Look up a specific Norwegian business by organization number (9 digits) and get its commitment profile. Returns temporal, financial, and operational commitment signals from Brønnøysund Register Centre.
| Name | Required | Description | Default |
|---|---|---|---|
| orgNumber | Yes | Norwegian organization number (9 digits, e.g. '984388659') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It discloses the data source (Brønnøysund Register Centre) and the nature of returned data (temporal, financial, and operational commitment signals). While it doesn't explicitly state side effects or limitations, a lookup operation is inherently read-only, and the description offers useful context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the action and key parameters, and every phrase is informative. No unnecessary repetition or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter lookup tool with no output schema, the description covers what it does, what it returns, and the data source. It could mention error cases or when not to use it, but overall it is adequately complete for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully documents the orgNumber parameter including format and example. The description reiterates the 9-digit format and adds Norwegian business context, but doesn't provide new semantic details beyond the schema, so it meets the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('look up') and resource ('Norwegian business by organization number (9 digits)') and adds the distinct output ('commitment profile') from the Brønnøysund Register Centre. This clearly distinguishes it from siblings like lookup_business and query_commitment.
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 clearly states the use case: looking up a specific Norwegian business using its org number. It implicitly signals that this is for Norwegian entities only, unlike broader tools like lookup_business, but it doesn't explicitly mention alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are clearly distinct by ecosystem and action, but the pair audit_github_repo and lookup_github_repo could be confused since both operate on GitHub repos (one audits dependencies, the other profiles the repo itself). The descriptions help, but the naming is similar enough to cause occasional misselection.
All tools follow a consistent verb_noun pattern: 'audit_' for dependency auditing, 'lookup_' for single-entity profiles, plus 'get_api_key' and 'query_commitment'. The 'lookup_business_by_org' variant is a clear sub-pattern, not a deviation.
12 tools is well-scoped for a multi-ecosystem supply chain risk scoring server. Each tool covers a distinct ecosystem or operational function (auditing, lookup, API key management, domain commitment), and none feel redundant.
Coverage is strong: flat audits for npm/PyPI/Cargo/Go, npm dependency tree traversal, GitHub repo audits, and single-package lookups across all major ecosystems. Minor gaps include no explicit tool for managing the monitoring/alerts feature mentioned in get_api_key, and no dependency tree traversal for non-npm ecosystems, but these are acceptable workarounds.