Firmenbuch

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

Annotations already cover readOnly/idempotent/non-destructive/closed-world. The description adds genuinely new behavior: Austria-only gating, the failure mode for German ids, the prefixed company_id in the response, and a recency caveat on peers. It does not discuss rate limits or pagination, but the added context is substantial.

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?

Front-loaded with purpose, then bulleted parameters, then return/alternative notes; every section earns its place. Slightly long for a two-parameter tool, but no filler sentences.

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 the description needn't detail return values, yet it still flags country, prefixed company_id, percentiles and the peer recency note. Combined with error behavior and the sibling alternative, an agent has everything needed 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 description coverage is 0%, so the description must carry the load, and it does: company_id format "AT:{fnr}" with bare FNR accepted and a country constraint, plus n's meaning as nearest-peer count with default 10. Both parameters are fully specified.

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 ("Benchmark ONE company against its size-class cohort") and enumerates the outputs (headline metrics, percentile ranks, nearest peers). The emphasis on "ONE" implicitly distinguishes it from the multi-company/peer-set 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?

Gives clear context: Austria only, requires parsed financials, German ids error out, and routes cross-border intent to find_peers with cross_border=true. It lacks an explicit when-not-to-use this for domestic list-building, but the alternative is named with its selecting condition.

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 description adds substantial behavioral context not available in the annotations: it explains id normalization from bare national ids to prefixed form, that unsupported filters are reported in a notice rather than silently dropped, and that the tool returns no company data. These are meaningful runtime behaviors beyond the readOnly and idempotent hints.

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 longer than typical but well organized with clear sections. It front-loads the core identity and read-only note, then elaborates on parameters and return structure. Slightly dense, but every major point earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with one optional parameter and an existing output schema, the description fully covers behavior, return shape, id normalization, filter handling, and guidance on when to call it. An agent has enough to invoke it correctly without further web searching.

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 must fully compensate. It does: it documents the country parameter's optionality, default value, allowed values ('AT' | 'DE' | 'all'), and exactly what each selection controls. This adds all meaning the bare schema lacks.

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 tool as a schema self-description resource and explicitly enumerates what it covers: unified id scheme, available filters, per-country capabilities, and per-country field catalogs. This is a specific verb-plus-resource statement that clearly distinguishes it from the data-returning sibling tools.

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 clear usage directive: call once up front when unsure which filter or tool to use, and explicitly notes that it returns no company data. However, it does not name specific alternative tools or spell out when to prefer them, so it falls short of a fully explicit routing recommendation.

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 declare readOnlyHint=true and destructiveHint=false, and the description enriches this by explaining the nuance: 'Read-only over company data; each call writes new short-lived export files (auto-deleted after ~1 day).' It also discloses download link expiry (~60 minutes), country-specific column differences (DE lacks financial columns to avoid falsely reading blanks as zero), and the notice behavior for unsupported filters. This is substantial behavioral context beyond the annotations, with no contradiction.

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 longer than average but well organized: a one-sentence purpose summary, a bulleted parameter list, then return format and behavioral caveats. Every sentence adds value, and the sibling distinction is placed at the end as a natural conclusion. Slightly verbose but justifiably so for a tool with nuanced export behavior.

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 purpose, parameters, return structure (per-country objects with download_url, rows, columns, notices), file format details (semicolon-separated, UTF-8 BOM, Excel-ready), deletion/expiry timelines, and country-specific column differences. Given the complexity of the underlying filters and the presence of an output schema, nothing critical is missing for an agent to select and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry the burden—and it does. Each parameter gets a meaningful explanation: filters are 'EXACTLY the same unified filters as search_companies,' sort applies 'where the country supports the field,' max_rows is a 'per-country row ceiling' with default/max stated, and country enumerates its allowed values. This goes well beyond the bare schema properties and defaults.

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: 'Export a matched company set as downloadable CSV files (lead lists).' The title also clarifies scope (AT + DE), and the description clearly differentiates from search_companies by adding 'For browsing/ranking on screen use search_companies instead.' This leaves no ambiguity about what the tool does or how it differs from its closest sibling.

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?

