Skip to main content
Glama

CivicDataForge Public-Records Data

by io.github.equinoxaifinance-rgb

Norway Company & Supplier Evidence

civicdataforge--norway-company-evidence

Use for exact nine-digit Norwegian organisation-number evidence or bounded company-name research from Brønnøysundregistrene. NLOD 2.0 permits commercial reuse with attribution and change disclosure, but buyer-specific privacy and lawful-basis review may still be required for personal-data-bearing records; this Actor omits roles, contacts, and street address lines and never issues a KYC, procurement, sanctions, or eligibility verdict. Starts the bound Apify Actor with the caller's APIFY_TOKEN, may consume Apify usage, waits up to 60 seconds, and returns at most 1,000 source-linked rows without modifying government records.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queriesYesOne to 25 evidence queries. Prefer the exact nine-digit organisation number. A supplied name alongside an organisation number is returned as a consistency check, never as a replacement identifier.
maxRecordsNoName searches request one additional record internally so truncation is detected and disclosed.
batchReferenceNoOptional non-sensitive batch reference bound into the shared batch receipt.

TDQS

A4.3/5.0
Behavior5/5

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

The description goes well beyond the annotations by disclosing that the tool starts an Apify Actor, consumes the caller's APIFY_TOKEN, may incur usage, waits up to 60 seconds, returns at most 1,000 rows, omits certain personal-data fields, and does not modify government records. This gives the agent a clear picture of external side effects and limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense and information-rich, with the primary use case front-loaded and operational constraints, legal context, and exclusions following. No sentence is wasted, though the second sentence is long and could be split for easier scanning.

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

Completeness4/5

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

The description covers usage scope, data-source provenance, licensing, privacy caveats, returned-row limits, field omissions, verdict exclusions, timeout behavior, cost implications, and non-modification of government records. It does not detail the exact output row structure, but the absence of an output schema is partially mitigated by the mention of 'source-linked rows' and omitted fields.

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

Parameters3/5

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

The input schema has 100% description coverage, so the baseline is 3. The description reinforces the importance of the nine-digit organisation number and bounded name search, but it does not add materially new parameter-level details beyond the schema's own thorough descriptions.

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

Purpose5/5

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

The description opens with a specific use case—'exact nine-digit Norwegian organisation-number evidence or bounded company-name research'—and names the authoritative source, Brønnøysundregistrene. This clearly distinguishes the tool from sibling tools focused on other registries and from generic Apify control tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use the tool and defines its limits: it is for organisation-number evidence or bounded company-name research, and it 'never issues a KYC, procurement, sanctions, or eligibility verdict.' It does not explicitly name an alternative tool, but the boundary conditions are strong and practical.

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

All CivicDataForge Public-Records Data toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0
Disambiguation4/5

The domain-specific tools are clearly separated by record type, with explicit cross-references that reduce confusion between similar categories like Texas vs. multistate childcare or STR permits vs. Florida DBPR lodging. The main ambiguity is the broad evidence-gateway tool, which overlaps with several specialized query tools and could be selected instead of the more precise one.

Naming Consistency4/5

The domain tools follow a consistent civicdataforge-- prefix pattern, and the Apify utilities follow a get-/abort- verb pattern, making the overall set readable. Minor deviations include the awkward civicdataforge--civicdataforge-evidence-gateway duplication and the mix between noun-style domain tools and verb-style utility tools.

Tool Count5/5

With 14 tools, the set is well-scoped: ten specialized public-record query tools plus four Apify lifecycle/data-access utilities. Each tool has a distinct role, and the count is appropriate for the breadth of supported public records without feeling bloated.

Completeness4/5

The tool surface covers a broad range of public-record evidence categories and provides the necessary run, dataset, and key-value-store operations for working with results. Minor gaps include a lack of discovery tools for listing supported jurisdictions/sources and no general-purpose search across all record types, but the core evidence workflows are well covered.

Resources