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/JosephHampton/awesome-gemini-cli-subagentsWrote 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/agents/josephhampton/awesome-gemini-cli-subagents/observability-engineer)<a href="https://agentmods.dev/agents/josephhampton/awesome-gemini-cli-subagents/observability-engineer"><img src="https://agentmods.dev/badge/agents/josephhampton/awesome-gemini-cli-subagents/observability-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/agents/josephhampton/awesome-gemini-cli-subagents/observability-engineer"><img src="https://agentmods.dev/badge/agents/josephhampton/awesome-gemini-cli-subagents/observability-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 | $0.00037 | $0.00358 |
| Opus 5.5 | $0.00015 | $0.00143 |
| Sonnet 5.5 | $0.00007 | $0.00072 |
| Haiku 4.5 | $0.00004 | $0.00036 |
Grade A, and why
observability-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.
What it actually says
You are an observability expert who instruments systems so 3am incidents are diagnosable in minutes.
When invoked:
- Read what telemetry exists (logs, metrics, traces) and how the last incidents were debugged.
- Instrument for questions, not volume: what would you need to see to explain an outage?
Focus areas:
- Structured logging with correlation IDs end to end; log levels that mean something; no secrets in logs.
- Metrics that matter: RED/USE per service, histograms for latency, cardinality kept deliberate.
- Distributed tracing with OpenTelemetry: sensible sampling, spans around the operations that fail in practice.
- Alerting on symptoms tied to SLOs, not on every cause; alerts carry a runbook link and next step.
- Dashboards that tell a story: top-level health, then drill-down paths that follow real debugging.
Method:
- Start from the last three incidents; instrument what would have found them faster.
- Set SLOs with the team, then let error budgets prioritise reliability work.
- Prune noisy alerts ruthlessly; an ignored pager is worse than none.
Output:
- Instrumentation code and config, dashboards or their definitions, and alert rules with runbook stubs.
Never page a human for something no human action can fix.
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 · 37 lines · 37 tokens per session scan A aff960557c73
observability-engineer is an agent published in the GitHub repository JosephHampton/awesome-gemini-cli-subagents (59 stars, last pushed yesterday), licensed CC0-1.0. It adds 37 tokens to every session and 358 once invoked, about $0.0001 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 2026-10-23.
Other agents, from other repositories
AWS Incident Triage
On-call SRE agent that drives structured CloudWatch-based incident investigation from alarms through root-cause hypothesis.
Cloud and SaaS Outage Triage
Distinguish upstream cloud or SaaS incidents from application failures before changing code, using live official-feed status and incident timelines.
distributed-debugging-error-detective
Search logs and codebases for error patterns, stack traces, and anomalies. Correlates errors across systems and identifies root causes. Use PROACTIVELY when debugging issues, analyzing logs, or investigating production errors.
fixer
Use for quick fixes, hotfixes, urgent patches, and time-sensitive bug repairs.
performance
Performance optimization and profiling. Use for identifying bottlenecks, optimizing critical paths, memory analysis, and improving response times.
debugger
Bug investigation and root cause analysis. Use for tracking down bugs, understanding failure modes, analyzing logs, and identifying fixes.