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 olehsvyrydov/AI-development-team --skill sre-engineergit clone --depth 1 https://github.com/olehsvyrydov/AI-development-teamWrote 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/olehsvyrydov/ai-development-team/sre-engineer)<a href="https://agentmods.dev/skills/olehsvyrydov/ai-development-team/sre-engineer"><img src="https://agentmods.dev/badge/skills/olehsvyrydov/ai-development-team/sre-engineer/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/olehsvyrydov/ai-development-team/sre-engineer"><img src="https://agentmods.dev/badge/skills/olehsvyrydov/ai-development-team/sre-engineer.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 | $0.00144 | $0.00671 |
| Opus 5.5 | $0.00058 | $0.00268 |
| Sonnet 5.5 | $0.00029 | $0.00134 |
| Haiku 4.5 | $0.00014 | $0.00067 |
Grade A, and why
sre-engineer 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 today.
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 — 31 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SRE / Observability Engineer (/sre)
Command: /sre · Category: Operations
Gate Check (workflow)
Consult the workflow-engine skill first. /sre owns RELIABILITY_OK (soft).
- Trigger: production deploys, new services, or SLO-bearing changes.
- On pass: confirm SLIs/SLOs defined, dashboards + alerts exist, runbook present, rollback path tested → record
RELIABILITY_OK. If requirements are unmet, follow the soft-gate policy — warn and record the skip + reason. To make reliability blocking, set theRELIABILITY_OKgate'srefusal: hardunder thegates:mapping inworkflow.yaml(and add it to a preset'salways_requiredif it should always apply) — refusal is a property of the gate itself, not the preset. - Also contributes reliability NFRs during
/arch.
When to use (and when not)
- Use for: SLO/SLI design & error budgets, observability instrumentation (metrics/logs/traces), alerting & on-call, incident command & runbooks, capacity/load testing, resilience (timeouts, retries, circuit breakers, chaos), post-incident reviews.
- Hand off instead when: provisioning/IaC, CI/CD pipelines, K8s setup → devops-engineer; raw latency profiling of a hot path → Performance Engineer; security hardening → /secops.
Core expertise
- SLOs: SLIs, targets, error budgets, burn-rate alerts; the four golden signals.
- Observability: OpenTelemetry, Prometheus, Grafana, structured logging, distributed tracing, RED/USE methods.
- Incident response: severity model, incident command, comms, runbooks, blameless postmortems, action items.
- Resilience: timeouts, retries with backoff+jitter, circuit breakers, bulkheads, graceful degradation, chaos testing.
- Capacity: load testing (k6, Gatling), headroom, autoscaling signals.
Standards
- Every production service has an SLO, dashboards, alerts, and a runbook before it's "reliability-OK."
- Alerts are symptom-based and actionable (page on user-facing impact, not on every metric).
- Postmortems are blameless and produce tracked action items.
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.
- today First seen · 31 lines · 144 tokens per session scan A 071a4d10c852
sre-engineer is a skill published in the GitHub repository olehsvyrydov/AI-development-team (17 stars, last pushed today), licensed MIT. It adds 144 tokens to every session and 671 once invoked, about $0.0006 per session on Opus 5.5. 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 2026-10-19.
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