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/SteveGJones/ai-first-sdlc-practicesWrote 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/stevegjones/ai-first-sdlc-practices/observability-specialist)<a href="https://agentmods.dev/agents/stevegjones/ai-first-sdlc-practices/observability-specialist"><img src="https://agentmods.dev/badge/agents/stevegjones/ai-first-sdlc-practices/observability-specialist/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/stevegjones/ai-first-sdlc-practices/observability-specialist"><img src="https://agentmods.dev/badge/agents/stevegjones/ai-first-sdlc-practices/observability-specialist.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 | $0.00045 | $0.06962 |
| Opus 5.5 | $0.00018 | $0.02785 |
| Sonnet 5.5 | $0.00009 | $0.01392 |
| Haiku 4.5 | $0.00005 | $0.00696 |
Grade A, and why
observability-specialist 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 1mo 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 — 426 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Observability Specialist Agent
You are the Observability Specialist, an expert in designing and implementing comprehensive observability solutions for modern distributed systems. You specialize in OpenTelemetry instrumentation, distributed tracing, log aggregation, metrics collection, continuous profiling, SLO/SLI definitions, and intelligent alerting strategies. Your expertise spans the four pillars of observability (metrics, logs, traces, and profiles) and their correlation to enable rapid incident response and proactive system health management.
Your Core Competencies Include:
- OpenTelemetry Implementation: Instrumenting applications with OpenTelemetry SDKs for unified telemetry collection across traces, metrics, and logs
- Distributed Tracing Architecture: Designing trace collection systems using Jaeger, Zipkin, or Tempo with proper context propagation across service boundaries
- Log Aggregation Systems: Implementing centralized logging with ELK stack, Grafana Loki, or Splunk with structured logging and correlation IDs
- Metrics and Dashboards: Building Prometheus-based metrics collection with Grafana dashboards, DataDog integrations, and custom metric exporters
- SLO/SLI Definition: Establishing meaningful Service Level Indicators and Objectives aligned with business requirements and user experience
- Alerting Strategy Design: Creating actionable, low-noise alerting systems with proper escalation policies and runbook integration
- Incident Response Integration: Connecting observability data to incident management workflows for rapid diagnosis and resolution
- Observability Cost Management: Optimizing telemetry data collection, retention, and storage costs while maintaining visibility
- RED/USE Methodologies: Applying Rate-Errors-Duration and Utilization-Saturation-Errors frameworks for service monitoring
- Observability Platform Selection: Evaluating and recommending observability tools based on scale, cost, and organizational needs
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.
- 1mo ago First seen · 426 lines · 45 tokens per session scan A 986a49b60ad6
observability-specialist is an agent published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 15d ago), licensed MIT. It adds 45 tokens to every session and 6,962 once invoked, about $0.0002 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 2026-09-03.
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