Install
openclaw skills install @dshcorrectover/ccs-receipt-batch-auditBatch Ed25519 signature verification for up to 200 AI-agent audit receipts, fully offline. Every receipt is checked against one issuer public key with Ed25519 verification plus RFC 8785 JCS/SHA-256 integrity checks; outputs aggregate valid/invalid statistics, pass rate, tampered-index list with per-receipt failure reasons, and optional hash-chain linkage, using the vendored open-source CCS verification core. Zero network calls. Use when batch-verifying CCS receipts, auditing a batch of signed agent decision receipts, or verifying a receipt chain.
openclaw skills install @dshcorrectover/ccs-receipt-batch-auditWhen you hold an entire batch of CCS AI-agent audit receipts — pipeline outputs, log archives, evidence sets handed across systems — and need to know in one shot which are authentic and which were tampered with or carry invalid signatures, use this skill. Verification runs locally by default (vendored open-source CCS core, no network, receipts stay on the machine). Up to 200 receipts per batch, verified against one issuer public key.
中文:本地批量审计最多 200 张 CCS 审计收据——逐张 Ed25519 验签 + JCS/SHA-256 完整性校验,输出有效/无效统计、通过率、篡改索引和逐条失败原因,可选哈希链 链接检查;默认零网络、数据不出本机。
Every receipt in the batch runs the same full pipeline as single-receipt verification:
total / valid / invalid / pass_rate, failure-reason
distribution, the tampered-index list (tampered_indexes), and
per-receipt results (index, decision_id, verdict, error summary, tamper
flag, duration).--check-chain): for ordered batches,
verify that previous_receipt_hash[i] equals the recomputed content
hash of the prior receipt; reports the first break point (index + reason).Stateless and idempotent: re-auditing the same batch gives identical statistics.
# Batch audit (public key embedded in the file, or supplied via -k)
python3 scripts/batch_audit.py -f examples/batch_mixed.json
# Separate public key + hash-chain check
python3 scripts/batch_audit.py -f receipts.json -k pub.pem --check-chain
# Machine-readable JSON (full per-receipt detail)
python3 scripts/batch_audit.py -f receipts.json -k pub.pem --json
# Read from stdin ({"receipts":[...]} or a bare receipt array)
cat receipts.json | python3 scripts/batch_audit.py -k pub.pem
Exit codes: 0 = all valid; 1 = at least one invalid/tampered receipt
(report still printed); 2 = input error.
Arguments:
| Arg | Description |
|---|---|
-f/--file | Batch JSON file ({"receipts":[...]} or a bare array); omit or - for stdin |
-k/--public-key | Issuer public key PEM file (required unless the file embeds public_key_pem) |
--check-chain | Also verify hash-chain linkage between receipts |
--json | Emit the full JSON report (per-item detail) |
--online | Explicitly use Correctover's hosted audit (default is local, offline) |
--endpoint | Online mode: override the service endpoint (self-hosted) |
Privacy boundary: default batch verification is entirely local — no
network request, receipts and public keys stay on the machine. The core is
the open-source CCS implementation (same code as the official hosted
service). Only with an explicit --online flag are receipts and the issuer
public key sent over HTTPS; private keys are never needed, read, or
transmitted.
{
"total": 5, "valid": 4, "invalid": 1, "pass_rate": 0.8,
"fail_reason_distribution": {"Ed25519 signature verification failed": 1},
"tampered_indexes": [4],
"chain": null,
"results": [
{"index": 0, "valid": true, "decision_id": "dec-batch-000",
"verdict": "allow", "errors": [], "tamper_detected": false,
"duration_ms": 1.8}
]
}
examples/batch_mixed.json holds 5 receipts (4 genuinely signed; the 5th
tampered — verdict flipped to block, checks.security.status flipped to
fail, signature unchanged):
total : 5
valid : 4
invalid : 1
pass : 0.8
tampered: [4]
Per-receipt (invalid only; use --json for full detail):
[#4] dec-batch-004 verdict=block tamper=True
content_hash does not match recomputed SHA-256(JCS payload)
Ed25519 signature verification failed (signature vs canonical payload mismatch)
A 5-receipt batch takes about 4–5 ms locally (measured; varies by machine).
Python 3.7+, standard library only (urllib/json/hashlib). No
third-party packages required for local mode.
By Correctover (Guigui Wang) — Correctover = AI Reliability. CCS (Correctover Conformance Shape) is an open, vendor-neutral runtime verification standard for AI agents: 7 dimensions with Ed25519-signed receipts that make agent tool calls auditable and tamper-evident — signed evidence you can hand across teams, pipelines, and systems. Homepage: https://correctover.com/?utm_source=clawhub&utm_medium=skill&utm_campaign=ccs_batch
Results are auto-generated and apply only to the submitted data. Automated checks are an aid only and constitute no security guarantee, compliance conclusion, audit opinion, or legal opinion. No endorsement by OWASP, IETF, or any standards body is claimed. The business impact of tampered receipts is outside the scope of automated checks and requires manual review; any security or compliance decision must ultimately rely on qualified human review.
MIT-0 for this ClawHub distribution. Anyone may use, modify, and redistribute it, including commercially, with no attribution required.