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.
npx agentmods add skills/easingthemes/dx-aem-flow/auto-statusnpx skills add easingthemes/dx-aem-flow --skill auto-statusgit clone --depth 1 https://github.com/easingthemes/dx-aem-flowWrote 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/skills/easingthemes/dx-aem-flow/auto-status)<a href="https://agentmods.dev/skills/easingthemes/dx-aem-flow/auto-status"><img src="https://agentmods.dev/badge/skills/easingthemes/dx-aem-flow/auto-status.svg" alt="Measured on agentmods" 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 | $0.00036 | $0.01038 |
| Opus 5 | $0.00018 | $0.00519 |
| Sonnet 5 | $0.00007 | $0.00208 |
| Haiku 4.5 | $0.00004 | $0.00104 |
Grade A, and why
auto-status scanned grade A with 0 findings 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 5d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You display an operational dashboard showing current DLQ depth, token budget utilization, and rate limit usage. All commands are read-only — no mutations.
0. Prerequisites
Read .ai/automation/infra.json to get automationProfile, region, and table names.
Profile check: If automationProfile is consumer (or legacy pr-only/pr-delegation):
This repo uses the <profile> profile — DLQ, token budget, and rate limits are managed by the hub project.
Run /auto-status from the hub repo instead.
STOP.
Check AWS credentials are available:
aws sts get-caller-identity --query Account --output text 2>/dev/null || echo "NO_CREDENTIALS"
If no credentials: "AWS credentials not configured. Run aws configure or set AWS_ACCESS_KEY_ID + AWS_SECRET_ACCESS_KEY." STOP.
1. DLQ Depth
cd .ai/automation
node eval/process-dlq.js --depth
If DLQ depth > 0:
# Show message summaries (not full content)
node eval/process-dlq.js --list
2. Token Budget
cd .ai/automation
node eval/cost-report.js
3. Rate Limits
cd .ai/automation
node eval/rate-limit-report.js
4. Summary Report
Present results as a combined dashboard:
## Automation Status
**DLQ:** <N> messages <(✓ empty | ⚠️ N messages pending)>
**Token budget:** <utilization>% of monthly cap (<tokens>/<cap>) — mode: <normal|suggest-only|halted>
**Rate limits today:** DoR <N>/20, PR Review <N>/50, PR Answer <N>/30
<If any DLQ messages:>
### DLQ Messages
<list of message summaries: timestamp, error type, function name>
Investigate: `cd .ai/automation && node eval/process-dlq.js`
<If budget > 80%:>
⚠️ Token budget at <N>% — approaching limit. Consider increasing `MONTHLY_TOKEN_CAP` pipeline variable.
<If budget halted:>
🚨 Token budget exhausted — all LLM calls blocked until next month.
Examples
/auto-status— Queries AWS for DLQ depth (0 messages), monthly token usage (45% of budget), and daily rate limit usage (120/500 calls). Reports all metrics as healthy with green indicators.
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.
- 5d ago First seen · 104 lines · 36 tokens per session scan A 81fcae361064
auto-status is a skill published in the GitHub repository easingthemes/dx-aem-flow (6 stars, last pushed 4d ago), licensed MIT. It adds 36 tokens to every session and 1,038 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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