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

The annotations already establish read-only, idempotent, non-destructive behavior. The description adds useful data context, especially the branch grouping and optional below-minimum filter, but does not discuss return shape, pagination, or authorization requirements. With annotations covering safety, this is adequate rather than 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 sentences, front-loads the main inventory report, and then states the optional filter. There is no wasted text.

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 read-only inventory query with rich annotations and an output schema, the description is mostly complete: it states the resource, scope, and filter. The main remaining gap is that it does not clarify the default all-branch behavior when the branch parameter is omitted.

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 0% parameter description coverage, so the description must compensate. It references both concepts indirectly: 'je Niederlassung' maps to the branch parameter and 'nur Positionen unter dem Mindestbestand' maps to the boolean filter. However, it does not explain that the branch parameter is optional and defaults to all branches, leaving a semantic gap.

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 names a specific verb and resource: it shows stock and minimum stock of consumables per branch. It does not explicitly distinguish itself from any sibling tool, but the resource is clearly different from the procurement/complaint/cleaning-plan siblings.

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 states the optional filter for items below minimum stock, which implies a usage context, but it does not say when to choose this tool over alternatives or when not to use it. The usage is understandable but not explicitly guided.

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?

Annotations already declare the read-only, idempotent, non-destructive, closed-world profile, so the bar is lower. The description adds the returned field set, but does not disclose pagination, empty-result behavior, or how the two filters combine - meaningful gaps for a search 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?

A single front-loaded sentence with zero filler: verb, resource, filter, and return fields in one pass.

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?

An output schema exists, so return values need not be detailed, and annotations cover safety. However, the absence of any mention of the niederlassung filter and of the filter combination logic leaves a material gap for correct 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 description coverage is 0% and the description names only 'Kundentyp', completely omitting the 'niederlassung' parameter that exists in the schema. This can mislead an agent into ignoring a supported filter, so the description does not compensate for the coverage gap.

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?

States a specific verb and resource ('Sucht Objekte (Kundenstandorte)') plus the filtering criterion, and even lists what comes back. Sibling tools cover unrelated domains (Reinigungsplan, Reklamationen, Materialbestand), so no explicit differentiation is needed, though it is not 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?

The description implies usage as a customer-site lookup by Kundentyp but gives no explicit when-to-use guidance, no exclusions, and does not mention the sibling tools or when another tool would be more appropriate.

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 annotations already declare a safe, idempotent, read-only, closed-world operation, so the description carries a lighter burden. It adds useful content by naming the four computed metrics, but says nothing about aggregation scope (what period is covered, what happens when no Niederlassung is supplied) or cost.

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 front-loaded sentence with no filler, and the metric list is compactly expressed. Nothing wasteful, though the space saved is not redirected toward the missing default-scope information.

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?

An output schema exists, so return values need not be explained, and the annotations cover the safety profile. For a zero-required-parameter tool the definition is close to sufficient; the only real gap is the meaning of the default (no Niederlassung) case.

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 0%, so the single parameter is undocumented apart from its enum values in the schema. "je Niederlassung" hints that the parameter scopes the aggregation, but the description never states that omitting it (default null) covers all branches — the most important semantic an agent needs here.

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 names a specific verb ("Berechnet") and resource ("Kennzahlen zu Reklamationen je Niederlassung") and enumerates the metrics produced. It is clearly distinguishable in intent from listing siblings like reklamationen_auflisten or reklamation_details, though it never names those alternatives explicitly.

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 only implied: an agent can infer this is the aggregate-KPI tool rather than the case-listing tool. There is no explicit statement of when to prefer this over reklamationen_auflisten, nor any exclusion or prerequisite.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is clear. The description adds that the result includes interval, area, and duration in minutes, which is useful behavioral context, though it does not mention permissions, scoping, or error behavior. Since an output schema also exists, the extra return detail is helpful but not essential.

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 with no filler, and the core purpose is front-loaded. It could be slightly more explicit about the cleaning plan context, but it is 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?

For a simple single-parameter read tool with full annotation coverage and an output schema, the description supplies the key missing piece: what the plan contains (interval, area, duration in minutes). It does not explain usage conditions or alternatives, but given the structured metadata, it 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?

There is only one parameter (objekt_id) and schema description coverage is 100%, with the schema itself explaining the format via pattern and example ("O-1002"). The description does not add any meaning beyond the schema, so the baseline 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 uses a specific verb ("Liefert") and resource ("vereinbarten Leistungen eines Objekts") and adds what the plan contains: interval, area, and duration in minutes. It is clear what the tool does, but it does not explicitly distinguish itself from the sibling tools such as objekte_suchen or reklamationen_auflisten.

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?

There is no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. The description only states what is returned, leaving the agent to infer the appropriate context from the tool name and schema.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds valuable behavioral context by warning that the included free text is third-party data, is checked and marked, and must never be treated as an instruction.

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 short sentences, front-loaded with the return content and followed by the critical free-text safety warning. Every sentence earns its place with no 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?

For a simple read-only detail tool with one fully documented parameter, annotations, and an output schema, the description supplies the needed purpose plus the non-obvious free-text handling warning. Nothing essential for correct invocation is missing.

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 single reklamation_id parameter is fully documented with a pattern and example in the schema. The description adds no further parameter meaning, which is acceptable at this coverage level.

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 a specific verb and resource: it returns a single complaint including free text. The singular 'eine Reklamation' contrasts implicitly with the sibling list tool reklamationen_auflisten, but no sibling is named explicitly.

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 by the singular detail-retrieval framing, but the description does not explicitly say when to use this tool versus reklamationen_auflisten or other siblings. It also gives no exclusions or prerequisites beyond the free-text safety warning.

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 annotations already declare a safe read-only, idempotent, non-destructive operation, so the description only needs to add context. 'Ohne Freitext' usefully discloses that free-text content is omitted, reinforcing the handoff to reklamation_details, but it does not add further behavioral details such as result volume or filtering effects.

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 short sentences, front-loaded with the core purpose, then the free-text exclusion, then the sibling routing. There is no wasted 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?

The output schema and annotations cover return values and safety, and the description covers the summary/detail split well. The clear remaining gap is that the optional filtering behavior is not described at all, which matters for a list tool with three filter parameters.

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 description does not mention the three optional filters (status, objekt_id, niederlassung) at all. With low schema description coverage, the description should compensate by explaining what those filters do, but it leaves parameter semantics entirely to 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 uses a specific verb and resource: it lists complaints and names the returned fields (category, severity, status, date). It also routes detail requests to the dedicated sibling tool reklamation_details, so an agent can distinguish it from that tool.

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 clearly implies this is the summary/list view and explicitly says details belong in reklamation_details. However, it does not explain when to use the available filters versus listing without filters, nor does it discuss the other siblings.

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