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 skills add dungnotnull/hybrid-harness-chaos-process-prm --skill s23-alerting-recommendationsgit clone --depth 1 https://github.com/dungnotnull/hybrid-harness-chaos-process-prmWrote 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/dungnotnull/hybrid-harness-chaos-process-prm/s23-alerting-recommendations)<a href="https://agentmods.dev/skills/dungnotnull/hybrid-harness-chaos-process-prm/s23-alerting-recommendations"><img src="https://agentmods.dev/badge/skills/dungnotnull/hybrid-harness-chaos-process-prm/s23-alerting-recommendations/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/skills/dungnotnull/hybrid-harness-chaos-process-prm/s23-alerting-recommendations"><img src="https://agentmods.dev/badge/skills/dungnotnull/hybrid-harness-chaos-process-prm/s23-alerting-recommendations.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 | $0.00088 | $0.03145 |
| Opus 5 | $0.00044 | $0.01572 |
| Sonnet 5 | $0.00018 | $0.00629 |
| Haiku 4.5 | $0.00009 | $0.00314 |
Grade A, and why
alerting-recommendations 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 12d 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 — 354 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Alerting & Recommendations (s21)
Purpose
Transform chaos experiment results into structured alerts and prioritized remediation recommendations — closing the feedback loop between finding and fixing resilience gaps.
Prerequisites
- Observability integration from s22 (dashboards and metrics)
- Chaos experiment results for alert threshold calibration
- Feature flag chaos gate config from s08 (optional)
- Security scan results from s11 (for security-related alerts)
- PagerDuty/Slack integration available for alert routing
Input Contract
| Input | Source | Required |
|---|---|---|
| Experiment results (all) | s12-s18 outputs | Yes |
| Observability alert rules | s20 output | Yes |
| Post-chaos test evidence | s11 (rerun results) | Yes |
| Blast radius violations | s14 output | No |
| Feature flag states | s08 output | No |
| Alert routing preferences | s02 taste (observability) | Yes |
Output Contract
| Output | Destination | Format |
|---|---|---|
| Alert routing configuration | .commandcode/artifacts/alert-routing.yaml |
YAML |
| PagerDuty / Slack integration config | .commandcode/artifacts/alert-destinations.yaml |
YAML |
| Remediation recommendations | s24 (scoring), s25 (postmortem) | Markdown prioritized list |
| Alert severity classification matrix | s18 (game day runbook) | Table |
| Auto-remediation scripts | .commandcode/artifacts/auto-remediate/ |
Bash/Python |
Alert Severity Matrix
| Severity | Trigger | Channel | Response Time | Auto-Action |
|---|---|---|---|---|
| P0 — Critical | Error rate > 10% during chaos, probe failure, customer impact detected | PagerDuty | 1 min | Auto-abort experiments |
| P1 — High | Error rate > 5%, p99 latency > 2x baseline, resilience < 60 | Slack + PagerDuty | 5 min | Pause experiments, manual review |
| P2 — Medium | Error rate 2-5%, slight latency increase | Slack | 15 min | Continue, note for postmortem |
| P3 — Low | Single probe warning, metrics near threshold | Slack (thread) | 1 hour | Log only |
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.
- 12d ago First seen · 354 lines · 88 tokens per session scan A 6dcb126d9dff
alerting-recommendations is a skill published in the GitHub repository dungnotnull/hybrid-harness-chaos-process-prm (19 stars, last pushed 3mo ago), licensed MIT. It adds 88 tokens to every session and 3,145 once invoked, about $0.0004 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 2026-08-30.
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