Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/dingdawg/dingdawg-governanceWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/dingdawg/dingdawg-governance/receipts)<a href="https://agentmods.dev/commands/dingdawg/dingdawg-governance/receipts"><img src="https://agentmods.dev/badge/commands/dingdawg/dingdawg-governance/receipts/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/dingdawg/dingdawg-governance/receipts"><img src="https://agentmods.dev/badge/commands/dingdawg/dingdawg-governance/receipts.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00394 |
| Opus 5 | $0.00000 | $0.00197 |
| Sonnet 5 | $0.00000 | $0.00079 |
| Haiku 4.5 | $0.00000 | $0.00039 |
Grade C, and why
receipts scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
#gvn_01J5KW9 Bash blocked 12:02:17 "Blocked: dangerous rm -rf pattern" What it actually says
/governance-receipts
View the tamper-evident receipts generated for governed actions in the current session or a specified time window.
Usage
/governance-receipts
/governance-receipts --limit 20
/governance-receipts --since 2024-01-15T09:00:00Z
Options
| Option | Description | Default |
|---|---|---|
--limit N |
Number of receipts to return | 10 |
--since ISO8601 |
Only receipts after this timestamp | current session |
--tool NAME |
Filter by tool name | all tools |
--status ok|blocked |
Filter by outcome | all |
What it does
- Calls the
query_receiptstool on the DingDawg Governance MCP server - Returns a chronological list of receipts with tool name, timestamp, and outcome
- Each receipt ID links to the full governance record on the DingDawg dashboard
Example output
DingDawg Governance — Recent Receipts
──────────────────────────────────────
#gvn_01J5KX2 Edit success 12:04:33
#gvn_01J5KX1 Bash success 12:03:58
#gvn_01J5KX0 Write success 12:03:41
#gvn_01J5KW9 Bash blocked 12:02:17 "Blocked: dangerous rm -rf pattern"
──────────────────────────────────────
4 receipts | View all: https://app.dingdawg.com/governance/receipts
Tool called
dingdawg-governance → query_receipts
Arguments forwarded from the command options above.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 46 lines · 0 tokens per session scan C a8722385822e
receipts is a command published in the GitHub repository dingdawg/dingdawg-governance (1 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 394 tokens. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
ai-act-incidents
Show real-world and research-demonstrated security incidents that map to a scanner dimension, EU AI Act article, or threat category. Surfaces OWASP LLM/ASI, NIST AI RMF, and MITRE ATLAS cross-references alongside published mitigations.
ai-act-scan
Scan a codebase for EU AI Act compliance evidence and gaps. Produces a dimension-scored report with per-file findings, architecture graph, and prioritized recommendations.
ai-act-article
Show which analyzers, compliance dimensions, and current findings in this codebase map to a specific EU AI Act article.
ai-act-ask
Answer an EU AI Act question grounded in the bundled knowledge base — verbatim statute text, obligation paraphrases, and the compound-risk taxonomy. Offline and deterministic by default; cites the articles it relies on.
ai-act-settings
View or change the scanner's settings — mode (deterministic vs assisted) and autoapply. Assisted mode lets the plugin use your own Claude Code for semantic scanning, grounded Q&A, and applying fixes.
ai-act-scan-fix
Scan a codebase, then propose concrete remediation (code edits, new files, tests) for the top compliance gaps. Does NOT auto-apply — always shows the plan first.