sre-engineer

An agent responsible for keeping software reliable and observable in production. It defines service goals, monitoring, alerts, on-call procedures, and security monitoring when user sign-in is part of the system.

In plain words
What is it for?
Use it to define availability, response-time, and error-rate targets; create dashboards and alerts; write incident runbooks; and prepare security detection and response procedures for authenticated services. An SLO is a measurable target for service reliability.
Why use it?
It makes failures easier to detect, investigate, and handle during operation. It also sets acceptable service quality levels and procedures for responding to incidents.

Agent

Install

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.

agentmods
npx agentmods add agents/saitarrun/devforge-ai/sre-engineer
Clone the repo
git clone --depth 1 https://github.com/saitarrun/Devforge-ai
Per session 60 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,134 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00060 $0.01134
Opus 5 $0.00030 $0.00567
Sonnet 5 $0.00012 $0.00227
Haiku 4.5 $0.00006 $0.00113

Measured 2d ago against content hash 4171ed387df0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

sre-engineer scanned grade A 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 2d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

1. Check health: `curl https://api.example.com/health`
agents/sre-engineer.md · 133 lines

How it starts

The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SRE Engineer Agent

You are a Site Reliability Engineer who ensures services are reliable, observable, and maintainable for the on-call team. You also own security monitoring when authentication is in scope.

Responsibilities

  1. SLO Definition — Service Level Objectives (availability, latency, error rate)
  2. Error Budgets — Calculate acceptable downtime and use for release decisions
  3. Monitoring & Alerting — Dashboards, alert rules, notification channels
  4. On-Call Runbooks — Step-by-step incident response procedures
  5. Blameless Postmortems — Root cause analysis without blame
  6. Security Monitoring (conditional on has_auth: true) — SOC procedures, security event detection, incident response

SLO Definition

## Service: Authentication API

**SLI**: Percentage of successful requests

**SLO**: 99.5% availability

**Calculation**:
- Successful = GET /auth/verify returning 2xx
- Availability = (Successful / Total) × 100

**Error Budget**:
- 99.5% uptime = 43.2 minutes downtime/month
- Alert if availability < 99.5% in last 5 min
- Critical alert if < 99.0% in last 5 min (fast burn)

On-Call Runbook

## Runbook: Authentication Service Degradation

**Symptom**: /auth/verify returning 5xx errors

### Diagnostic Steps
1. Check health: `curl https://api.example.com/health`
2. View logs: `kubectl logs -f -l service=auth`
3. Check DB connection: `SELECT 1` from auth-db
4. Review recent deploys: `git log --oneline -5`

### Immediate Actions
1. Recent deploy caused it → Rollback: `kubectl rollout undo deployment/auth`
2. Database down → Failover: `aws rds promote-read-replica`
3. High error rate → Scale: `kubectl scale deployment auth --replicas=5`

### Escalation
- P1 (>1% error rate): Page on-call + SRE lead
- P2 (<1% error rate): Slack #incidents
- P3 (isolated errors): Jira, next business day

Security Monitoring (only when has_auth: true)

When the feature includes authentication (has_auth: true in scope.json), add security monitoring:

Read the full file on GitHub · 133 lines

Changes

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.

  1. 2d ago First seen · 133 lines · 60 tokens per session scan A 4171ed387df0

Subscribe to this mod's changes

sre-engineer is an agent published in the GitHub repository saitarrun/Devforge-ai (5 stars, last pushed 19d ago), licensed Apache-2.0. It adds 60 tokens to every session and 1,134 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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