From atp
Evaluate legal and regulatory compliance under Vietnamese law. Produces cited legal analysis with verbatim Vietnamese legal text, obligation mapping, and compliance status.
How this skill is triggered — by the user, by Claude, or both
Slash command
/atp:evaluate-legalThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
You are orchestrating a legal compliance evaluation. Your job is to gather context and evidence, then produce a cited legal analysis grounded in Vietnamese law that the user can act on and verify.
You are orchestrating a legal compliance evaluation. Your job is to gather context and evidence, then produce a cited legal analysis grounded in Vietnamese law that the user can act on and verify.
You will be provided with:
This skill evaluates legal and regulatory compliance for activities subject to Vietnamese law — exchanges, asset issuance, remittance, trading, custody, and related operations. It returns cited analysis with verbatim Vietnamese legal text (nguyên văn), obligation mapping, and compliance status.
See references/report-architecture.md for report rendering guidance.
$ARGUMENTS
Do not retry, abort, or report failure for ATP tool calls until you receive a final response or an explicit error. Tool calls may take up to 10 minutes — the skill pipeline runs multiple AI agents sequentially. If you see a timeout warning, ignore it and wait for the result.
Execute the following eight tasks sequentially.
Task 1 — Create context questions: Call the gather_context tool with factual, correct, and detailed information from <goal>. Stop and wait for the tool to return its output that includes context questions for the user to answer. Don't proceed to task 2 until the tool has returned output.
Task 2 — Gather context: Present the context questions gathered in task 1 to the user. Stop and wait for their responses.
Task 3 — Gather evidence: Call the gather_evidence tool with: (1) factual, correct, and detailed information from <goal>; (2) and the users' answers to the questions in task 2. The tool returns an evidence summary with an evidence_id. Save this ID — you will pass it to the evaluation tool. Proceed to task 4.
Task 4 — Enrich with web search: Use web search to supplement both context and evidence gathered in task 2 and 3. Once the web search process returns output, proceed to task 5.
Task 5 — Evaluate Legal: Call the evaluate_legal tool with:
user_query: concise — e.g. "USDT remittance corridor legal compliance under Vietnamese law"evidence_id: the evidence ID string from task 3evidence: structured dict containing gather_context_result (user answers from task 2). The server resolves the full evidence internally using evidence_id.evaluation_id and the full legal report — cited Vietnamese legal findings with verbatim text, applicable laws, obligations, restrictions, and penalties. Retain the returned blob for task 8. Pass only the evaluation_id to task 6. Proceed to task 6.Task 6 — Simulate: Call the simulate tool with:
user_query: same as task 5evaluation_id: the evaluation_id from task 5. The server also injects the legal findings from task 5 automatically — do not pass legal_output.Task 7 — Present simulation results: Summarize the simulation findings for the user. Highlight any scenarios that failed or produced unexpected outcomes — these indicate compliance gaps or regulatory risks. Proceed to task 8.
Task 8 — Craft reports: Produce a markdown report and a self-contained HTML report for the user, grounded in the full blobs returned by task 5 (legal) and task 6 (simulation). Three references govern the work:
<!-- TITLE -->, <!-- SIDEBAR_NAV -->, <!-- CONTENT_SECTIONS -->, <!-- MARKDOWN_CONTENT -->, <!-- JSON_CONTENT -->.Sections to emit:
<div class="card always-open"> framing the entire legal analysis: entity type, applicable legal status (e.g., "Virtual Asset Service Provider — pilot under NQ 05/2025"), jurisdiction, classification caveats or regulator positions. Ambiguities in classification get a badge-medium amber pill.nguyên văn — never paraphrase), status (badge-low MET / badge-critical UNMET / badge-medium AMBIGUOUS / badge-governance N/A), gap risk (badge-critical / badge-high / badge-medium / badge-low). This is the defensibility claim — every row must carry a verbatim citation.<div class="card"> per regulatory ambiguity. Each card: the ambiguous area, why it is ambiguous (no statute / conflicting interpretations / absent jurisprudence), what the skill concluded and on what basis (e.g., applying BLDS agency principles to software agents lacking explicit regulation). Collapsed if empty, visible if populated. This is where the skill's lateral-bridging value becomes visible.verbatim_text, cite the law reference from applicable_laws in <strong> (e.g., "NQ 05/2025, Điều 7", "BLDS 2015, Điều 584"), and include obligations, restrictions, penalties, and identified gaps. Follow the Legal Analysis pattern in report-format.md.report-format.md — regulatory_gap gets amber + gap framing, not red + failure framing. Failed scenarios should link by id to the related obligation in the Obligations table.badge-p0 (required before activity proceeds — e.g., obtain licence, file notification) / badge-p1 (during operation — periodic reporting, record retention) / badge-p2 (escalate to counsel). Each recommendation must cite the obligation or ambiguity that motivates it.Diagrams to emit:
sequenceDiagram showing the primary regulated workflow end-to-end across actors with governance touchpoints marked on each step.stateDiagram-v2 for any obligation with a lifecycle (AML reporting state, licence lifecycle, record retention window).Assemble and sanitise: Bundle the source markdown inside the HTML via the <script id="report-markdown" type="text/markdown"> block in the skeleton so the "Download Markdown" button works. Do not re-expose any internal tool names, IDs, or agent names in either the markdown or the HTML — strip them per the safety section of report-format.md.
This completes the skill.
npx claudepluginhub s27183/adi-atp-plugin --plugin atpProvides CDSS development patterns for drug interaction checking, dose validation, clinical scoring (NEWS2, qSOFA), and alert classification integrated into EMR workflows.