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

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 operation is known to be safe and repeatable. The description adds the filtering-vs-full-fetch behavior and example topics, but does not state matching semantics or result shape; the added behavioral context is modest.

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 short sentence with inline examples; no redundant content, and the core retrieval modes are stated immediately.

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 simple one-parameter, read-only, idempotent nature of the tool, the description, schema, and annotations cover what is needed to call it correctly. The only minor omission is explicit routing guidance relative to sibling search/content tools.

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 documents frage as 'Suchbegriff oder Frage; leer für alle Einträge', and schema coverage is 100%. The description reinforces this and adds concrete example search terms, which slightly increases semantic clarity for an agent choosing a query.

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 identifies the resource (the website's FAQ questions and answers) and the two retrieval modes: full list or filtered by search term. It is clear, but it is a noun phrase with no explicit verb and does not explicitly contrast with sibling tools such as website_durchsuchen.

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 concrete invocation context: pass a search term such as GEO, Barrierefreiheit, or E-Commerce, or leave the parameter empty to retrieve everything. It does not say when to prefer this tool over website_durchsuchen or inhalt_abrufen, but the FAQ-specific scope makes the intended use reasonably 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?

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?

The annotations already indicate a read-only, idempotent, non-destructive call. The description adds meaningful behavioral context by stating that the contacting user writes the message themselves and the interface does not take personal data, which clarifies that this is not a message-submission tool. No annotation contradiction exists.

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 carry the full semantics: the first front-loads the purpose and deliverables, the second clarifies the interaction model. Every phrase contributes; there is no redundancy or 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 lookup tool with one optional parameter and no output schema, the description gives enough for an agent to select and invoke it correctly: the return content (email, form link, location, languages), the use of the subject-line keyword, and the non-collection of personal data.

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 description covers 100% of the params, so the baseline applies. The description's mention of a 'vorbereitete Betreffzeile' aligns with the schema's explanation of 'thema', but does not add new parameter-level meaning 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 defines what the tool is for: providing the contact routes for a substantive inquiry — email with a prepared subject line, a link to the website's contact form, and location/language information. It is distinct from the sibling FAQ and search tools, though it is not framed as an explicit verb-plus-resource action.

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 phrase 'für eine fachliche Rückfrage' gives a clear context for when to use the tool: when someone wants to contact the organization with a domain-specific question. However, it does not mention sibling alternatives such as 'faq' or 'website_durchsuchen', nor does it say explicitly when not to use it.

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 fully covered. The description adds the filtering behavior (optional narrowing to one Bereich), which is useful operational context. No contradiction with annotations, but no additional behavioral detail like return format or output structure is disclosed.

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 that names the core deliverable first, then lists the six areas, then states the filter option. The list of six focus areas adds length but each item is meaningful content an agent may need. There is no filler or redundant phrasing relative to the title.

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 content tool with one optional, fully documented parameter and no output schema, the description is nearly complete: it enumerates all six areas and explains the optional scope filter. It could arguably state the return format, but that is not essential for an agent to successfully invoke this list 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?

Schema description coverage is 100% — the 'bereich' parameter is thoroughly documented in the schema with examples ('KI', 'Cloud', 'GEO') and the empty-for-all default. The description only reinforces the filtering concept ('Optional auf einen Bereich eingegrenzt') without adding meaning beyond the schema. Baseline 3 is appropriate given the 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 resource: the six professional focus areas (IT-Strategie, KI/ML, Datenanalyse, Cloud/DevOps, Software-Architektur, SEO/GEO/Barrierefreiheit), which is distinct from siblings like faq, publikationen, profil and kontakt. The verb (list/retrieve/return) is only implied rather than explicit, but the content is unambiguous and the tool's scope is fully differentiated from its 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?

The use case is strongly implied by content — an agent can infer this tool answers questions about the person's professional focus areas. However, no explicit when-to-use guidance or naming of alternative tools (e.g., when to prefer profil or publktionen) is provided. For a simple content-listing tool the implied guidance is acceptable but minimal.

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.