Stalsoft – Dr. Alex Stolz, IT- und KI-Beratung

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

Annotations already indicate a safe read-only, idempotent operation. The description adds valuable behavioral context by specifying the exact informational scope: the four steps from initial contact to project start, including conditions and billing models. This goes beyond the annotations and clarifies what the agent will receive.

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 packs in the essential information: the four steps, the phases, and the additional details on conditions and billing. It is front-loaded and free of 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 parameterless, read-only tool with no output schema, the description is sufficiently complete. It conveys the tool's subject matter clearly enough for an agent to decide when to invoke it. A minor gap is the lack of an explicit statement that the tool 'shows' or 'provides' this content, but the context makes this obvious.

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 zero parameters, the baseline is 4. The description correctly has no parameter-related text, and no additional explanation is needed since there are no inputs.

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 identifies the resource ('Ablauf einer Zusammenarbeit') and its content (the four steps, conditions, and billing models). It avoids tautology and distinguishes from sibling tools like 'kontakt' or 'leistungen'. However, it lacks an explicit verb such as 'returns' or 'displays', making the tool's action slightly implicit.

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 does not provide explicit guidance on when to use this tool versus alternatives. It merely describes the content, leaving it to the agent to infer that this is the appropriate tool for questions about the collaboration process. No exclusions or alternative tool references are given.

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, and destructiveHint=false, covering the safety profile. The description adds the filtering behavior and website scope, but no additional behavioral traits like pagination or order. It doesn't contradict annotations and adds some context, but the bar is low.

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 examples and a dash structure, front-loading the core function. Every word contributes; no wasted content.

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 FAQ tool with one optional parameter, the description is complete. It covers the main behavior, examples, the empty-parameter case, and the website scope. No output schema is needed at this complexity.

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% for the single parameter 'frage', which is fully described as a search term or question, empty for all entries. The description reinforces this with examples but adds little beyond the schema, so the 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 resource ('Die häufigen Fragen und Antworten der Website') and the action (retrieve complete or filtered by a search term). It differentiates from siblings like 'website_durchsuchen' by being FAQ-specific and explicitly mentions filtering capability.

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 gives clear usage context: you can retrieve all FAQs or narrow by a search term, with concrete examples (Remote, Abrechnung, GEO). It doesn't explicitly mention alternatives or when not to use it, so it falls just short of full guideline coverage.

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 indicate read-only and idempotent behavior. The description adds valuable behavioral context by explaining the conditional return: full-text passage with an ID, or a table of contents (with ID, section, and title) without one. This goes beyond safety hints and clarifies output expectations, though it does not discuss errors, pagination, or auth requirements.

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-loaded with the primary purpose, and covers both usage modes without redundant words. Every sentence contributes meaningful information, making it an excellent example of concise, structured documentation.

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, and rich annotations—the description fully covers all necessary aspects. It explains both invocation modes, the content of the response, and its relationship to the search tool. No critical information is missing for an 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?

The schema describes 'id' as the passage identifier with an example, achieving 100% coverage. The description adds provenance by stating the ID comes from "website_durchsuchen", which is not in the schema and helps the agent understand where to obtain valid values. This additional context elevates the semantics above the schema 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 tool's function: "Liefert eine Passage der Website im Volltext" (delivers a full-text passage), and it distinguishes itself from siblings by referencing the ID from "website_durchsuchen". The no-ID case (returning a table of contents) is also explicitly described, leaving no ambiguity.

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: use the ID from "website_durchsuchen" to retrieve a specific passage, or omit the ID to get an overview. This establishes the prerequisite workflow and clearly defines when each mode is appropriate, which is more explicit than just stating the tool exists.

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 read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations by explicitly stating that no personal data is accepted and that the user must submit the inquiry themselves, clarifying the tool's non-actionable nature and what information it provides.

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 consists of two focused sentences. The first front-loads the purpose, and the second clarifies the user's action and privacy boundary. No redundant phrases or filler, making it easy to scan.

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 contact-info tool with one optional parameter, strong annotations, and no output schema, the description covers all essential aspects: contact routes, response time, consultation terms, and the no-personal-data policy. It is complete for the tool's purpose.

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 describes the single parameter 'thema' with an example, so the description adds little beyond the schema. The mention of 'vorbereiteter Betreffzeile' aligns with the theme parameter but does not significantly extend its semantics; the baseline 3 is appropriate given full schema 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 clearly identifies the tool as providing contact routes ('Die Wege zu einer Anfrage') and enumerates email with prepared subject line, website form link, response time, and initial consultation terms. It distinguishes itself from sibling content tools by focusing on contact, though it lacks an explicit verb like 'zeigt' or 'liefert'.

