Get user feedback for QA review. Requires admin API key.
Filters: status (new/reviewed/resolved/dismissed), feedback_type (data_quality/bug/feature_request/other),
context_type (document/obligation/general).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| status | No | ||
| context_type | No | ||
| feedback_type | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, and the description adds the admin API key requirement, a valuable behavioral disclosure. 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 compact: a clear purpose sentence, an auth requirement, and a well-structured filter list. Every sentence provides necessary information without redundancy.
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 and annotations cover safety, the description adequately covers purpose, auth, and filter options. This is sufficient for a simple filtered-list tool.
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 schema description coverage at 0%, the description compensates by enumerating valid values for status, feedback_type, and context_type. It omits any explanation of the limit parameter, but the name and default value make it self-explanatory.
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?
Clearly states the tool retrieves user feedback for QA review, using a specific verb and resource. Distinguishes itself from sibling tools that fetch obligations, documents, or 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?
Provides clear context (QA review) and a prerequisite (admin API key). However, it does not explicitly mention alternatives or when not to use the tool, so it stops short of full usage guidance.
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.
Each tool targets a distinct resource (obligations, documents, enforcement, Finnish statutes, CJEU cases) with clear parameter differences. Minor overlap exists between get_obligations and get_canonical_obligations, but descriptions explicitly differentiate them.
All tools consistently use verb_noun patterns: get_ for retrievals, search_ for queries, list_documents, and audit_taxonomy. No mixed casing or inconsistent verb styles are present.
At 26 tools, the surface exceeds the 25-tool threshold for 'too many'. While the domain is broad, the large number of specialized search/get tools could be consolidated without losing functionality.
The API covers the full regulatory compliance workflow: company profile, obligations, deadlines, documents, enforcement, and multiple legal sources (EU, Finnish, CJEU). Some Finnish/KHO tools return URLs requiring web fetch rather than direct data, which is a minor but by-design gap.