Provides explicit usage context: the tool is for obtaining downloadable CSV lead lists, while on-screen browsing/ranking is explicitly routed to search_companies. It also notes that filters and sort behave 'exactly the same' as search_companies, giving the agent clear conditions for reuse and the boundary between the two 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?

Beyond the read-only/idempotent/destructive annotations, the description richly explains behavioral semantics: empty peers_home indicates an unknown id or missing ranking data, peers_abroad is a meaning-based rather than financial match, and differing data depth between countries is acknowledged. This goes far beyond what annotations alone 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?

The description is well-structured: purpose and read-only status are front-loaded, then parameters, then return semantics, then routing to alternatives. Although detailed, every sentence adds necessary information rather than padding.

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 three parameters, 0% schema description coverage, and the tool's nuanced cross-border behavior, the description covers all needed information: input format, response envelope, empty-result meaning, and when another tool fits. The agent can make a correct invocation decision without further context.

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 parameter section carries full weight. It defines the company_id format with examples, notes that bare national ids are accepted, clarifies n is per country, and explains cross_border's effect on the response. This fully compensates for the schema's lack of parameter documentation.

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 operation and resource: finding companies most similar to a given one, with optional cross-border peers. It distinguishes itself from siblings by describing what it returns and explicitly pointing to search_companies as the strict-filter alternative.

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 explains when to enable cross_border, clarifies that peers_home uses each register's own peer logic, and routes non-peer use cases elsewhere: 'For a strict filtered list use search_companies; for aggregates use the country server's cohort tools.' This is explicit guidance an agent can act on.

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 safety (readOnly, idempotent, non-destructive, closed-world), so the description is not burdened with that. It adds genuine non-obvious behavior: 'gkl' excludes DE with a notice, and per-country payloads are reported side by side rather than force-merged because registers aggregate different metrics. It does not cover auth requirements or performance/rate characteristics, so not a full 5.

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?

Front-loads the one-line purpose plus read-only status, then a parameter block, then return/fan-out semantics. Because schema coverage is 0%, the parameter listing is necessary rather than redundant, and every sentence carries routing or behavioral 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?

For a 3-param aggregate tool with an output schema present, the description supplies everything needed: the parameter contract, the country/dimension interaction rules, the notice mechanism, and hand-offs to the two sibling tools. Return-value explanation is kept brief because the output schema covers structure.

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 full burden and does so: it documents all three parameters, marks required vs optional, gives the default for country, enumerates valid dimension values, supplies example values ('Wien', 'GmbH'), and discloses the 'size_gkl -> gkl' alias that appears nowhere in 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 with scope: aggregate statistics for a cohort of companies, broken down per country. It explicitly contrasts itself with get_company_details (single company) and search_companies (filtered list), so an agent can place it among siblings 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?

Names the two nearest alternatives and the exact condition that selects each: 'For one company use get_company_details; for a filtered list use search_companies.' It also explains when a dimension fans out to multiple countries versus when it is Austrian-only, which is precisely the routing decision an agent must make.

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/idempotent/non-destructive, so the description earns credit for what it adds: the not_found error shape for unknown ids and the critical warning that missing German figures may mean 'not processed yet' rather than zero, which prevents silent data misinterpretation.

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?

Front-loaded with the core purpose and well-organized under Parameters/Returns headings, but the long Returns paragraph partly restates what the output schema already covers. Efficient for its information density, though slightly heavier than necessary.

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 everything an agent needs for a 2-parameter detail fetch: id format, parameter edge cases, error behavior, and the reporting_status caveat about absent German financials. With an output schema present, the extra detail is complementary rather than 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 0%, so the description carries the full burden and does: it gives exact company_id formats with worked examples ('AT:123456a', 'DE:D2601_HRB135076'), accepts bare national ids, and defines max_signatories' default (15), the 0=all sentinel, and AT behavior.

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 ('Full profile for ONE company') and names the routing key (unified id). It also distinguishes itself from search_companies by noting the name-based alternative, so an agent can place it among siblings without opening schemas.

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 explicit when-to-use routing: use search_companies first when you only have a name, and take company_id from a search card's field. It also scopes max_signatories to DE only and notes it is ignored for AT, leaving nothing 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 cover the safety profile, but the description adds behavior beyond them: empty DE series means 'not-filed or not-yet-loaded, never zero', AT vs DE backend differences, and metrics being ignored for DE. These are non-obvious operational facts an agent could not infer from annotations or schema.

