planner

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

With no annotations, the description carries the full burden for behavioral transparency. It only states the action (retrieving balance) but does not disclose whether it is read-only, whether it requires authentication, what side effects (if any) occur, or any rate limits. For a simple query tool, this is minimal but acceptable; however, it lacks explicit safety cues.

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 with no unnecessary words. It is front-loaded with the key information ('Aktuelles Token-Guthaben') and the parenthetical adds relevant context. Every word 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?

Given the tool's simplicity (zero parameters, output schema exists), the description is mostly complete. It clearly states what the tool retrieves. However, a brief mention of the output structure (e.g., 'returns current token count') would improve completeness, but the output schema already covers that, so the description is 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?

The input schema has no parameters and schema description coverage is 100%, so the baseline is 3. The description does not add any parameter semantics because there are none, and it does not need to. It correctly implies no parameters are needed for the operation.

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 the tool's purpose: retrieving the current token balance of the own organization. The phrase 'Aktuelles Token-Guthaben der eigenen Organisation' is clear, and the parenthetical 'Solves kosten Tokens' adds context about the token usage. However, it does not explicitly use a verb like 'get' or 'check', and the German phrasing may be slightly ambiguous for non-native speakers, which prevents a perfect score.

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., solve_submit, service_info). The description does not mention prerequisites, alternatives, or exclusions, leaving the agent to infer usage context from the tool name alone.

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 that incorrect parameter names are silently ignored, which is a useful behavioral trait. However, it does not mention whether the tool is read-only, idempotent, or has side effects, leaving some 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 a single sentence that is front-loaded with the core purpose ('sofort lauffähiger Beispiel-Payload für solve_submit') and then efficiently elaborates on the three kinds. No redundant information, every part 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?

For a simple tool with one optional parameter and an output schema, the description covers the parameter fully and mentions a behavioral detail. It does not explicitly state that the output is a valid payload for solve_submit, but this is implied by the purpose. Sibling tools are diverse and not relevant to 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 input schema has only one parameter (kind) with a default but no description or enum, resulting in 0% schema coverage. The description fully compensates by explaining the three possible values (simple, wishes, rules) and their meanings, adding critical semantic 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 an immediately runnable example payload for solve_submit, with three distinct kinds (simple, wishes, rules) each explained. This distinguishes it from sibling tools like solve_submit, solve_status, etc., which have different purposes.

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 is used to obtain example payloads for solve_submit, but it does not explicitly state when to use it versus alternatives (e.g., before calling solve_submit to test inputs). No when-not or exclusion guidance is provided.

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 fully discloses the returned data fields (version, gitCommit, buildTime). It implies a read-only operation and does not mention side effects, which is appropriate for this simple info 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?

Two sentences, each earning its place: the first states the purpose and data, the second specifies the use case. No redundancy or 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?

Given the tool's simplicity (no parameters, no annotations, output schema exists but description lists the key fields), the description is complete enough. It covers what the tool returns and when to use it.

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 information, which is acceptable since no parameters exist.

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 returns the build status of the Planner-Service, naming specific fields (version, gitCommit, buildTime). This distinguishes it from sibling tools like account_balance or solve_submit, which have different purposes.

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 the tool is intended for support requests and mapping results to a software version, providing clear context. It does not list exclusions, but given the tool's simplicity, this is sufficient 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 bears full responsibility for behavioral disclosure. The description indicates it is safe (returns results) and mentions specific output fields (assignments, unassigned_shifts, statistics), adding value beyond reading. However, it does not state idempotency, rate limits, or potential side effects. It is clear 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 single sentence that lists key output components, which is concise and front-loaded with the main purpose. However, it uses a compact style that blends German and technical terms, which might reduce clarity for some agents.

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 only one parameter and an output schema (which presumably details the return structure), the description is reasonably complete. It lists the main categories of data returned. For a simple retrieval tool, this suffices, but it could explicitly mention that it requires a valid job_id from a completed solve_submit call.

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?

With schema description coverage at 0% and only one required parameter ('job_id'), the description compensates by indicating the parameter identifies a completed job. The description adds meaning by mentioning the job must be 'fertig' (finished). However, it could further clarify the format or origin of job_id.

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 explicitly states it returns results of a completed solve job, including assignments, unassigned shifts with reasons, and statistics. This clearly identifies the tool's purpose and resource. However, it does not differentiate from sibling tools like 'solve_status' or 'solve_submit' beyond implying finality.

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 after a solve job has completed ("fertigen Solve-Jobs"), but it does not explicitly state when to use this versus alternatives like 'solve_status' or 'solve_submit'. No exclusions or prerequisite conditions are provided, leaving the agent to infer 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 carries the full burden. It discloses the status values and progress information, which is the core behavior. However, it does not mention error cases, non-destructive nature, or any other operational details. For a simple status tool, 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 a single concise sentence in German that effectively front-loads the purpose and key details without extraneous text. Every word adds value.

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 with one parameter and an output schema exists (as indicated by context), so the description does not need to detail return values. The description covers the essential status values and progress. It could mention edge cases or prerequisites, but for this tool, the information is largely sufficient.

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 zero description coverage for job_id (0%). The description does not explicitly explain what job_id is, its format, or how to obtain it, aside from referencing a 'Solve-Job'. Since coverage is low, the description should compensate but does not, leaving the parameter merely named.

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: retrieving the status of a Solve job, listing specific status values (pending/running/completed/failed) and progress. This distinguishes it from siblings like solve_submit (submission) and solve_result (final result).

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?

Usage is implied: use this to check a job's status and progress. However, no explicit guidance is given on when to use this instead of solve_result or solve_submit, such as polling before retrieving results. Lacks explicit when-to-use and exclusions.

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 full responsibility for behavioral disclosure. It explains that the tool submits a job and returns {job_id, status}, and mentions privacy requirements. However, it lacks details on potential side effects, long-running nature, error conditions, or permissions needed, which limits 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?

The description is information-dense and each sentence adds value. It opens with the core action, then details the payload, and ends with privacy and cross-reference. While well-organized for plain text, it could be slightly more scannable (e.g., using bullet points for the field list), but overall it's appropriately sized.

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 (many nested parameters, optional fields, special rules) and the existence of an output schema, the description covers all necessary aspects: purpose, required vs. optional fields, data format (ISO dates, IDs), edge case (vacations after end_date), and response structure. It is fully sufficient for an agent to use 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?

With only one parameter 'payload' having a schema that is an open object (additionalProperties: true, 0% coverage), the description fully compensates by listing all required fields (start_date, end_date, department, employees, shifts) and many optional ones (planning_rules, wishes, etc.), plus special notes on data types and constraints. This adds significant meaning 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's action: submitting a scheduling solve job ('Reicht einen Dienstplan-Solve-Job ein'). It distinguishes from siblings like 'solve_result' and 'solve_status' which are for querying results, and 'example_payload' for examples, making its unique purpose obvious.

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 detailed guidance on payload content (required and optional fields), privacy (use IDs), and a special case (vacations may contain dates after end_date). It references 'Instructions' for further context, implying when to use this tool versus others. However, it does not explicitly state when not to use it or contrast with sibling tools.

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