional parameter and no output schema, the description adequately conveys the purpose. However, it does not specify the return format (e.g., list, text) or handling of invalid input, leaving some 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?

Schema already covers the parameter (chapter number 1-24, empty for overview) with 100% coverage. The description adds that providing a number yields title and act, which provides marginal additional context 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 clearly states the tool provides a chapter overview of 'Zukunft führen' with chapter numbers, titles, and acts. It distinguishes itself from siblings like 'glossar' or 'bani_einordnung' by focusing on chapter structure, but does not explicitly differentiate.

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?

No guidance on when to use this tool versus alternatives. The description only explains what it does, not context or exclusions. Lacks any when-to-use or when-not-to-use information.

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 does not disclose any behavioral traits beyond the purpose. Since no annotations are provided, the agent has no information about side effects, read-only nature, authentication needs, or response format. The tool's behavior is essentially a black box.

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 sentence, concise and front-loaded with the key purpose. However, it lacks any structural elements (e.g., bullet points) that could improve readability for an agent.

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 parameter and no output schema, the description provides the basic purpose but misses important contextual details like when to use it, what happens when invoked, and any constraints. Given the absence of annotations, the description should be more thorough.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already describes the 'thema' parameter with examples. The tool description adds no additional meaning beyond what is in the schema. With 100% schema coverage, baseline is 3, and the description does not improve it.

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 indicates the tool provides a 'short impulse' for acute leadership situations with a chapter reference. The verb is implied rather than explicit, and the resource is somewhat vague ('acute leadership situation'). It distinguishes from siblings like 'bani_einordnung' or 'glossar', but the specific action is not clearly stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus its siblings (e.g., bani_einordnung, experiment_status). There is no mention of prerequisites, alternatives, or contexts where the tool is inappropriate.

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