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?

Well front-loaded with purpose, then clearly sectioned Parameters and Returns blocks; every line is information-dense. Minor ding: the standalone 'Read-only.' sentence repeats readOnlyHint from annotations, adding no new 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?

For a backend-varying tool with 2 params, coverage is complete: id formats, metric filtering, payload shape (per-metric {year: value} plus country/prefixed id), and sibling routing are all present. The output schema exists, yet the description still adds the AT/DE interpretation nuance an agent needs.

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 carries the full burden and does: it defines the company_id formats ('AT:{fnr}', 'DE:{court}_{type}{number}', bare national ids accepted) and the metrics parameter (optional, AT-only, example metric names, omitted = all). This fully compensates for the empty 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+scope ('Per-year financial-metric history for ONE company'), and explicitly routes to siblings get_company_details (single snapshot) and get_full_record (complete record). An agent can distinguish it from every sibling without opening a 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?

Gives explicit routing rules: use get_company_details for a snapshot, get_full_record for the complete record. It also states a condition on a parameter ('metrics optional, AT only... Ignored for DE'), so both when-to-use and edge conditions are covered.

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 and idempotentHint, but the description adds valuable behavioral context: it explains countries_unavailable behavior, the backfill caveat for DE counts, and how not to interpret low counts. This clearly exceeds the annotation baseline and helps the agent avoid incorrect conclusions.

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 dense but well-structured: a one-line usage cue, a compact parameter section, and a return-shape explanation. Every sentence adds necessary information, and the critical 'call first' guidance 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?

The description covers the single optional parameter, the return structure, error handling for unreachable countries, and the meaning of incomplete data. Given the output schema and sibling context already provided, nothing necessary for safe and 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 0%, so the description is the only source of parameter meaning. It explains the country parameter is optional, defaults to "all", and defines the allowed values "AT", "DE", and "all". It also clarifies how the parameter affects the returned payload.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns dataset coverage and a capability matrix per country, which is a specific resource and purpose rather than a tautology. It also distinguishes itself from sibling tools by explicitly routing to describe_fields for filter values and search_companies for per-company data.

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 an explicit directive: 'CALL THIS FIRST before concluding that something does not exist in a country.' It also names alternatives and the conditions under which they should be used, making the selection decision clear.

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?

Adds substantial behavior beyond the annotations: ~10s cold latency then caching for AD/CD, JA served from the stored publication as HTML with no source PDF, the 'available=false + note' no-dead-link failure mode, short-lived link semantics, and an error on non-DE ids. These are exactly the traits annotations do not capture.

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 sentence, then tightly organized bullets for parameters and a compact run of return/behavior facts. Every sentence (Austria exclusion, latency, JA source format) 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?

Despite an output schema existing, the description adds the non-derivable parts: id syntax, kind semantics, latency/caching, availability flag meaning, and error conditions. Nothing an agent needs to call it correctly 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?

With 0% schema description coverage, the description fully carries the burden: company_id's exact format with a worked example and the bare-id fallback, and all three 'kind' values (AD/CD/JA) with expansions and behavioral consequences including the default.

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+scope: 'On-demand official register document for ONE German company', with 'Read-only' clarifying the operation class. It is clearly distinguishable from siblings such as get_company_details or export_companies_csv 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?

Gives concrete routing context: which 'kind' to pick and why, the limitation that Austria is not supported here, and that a non-DE id errors out. It never names a sibling as an alternative for the non-supported cases, so it stops short of explicit when-not/use-instead guidance.

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

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

Annotations already declare readOnlyHint/idempotentHint, so the 'Read-only' restatement earns no credit. However the description goes beyond them meaningfully: it discloses truncation behavior and the clamp range (1000-120000, default 40000) and notes the response carries the filing's Stichtag for citation. Return-shape specifics are largely left to the output schema.

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?

