Helfer & Profi

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

Annotations only declare readOnly/openWorld/destructive flags, so the description adds real value: it discloses that user data (name, contact, location, message) is forwarded to the provider, that the provider replies directly to the user, and that internet links are disallowed. It stops short of describing confirmation, failure modes, or rate limits.

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?

Four short, front-loaded sentences with no filler; the consent requirement and data-transmission semantics come first. Slightly terse on downstream behavior, but nothing is wasted.

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 7-parameter mutation tool with no output schema, the description covers the consent prerequisite, the transmitted payload, and a content restriction. It could say more about confirmation or post-send behavior, but an agent has enough to call 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?

Schema coverage is already high (86%), yet the description still adds meaning by mapping which fields are transmitted ('Name, Kontakt, Ort und Nachricht') and reinforcing the consent gate that the consent parameter encodes. The optional text_only parameter is left to 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 states a specific verb+resource ('Einen Anbieter ... anfragen') and its scope, plus where the provider_id comes from ('aus search_providers'). This lets an agent distinguish it from search_providers, register_provider, and provider_reviews without opening any schema.

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 gives an explicit precondition ('Nur nach Zustimmung des Nutzers') and implies the workflow of first searching via search_providers. It does not, however, state when-not to use it or name explicit alternatives beyond the ID source.

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=false and destructiveHint=false, so the write nature is covered; the description adds genuine behavioral context beyond that: the listing appears immediately or after review depending on settings, email contacts receive automatic offers, and phone-only contacts get a call from the operator. This is meaningful workflow disclosure a bare mutation flag would not convey.

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?

Four short sentences, front-loaded with the core action before the confirmation precondition and behavioral consequences. No filler, though the email/phone clause compounds two ideas in one sentence.

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 an 8-parameter creation tool with no output schema, the description adequately covers the mutation outcome and consent gate but leaves several optional parameters unexplained. The safe-write profile is carried by annotations, so the remaining gap is moderate rather than severe.

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 75%, so most parameters are already documented. The description explains the contact email/phone consequence but largely restates what the contact schema field says, and says nothing about budget_eur, house_call, text_only, or display_name, so it adds only marginal value over 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?

States a specific verb+resource combination ('Gesuch für den Nutzer aufgeben'), making the create action distinct from read-oriented siblings like get_job and search_jobs. It does not, however, explicitly name or contrast itself with any sibling, so an agent must infer the boundary.

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 provides a real precondition – 'Nur nach Bestätigung durch den Nutzer' – which tells the agent not to call this without explicit user consent. But it never states when to prefer this over alternatives such as submit_offer or contact_provider, leaving usage routing implied.

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 readOnly/no-destructive, so safety is covered. The description adds real behavioral context beyond them: contact data is stripped, and an empty list is returned when the posting is no longer visible — a non-obvious outcome for what reads like a single-item fetch.

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 short clauses, both load-bearing: what is returned and the edge-case return value. Nothing redundant and the key fact is front-loaded.

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?

With no output schema and no annotations covering return shape, the description does the necessary work by describing the payload (no contact data) and the empty-list edge case. Only the job_id semantics remain thinly covered.

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%, so the description carries the burden for job_id. The link example '…/#gesuch=12' weakly implies the id format, but it never explicitly maps job_id to that fragment value or states its type, leaving the sole parameter only partially explained.

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 (retrieve) and resource (a single visible job posting), and the scope marker 'einzelnes' implicitly contrasts with the sibling search_jobs. The parenthetical clarifies what is excluded (contact data), but it never names the sibling it differs from.

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 gives a concrete triggering context (a shared link like …/#gesuch=12), which is useful implied guidance, but there is no explicit when-not or pointer to search_jobs for the more general lookup case.

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, non-destructive and closed-world, so safety is covered. The description adds the important scope constraint that only reviews from brokered customers are returned, which the agent could not derive from annotations. It does not mention pagination despite max_results.

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 short sentence with no filler, front-loading the resource. It is concise but perhaps too short for a 2-parameter tool with no documented schema.

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?

No output schema exists, so the description should at least say what a review contains or how results are ordered/limited. With 0% parameter coverage and no output schema, the definition leaves the agent under-informed about both inputs and returns.

