Make your compliance report tamper-proof for Art. 12 audit trail — pass the report JSON, get back a proof_id and a public verification URL you can hand to auditors. Certified plan required. Run generate_report() first to produce the report.
| Name | Required | Description | Default |
|---|---|---|---|
| report_data | Yes | JSON string of the compliance report to certify. | |
| trust_layer_key | Yes | ArkForge Trust Layer API key. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It explains the transformation (tamper-proofing), the output (proof_id, URL), and prerequisites (generate_report, certified plan). It does not cover rate limits or side effects, but for a certification action this is reasonable and informative.
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 two sentences with no redundant words. The main purpose and key outputs are front-loaded, and the prerequisites are in the second sentence. Every piece contributes to understanding.
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 explains the return values (proof_id, verification URL) and the audit context (Art. 12, auditors), which compensates for the absence of an output schema. It also gives a prerequisite and a required plan. Minor gaps like error handling or key input are not significant given the simple parameter set.
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 already describes both parameters fully (report_data as JSON string, trust_layer_key as API key). The description reinforces 'pass the report JSON' but adds no new parameter semantics beyond what the schema provides, so the baseline score of 3 is appropriate.
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 starts with a specific verb phrase 'Make your compliance report tamper-proof' and identifies the resource (compliance report) and the outcome (proof_id and public verification URL). It clearly distinguishes this certification tool from sibling tools like generate_report and check_compliance.
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 provides a clear prerequisite: 'Run generate_report() first to produce the report' and notes 'Certified plan required.' This gives strong guidance on when to use the tool, though it does not explicitly state when not to use it or name alternative tools.
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.
Multiple tools overlap in scope: scan_project, gdpr_scan_project, and combined_compliance_report all perform scanning, while check_compliance, gdpr_check_compliance, and combined_compliance_report all return pass/fail results. The combined tool explicitly replaces the individual scanners, yet they remain available, creating confusion about which to call.
Naming conventions are inconsistent: EU AI Act tools use verb-first patterns (generate_report, scan_project), while GDPR tools prefix the law (gdpr_generate_report, gdpr_scan_project). 'combined_compliance_report' breaks the verb_noun pattern entirely, and the placement of 'gdpr' varies inconsistently across tools.
16 tools is on the heavier side for this domain, but the dual EU AI Act + GDPR scope partially justifies the count. However, several tools are redundant (e.g., scan_project vs. combined_compliance_report), inflating the total without adding unique functionality.
The tool set covers the compliance lifecycle well: scanning, gap analysis, reporting, templates, roadmap generation, certification, and risk classification. Minor gaps exist (e.g., no tool to manage specific remediation status), but the core workflows are fully supported.