Front-loads the one-line purpose, then uses compact labeled parameter and return sections. Every sentence carries actionable information (scope, prerequisite, default, clamp range); 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 2-parameter read tool with an output schema already present, the description supplies everything an agent needs: jurisdictional scope, key discovery path, sibling disambiguation, truncation knobs, and citation context. 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 description coverage is 0%, so the description must carry the full burden and it does: doc_key is tied to its source field (document_ref from list_documents) and its Austrian-filing meaning, while max_chars gets default, optionality, and the enforced clamp bounds that appear nowhere in 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 (extract text) and resource (ONE Austrian filing document) scoped by document key, and explicitly distinguishes itself from the sibling get_document by jurisdiction (Germany abstract) and from list_documents (key discovery). An agent can route correctly 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?

Gives the prerequisite workflow ('Use list_documents to discover the key') and names the alternative tool with its selecting condition ('for the German official register abstract use get_document'). Also constrains applicability with 'Austria only today', so when-not-to-use is covered.

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?

Read-only is already covered by annotations, but the description adds important non-obvious behavior: default date window, availability differences by country, the 'never as zero' rule for DE, and the top-level return shape. It exceeds annotation coverage without contradicting it.

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 dense sentences, each adding value: the function's result, the parameter list, the availability caveat, and the sibling route. It is front-loaded with the primary purpose and avoids fluff.

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 read-only tool with an output schema, this description covers parameter selection, default behavior, availability limitations and where to go for individual events. Nothing about selecting or invoking the tool correctly seems 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?

The input schema has zero parameter descriptions, but the description compensates by listing all parameters, marking them optional, giving the last-30-day default, restricting nace_division and legal_form to AT, and enumerating country values. It falls slightly short only because it does not spell out the expected string format for dates or explain the NACE/bundesland concepts.

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 and resource: aggregate counts of register changes by type and region per country. It also distinguishes itself from list_events, which is for individual changes, so an agent can select it correctly.

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 explicitly routes the agent to list_events for individual changes and makes the current availability clear: only AT exposes event statistics, while DE reports 'not yet available' instead of zero. This gives both positive and negative usage guidance.

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

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

Annotations already declare readOnly, idempotent and non-destructive, so safety is covered. The description adds real value beyond them: relative cost ('heaviest read'), the Austria-only limitation with the German-id error behavior, and the unknown-code passthrough. It stops short of describing size/pagination of the payload, but that is a minor gap.

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?

Front-loads purpose, scope and the cost warning, then a labeled Parameters block. Slightly long with the code-formatting and lineage phrasing, but every sentence earns its place; 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?

An output schema exists, so return values need not be enumerated, yet the description still helpfully notes the payload includes 'country', the prefixed company_id, unknown-code passthrough and covered filing years. Nothing an agent needs to call this correctly 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 0%, so the description must carry the parameter — and it does, giving the id format 'AT:{fnr}', noting a bare FNR is accepted, and stating the Austria-only constraint. This fully compensates for the empty 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 and resource ('complete multi-year record for ONE company') with explicit scope ('every balance-sheet and P&L position's full per-year history'). It directly names the sibling it is not — get_company_details for a normal profile — so an agent can separate the heavy read from the light one.

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?

Explicitly routes the agent: 'The heaviest read - use get_company_details for a normal profile', plus the hard constraint that only Austria works today and a German id returns an error. When-to-use and when-not-to-use are both present.

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?

Beyond the existing readOnly/idempotent/destructive annotations, the description adds important behavioral context: it only returns the calling key's own usage, never another user's data, never the email behind the key, and it explains that a single meter spans AT and DE as the billing point. This provides meaningful transparency about limits and privacy.

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 well structured and front-loaded: it opens with a clear summary and then provides parameter details and return-scope specifics. It is slightly repetitive around 'own usage' and 'calling key's own usage,' but every section earns its place and nothing is irrelevant.

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 a single optional parameter, existing safety annotations, and an output schema present, the description is complete for making a correct call. It states the call filter, the result scope, the billing-meter behavior, and a practical use case, leaving no important operational 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?

The schema provides only the parameter name, type, and default, with no descriptions. The tool description compensates fully by documenting the optional window parameter, its default value of 'today', and every valid value: today, yesterday, month_to_date, last_30_days, and all.

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 precisely what the tool does: obtain the calling API key's own usage, including call count and weighted compute-units, per tool, and it clarifies the 'both registers' scope. It also distinguishes the tool from siblings by emphasizing 'your own' usage and explicitly excluding other users' data.