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 description must carry the parameter load, but it says nothing about provider_id or max_results, including the 1-200 cap on results. The agent gets no guidance on what provider_id refers to or how max_results affects the response.

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 resource (published reviews of a provider) and clarifies scope (only from brokered customers). It does not explicitly distinguish itself from the sibling submit_review, which is the write counterpart, but the verb 'Bewertungen veröffentlicht' implies retrieval.

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 no when-to-use guidance, no exclusions, and never mentions submit_review as the alternative for submitting a review. The agent must infer that this is the read-side of the review flow from the 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?

Annotations only tell us this is a non-read-only, non-destructive, non-open-world write. The description adds real behavioral context the annotations cannot convey: the entry only appears after operator review, and name/location/services become publicly visible. It stops short of describing what happens on rejection or whether re-submission is possible.

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 compact sentences, front-loaded with the action and eligibility, followed by the review/publishing behavior and the data-placement warning. No filler, though the dash-clause about public fields is dense and slightly compressed.

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?

With six required parameters, no output schema, and a moderation step, the description covers the essentials: eligibility, review-gated visibility, and where contact data belongs. It does not state what the call returns or how the pending state is represented, which is the remaining gap.

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 already 100%, so the baseline is 3. The description earns above baseline by explaining a semantic constraint the schema does not encode: which fields become public and that phone, e-mail, street address and links must not be placed in name/location/services, only in contact.

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 ('Anmeldung als Anbieter') plus an eligibility constraint (nur Volljährige), so an agent immediately knows this creates a provider registration. It does not, however, name or contrast itself with siblings such as contact_provider or submit_offer, so differentiation is left to inference.

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 when someone wants to sign up as a service provider and is an adult. There is no explicit guidance on what to do for an already-registered provider, nor any named alternative tool for contacting or updating a provider, which leaves the routing decision partly to inference.

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 safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=false), so the bar is lower. The description adds the DSA legal framing, which is useful context, but says nothing about what happens after submission (receipt, ticket, anonymity via optional contact) or any rate limits.

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 compact sentence with the core action front-loaded and the legal citation and valid target values attached in one clause. No padding, though it is so terse that it omits information an agent would want.

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 4-parameter mutation tool with no output schema, the definition covers the essential what but not the outcome of a report or the meaning of target_id. Annotations cover the safety profile, so the gap is moderate rather than severe.

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 50%: reason and contact are documented in-schema, and the description re-lists the target_type enum values, partly duplicating structured data. The undescribed target_id is not clarified anywhere, so the description only partially compensates 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 (report illegal content) and cites the legal basis (Art. 16 DSA) while enumerating the three reportable target types, which is genuinely more specific than a bare 'report content'. However, it does not explicitly differentiate itself from siblings like submit_review or contact_provider, leaving the agent to infer the distinction.

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 'illegal content under Art. 16 DSA', which frames this as a regulatory report rather than a generic flag. There is no explicit when-to-use/when-not guidance, no mention of prerequisites (authentication, eligibility) or alternatives to consider before reporting.

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 cover the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=false), so the bar is lower. The description still adds real behavioral substance: results exclude contact data, and a radius query augments results with distance_km and sorts by distance. It omits pagination/truncation behaviour and what max_results defaults to.

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?

Purpose is front-loaded in the first clause, followed by tightly packed parameter rules with no filler sentences. The telegraphic style is efficient, though the compressed notation ('location = 5-stellige PLZ und radius_km') costs a little readability.

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 read-only search with no output schema, the description usefully discloses what is filtered out (contact data) and what is added on radius queries. Remaining gaps are minor: no default for max_results and no hint about result volume or pagination, which an agent calling an unpaginated search would benefit from knowing.

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 75% schema coverage the baseline is 3, but the description contributes beyond the schema by stating the coupling rule (radius_km only works when location is a 5-digit PLZ) and the resulting output change. It adds nothing for max_results, the one undocumented parameter.

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 gives a specific verb+resource ('Offene Gesuche suchen') and a scoping trait ('ohne Kontaktdaten') that separates it from search_providers. It never names a sibling tool explicitly, so the routing is inferred from semantics rather than stated, which keeps it below a 5.

