Search Australian businesses and look up ABN and GST records from the Australian Business Register.
Scored across 2 tools
The two tools target clearly distinct retrieval modes: exact ABN lookup versus business-name search. An agent can easily choose based on whether it has an identifier or a name.
Both names use consistent snake_case with the same 'abn_' prefix and descriptive action suffixes. The pattern is predictable and readable.
Two tools is minimal but well matched to this narrow domain, with no redundant operations. It is slightly thin compared with broader registries, but each tool clearly earns its place.
The core ABN workflows of lookup-by-number and search-by-name are covered. Minor gaps such as ABN validation or bulk lookup exist, but agents can work around them for typical use.
Look up detailed information for a specific Australian Business Number (ABN).
| Name | Required | Description | Default |
|---|---|---|---|
| abn | Yes | 11-digit ABN to look up | |
| includeHistorical | No | Include historical records |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. 'Look up' implies a read-only operation, but nothing is said about what 'detailed information' actually contains, whether historical data requires anything special, error behavior for an invalid or unknown ABN, or any auth/rate-limit constraints.
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 efficient sentence with the resource front-loaded and zero filler. It is arguably too terse rather than too long, but structurally clean.
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 two-parameter lookup with fully documented schema this is close to adequate, but with no annotations and no output schema, the description leaves the agent guessing about what 'detailed information' returns and what happens on lookup failure.
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% (both 'abn' and 'includeHistorical' are documented in-schema), so the baseline is 3. The description adds no meaning beyond the schema and says nothing about the includeHistorical flag or expected ABN formatting.
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 ('look up') and a specific resource ('Australian Business Number'), and the phrase 'specific ABN' implicitly signals this is a direct-identifier lookup rather than a name search. It does not name the sibling abn_search_by_name, so the 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 only implied: an agent can infer this is the tool to use when it already has an ABN, and the sibling name 'abn_search_by_name' hints at the alternative path. There is no explicit when-to-use/when-not statement or reference to the sibling tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search for Australian Business Numbers (ABN) by business name.
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | Search query string (business name) | |
| limit | No | Result limit (1-50) | |
| state | No | State filter (e.g., NSW, VIC, QLD) | |
| includeHistorical | No | Include historical records |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full behavioral burden and does essentially none of it — nothing about matching behavior (exact vs fuzzy), whether the upstream register is rate-limited or requires a key, or how results are ranked. The only behavioral signal, includeHistorical, is documented in the schema rather than the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with zero waste. The brevity edges into under-specification, which is penalized under contextual completeness rather than here, but it stops just short of a 5 because there is no second sentence of routing value.
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 annotations and no output schema, the description is the only place an agent can learn behavior, and it says nothing about what comes back (name, ABN, status, address) or how to handle zero/many matches. For a 4-parameter public-register search, a one-line description leaves material gaps.
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% — q, limit, state, and includeHistorical are all documented in the schema, so the baseline is 3. The description adds no guidance on query syntax (partial names, ABN prefixes, punctuation) or on how state and includeHistorical interact with the search.
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 (search) and resource (ABNs) with the key constraint that matching is by business name rather than by number. It does not, however, mention or distinguish itself from the sibling abn_lookup, so the agent must infer that lookup handles number-based 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?
Usage is only implied: because the query is a business name, an agent can infer this is the entry point when it doesn't already have an ABN. There is no explicit when-to-use, no statement of when to prefer abn_lookup, and no prerequisite or fallback guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
abn_lookupabn_search_by_nameValidate Australian ABNs and ACNs, and verify ABNs live against the Australian Business Register.
Australian company search by name, ABN, ACN, ABN status, state and postcode, with trading names.
Verify ANZ businesses against government registers. Surfaces cross-jurisdictional findings.
Australian identifier validation, GST arithmetic, fuzzy name matching, OFAC sanctions screening.
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