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 a concrete use case: 'Use it to check your consumption against the plan's rate limits.' It is clear about context but does not explicitly name alternatives or provide when-not-to-use guidance, which keeps it slightly below the top score.

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, idempotentHint, destructiveHint=false and openWorldHint=false, so safety is covered. The description still adds useful behavior beyond that: the list is metadata-only, sorted newest first, and the AT backend enriches output with ``country`` and a prefixed ``company_id``.

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 and read-only status are front-loaded in the first two lines, followed by a compact parameter note and a return summary. Every line adds information; there is no filler despite the multi-section layout.

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 single-param listing tool with an output schema present, the definition covers the id format, the geographic restriction, the alternative tool for DE ids, the ordering, and the downstream chaining. Nothing needed to call it correctly 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 0%, so the description carries the full burden, and it delivers: the required company_id accepts "AT:{fnr}" with bare FNR tolerated, and it warns that this is Austria-only. An agent can construct a valid id without guessing.

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 (chronology of a company's filing documents) plus ordering (newest first) and scope (metadata). It is clearly distinguishable from get_document (single document) and get_document_text (extracted text), which are named as the alternatives/follow-ups.

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?

Explicitly routes the agent: for Austrian filings use this tool with an "AT:{fnr}" id, while for the German official register abstract use get_document with a "DE:" id. It also tells the agent to feed a resulting document_ref to get_document_text, giving a clear when-to-use and how-to-chain picture.

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 provide readOnlyHint and idempotentHint, and the description substantially deepens behavioral context: it explains subset type skipping, per-country feeds, data availability windows so empty stretches are not misread, prefixed company_ids, and before/after values only for detailed AT types. 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 well-organized with a leading purpose sentence, a bulleted parameter list, and a compact return-value explanation. Every sentence or bullet adds essential operational detail without redundancy, making the length justified given the tool's API complexity.

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 output schema exists, the description still provides the important context that can't be inferred from schema: country-specific availability windows, AT/DE type distinctions, company_id constraints, and routing to sibling tools. It leaves the agent a fully operational understanding of when and how to invoke it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description compensates fully by documenting every parameter, including the full types superset enum, ISO date defaults, country-specific bounds for nace_division/legal_form, the company_ids AT/DE difference, and pagination defaults. It also states that all parameters are optional and AND-combined.

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 lists cross-company, cross-country register changes, newest first, and labels it as the market-watch/deal-sourcing surface. This goes beyond the title by specifying scope, sorting, and data source, and it is immediately distinguishable from sibling tools that retrieve company details or aggregate stats.

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 directs users to alternatives: 'For aggregate counts use get_event_stats; for one company's history use get_company_details.' It also explains parameter AND-combination semantics and country-specific type behavior, helping the agent decide when and how to call 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 cover read-only/idempotent/no-destruction, so the description's 'Read-only' is redundant. It does add real context the annotations cannot: data is served from the Austrian backend, the value lists and counts are Austrian-specific (with an in-response notice), while OENACE/WZ/NACE Rev.2 codes are country-identical. Missing only notes on response size/pagination.

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?

Front-loaded with purpose and the key scoping caveat, then a clean Parameters block. Most sentences earn their place, though the backend/NACE paragraph is slightly dense and could be tightened.

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 less exposition, yet the description still maps the 'matches' shape and the omitted-query case. Combined with the provenance caveat, an agent has everything needed to call it correctly and interpret results.

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 load. It documents the single optional parameter, gives example category words, and explains the two distinct return shapes depending on whether query is supplied — substantially more than the bare 'query: string|null' schema 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?

States a concrete verb and resource (list sectors and value lists for filtering) and explicitly contrasts itself with search_companies, which consumes the resolved nace_* filter. An agent can distinguish it from every sibling without opening a 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?

Gives explicit when-to-use guidance ('call it once up front to resolve a filter value') and a when-not signal ('It returns no company data'), plus the alternative that does the actual search. The optional-vs-omitted query behavior is spelled out.

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, idempotent, and non-destructive. The description adds transparency beyond annotations by explaining the optional 'cheap connection handshake' against every configured backend and how per-country reachability is reported, plus the high-level response shape.