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 context for the search itself is only implied; the only genuine guidance is parameter-level (when 'location' is a numeric prefix vs. a place name, and that radius search requires a full 5-digit PLZ). There is no statement of when to prefer this tool over search_providers or 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 state readOnlyHint/openWorldHint=false, so safety is covered. The description adds non-obvious behavior: only activated providers are returned, average rating is included, and radius mode switches output to include distance_km sorted ascending. No permission or pagination notes, but the added context is substantive.

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 tight sentences with no filler; the result scope comes first, then the two query modes in priority order. Every clause carries information an agent needs.

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?

With no output schema, the description carries the return shape (rating, distance_km, distance sort order) well. The only omission is max_results behavior, which is minor but leaves one parameter wholly undocumented.

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 explains how near and radius_km interact and that results then carry distance_km sorted by distance, which is real semantic value. But max_results (one of four params) is undocumented in both the schema and the description, leaving a gap at 75% 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?

Names the resource precisely and adds a scope qualifier: only activated providers, returned with an average rating. No explicit verb ('search/list') and no differentiation from siblings such as provider_reviews or search_jobs, so an agent must infer the operation from the tool name.

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?

Explains the two operating modes (keyword/PLZ-prefix via q, vs. radius search via near + radius_km), which is useful invocation context. However it never states when to pick this tool over siblings or any prerequisites/limits beyond the radius bounds.

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 only declare it is a non-destructive write; the description adds real behavioral context beyond that: the offer is delivered to the client by email, with fallback delivery via the operator, and links are forbidden in the content. It still omits what happens on failure or whether an offer can be withdrawn, but the delivery path and content constraint are valuable disclosures.

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, front-loaded sentences with no filler; the core action leads and constraints follow. Slightly dense but every clause carries 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?

Covers the consent gate, delivery mechanism and content restriction, which is solid for a mutation tool. With no output schema, however, it says nothing about the result of submission (success confirmation, rejection, duplicate offers) and leaves job_id semantics unaddressed.

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 71% and already documents name, contact, message, text_only and consent, including the consent/privacy condition. The description reinforces that contact and price go to the client but adds little beyond the schema, and says nothing about job_id or the price_eur bounds.

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+resource: submitting an offer (Angebot) to a job posting (Gesuch), and enumerates the payload (name, contact, price, message). It is distinguishable from create_job and submit_review by resource, though it never explicitly contrasts itself with the sibling contact_provider, which is the closest alternative 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?

Gives one hard prerequisite — the offer may only be sent after the user's consent — which is genuinely actionable. However, it offers no guidance on when to prefer this over contact_provider or how it relates to the job lifecycle (e.g. must the job still be open), leaving selection between siblings to inference.

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 this is a non-destructive write in a closed world, so the safety profile is covered. Beyond that, the description adds genuinely useful behavior: the code is single-use ('einmalig') and originates from a completed placement, which the agent needs in order to set expectations. It still says nothing about moderation, publication timing, or what happens with an already-consumed code.

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 no filler, and the critical prerequisite (the code) is stated immediately. It is arguably too terse for a review-submission tool, but nothing is wasted.

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?

With 5 parameters, 3 required, and no output schema, the description covers the gating prerequisite but omits the outcome: whether the review is published immediately, moderated, or tied to the consent flag. An agent can call the tool correctly, but cannot set the user's expectations about what happens next.

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 80%, so the schema already documents most parameters; the baseline is 3. The description adds the code format (XXXX-XXXX) beyond the schema's generic 'Bewertungscode', but stays silent on stars, comment, consent, and reviewer_name, so the added value is limited.

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 action (submitting a review) and names the required artifact (the one-time review code in XXXX-XXXX format), so the agent understands what the tool consumes. It does not, however, differentiate itself from the sibling provider_reviews, which also concerns reviews.

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 rather than stated: the code is described as one the customer received after a placement ('nach einer Vermittlung'), which tells the agent this is a post-transaction, customer-facing action. There is no explicit when-to-use vs. alternative guidance, e.g. how this relates to provider_reviews or what to do if the customer has no code.

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