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 that the interested party submits the inquiry themselves ('Die Anfrage stellt der Interessent selbst') and that the interface does not accept personal data, which clearly signals its read-only informational role. It gives clear context and an implicit exclusion but does not explicitly name alternative 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds minimal behavioral context beyond that: it mentions the optional filtering capability, but this is also already covered by the parameter schema. No contradiction with annotations.

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 front-loads the core purpose, then lists content areas and closes with the optional filter. No wasted words; every segment 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 (one optional parameter, no output schema, no nested objects) and rich annotations, the description fully covers what the tool returns and how it can be filtered. It is complete for its complexity.

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 parameter is documented. The description adds value by listing all six competency area names, which serve as concrete valid values for the 'bereich' parameter, going beyond the schema's examples (KI, Cloud, GEO). This enriches the parameter's semantics.

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 provides the six competency areas of Stalsoft with detailed descriptions, listing them explicitly (IT strategy, AI, data analysis, cloud/DevOps, software architecture, SEO/GEO/accessibility). This specific verb+resource scope distinguishes it from sibling tools like faq or profil.

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 makes it obvious when to use the tool (when information about Stalsoft's service areas is needed) and mentions the optional filter, but it does not explicitly name alternatives or when-not-to-use scenarios. This is clear context without 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the scope of content (career, teaching, languages, links) but does not disclose any additional behavioral traits like response format or limits. Given the annotations, 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 sentence but packs in a lot of detail with a clear front-loaded lead ('Wer hinter Stalsoft steht'). It could be slightly trimmed, but every piece of information serves a purpose in conveying the tool's content. Overall efficient and 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?

For a simple informational tool with no parameters and no output schema, the description fully covers what the tool returns: a short profile with specific sections. There are no gaps that would leave an agent uncertain about invoking this 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?

The tool has zero parameters, so the input schema is empty. The description appropriately focuses on what the tool returns rather than parameter syntax. Baseline of 4 for no-parameter tools is appropriate, and the description adds no unnecessary parameter noise.

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 short profile of Dr. Alex Stolz, including academic and industrial career, teaching, experience, languages, and profile links. This specific verb+resource pairing distinguishes it from sibling tools like 'publikationen' (publications) or 'kontakt' (contact), making it unmistakable.

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 opening phrase 'Wer hinter Stalsoft steht' sets clear context for when to use this tool (when wanting to know about the person behind the company). While it doesn't explicitly mention alternatives or exclusions, the content makes the usage obvious in relation to the 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds context about the content (e.g., RDF Translator, publication list) but does not disclose return format or any additional behavioral details, which is acceptable given the annotation coverage.

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 efficiently lists key topics without redundancy. It is somewhat dense but remains readable and front-loads the main subject.

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 parameter-free informational tool, the description adequately covers the scope of content (research areas, publications, tools, directories). It does not specify the response format or whether it returns a list of publications, but the title and annotations make the intent sufficiently 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?

The tool has zero parameters, so schema description coverage is 100%. The description adds contextual value by listing the types of content included, but there are no parameter details to explain.

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 identifies the tool's subject matter (research foci, publications, developed tools, directories) and distinguishes it from sibling tools by topic. However, it lacks an explicit verb like 'retrieves' or 'displays', so the action is implied rather than 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 explicit guidance is given on when to use this tool versus siblings such as 'website_durchsuchen' or 'profil'. The intended usage is only implied by the content focus on publications and research.

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, and destructiveHint=false, so the safety profile is known. The description adds meaningful behavioral context: it searches all passages, returns the best-matching text sections along with section identifier, relevance score, and link. This goes beyond the annotations and clarifies the tool's output behavior without contradicting them.

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-loaded with the main purpose and output, followed by a clear usage guideline. Every word earns its place; there is no fluff or repetition of schema 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?

The description is complete for a search tool with two well-documented parameters. It explains the return format (section, hit value, link) despite no output schema, and provides usage guidance. The annotations cover safety and idempotency, so nothing essential 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 coverage is 100%, meaning both parameters ('frage' and 'treffer') are fully described in the schema. The description does not add additional parameter semantics beyond what the schema already provides, so the 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 clearly states the tool searches all passages of stalsoft.com for a question or keyword and returns the most relevant passages with section, hit value, and link. It also distinguishes itself from sibling tools by positioning itself as the first choice when uncertain which tool contains the answer.

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 gives usage context: 'Erste Wahl, wenn unklar ist, welches der übrigen Werkzeuge die Antwort enthält' (first choice when unclear which of the other tools contains the answer). This tells the agent when to use this tool and implies alternatives are the sibling tools, without needing to name them individually.

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