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 structured and info-dense: a one-line purpose, a parameter breakdown, and a return summary. It loses a point for a little redundancy: 'confirms the server is up' and 'only says whether the server is up' say similar things.

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 liveness tool with one optional parameter, an output schema, and strong annotations, the description fully covers what the agent needs: purpose, parameter semantics, return contents, and how it differs from the relevant sibling. 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?

The schema has 0% description coverage, so the description carries the full parameter documentation burden. It fully explains check_backends: its default(false), optional nature, behavior when true, and the per-country reachability information it produces.

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 opens with 'Liveness probe' and says it 'confirms the unified register server is up,' giving a specific verb and resource. It also explicitly distinguishes itself from get_coverage by stating 'this tool only says whether the server is up,' which prevents confusion with a sibling.

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 names the alternative get_opcoverage for data completeness and clearly states the boundary of this tool. The optional check_backends parameter is also described with its effect, telling the agent when it is appropriate to invoke the deeper behavior.

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, non-destructive, so the description's extra value is in the operational caveats: a filter one country lacks excludes that country with a notice rather than failing, an unreachable backend lands in countries_unavailable, exact_count triggers a full scan, and keyset cursors are per-register (single country only). It also warns not to treat missing German financials as zero and points to the per-Bundesland rollout. Slightly dense but genuinely additive.

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 and the 'START HERE' cue are front-loaded, then parameters, then returns, then sibling routing — a sensible order. It is long and occasionally dense (the filters run-on lists many fields in one sentence), but nearly every clause carries information that the empty schema does not; the sizing is defensible.

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?

Complete for a high-complexity, zero-required-parameter fan-out search: country semantics, filter combinations, paging modes, cost of exact_count, response envelope shape (countries, total, results, per_country, notices), and caveats on partial German coverage are all present. It explains return fields despite an output schema existing, which in this case is helpful rather than redundant.

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 property coverage is 0%, so the description must carry the full burden and largely does: substring vs. meaning-based hybrid semantics for name/query, postal-code prefix conventions (AT 4-digit / DE 5-digit), NACE/OENACE/WZ equivalence across countries, company_ids prefix format and max 100, per-country valid sort fields with default fallback, and page/page_size/after/country/exact_count defaults. An agent can construct a correct call from the description 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?

States a specific verb and resource (find companies across the Austrian Firmenbuch and German Handelsregister) plus an explicit routing cue ('START HERE for any company lookup'). Clearly separable from siblings like get_company_details, export_companies_csv, and get_coverage.

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?

Names the alternatives and the condition that selects each: get_company_details for one company's full profile, export_companies_csv for a downloadable list, get_coverage for dataset completeness. It also tells the agent when to use keyset paging (bulk extraction) versus offset paging.

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?

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses return-envelope shape, per-country matching semantics (AT matches only the primary managing director; DE matches all MDs and signatories), and the critical caveat that name-based matching with only birth-year published does not prove a single person across companies/countries. This contextual warning directly prevents agents from drawing false conclusions.

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 core purpose is front-loaded and the parameter block is organized, with every sentence earning its place. Minor deducts: it repeats defaults already present in the schema as data, and the phrase '(the notice says so)' is a slightly noisy aside in an otherwise lean definition.

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 definition is complete for a 4-parameter search tool: it covers required input, output envelope and per-card fields, per-country behavioral differences, the identity-matching hazard, and sibling-tool routing. With an output schema present, nothing an agent needs to invoke this correctly 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 0%, so the description carries the full burden of param semantics. It covers every one of the 4 parameters with defaults, allowed values (AT/DE/all; active/inactive/all), format (substring, case-insensitive, e.g. 'Mustermann'), and behavior implications (page_size = results per country). It exceeds what the bare JSON schema 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 states a specific verb and resource: 'Find every company a person runs or represents - across BOTH registers in one call (cross-border person search)'. It names the sibling it is not ('For general company search use search_companies'), so an agent can distinguish it from search_companies without opening the 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?

The description explicitly routes to an alternative: 'For general company search use search_companies with other filters; manager_name can be combined there too.' It also clarifies when this tool applies (person-centric cross-register search) and sets expectations with the AT vs DE matching differences, leaving no ambiguity about tool selection.

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