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 vasilyu1983/AI-Agents-public --skill qa-observabilitygit clone --depth 1 https://github.com/vasilyu1983/AI-Agents-publicWrote 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/vasilyu1983/ai-agents-public/qa-observability)<a href="https://agentmods.dev/skills/vasilyu1983/ai-agents-public/qa-observability"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/qa-observability/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/vasilyu1983/ai-agents-public/qa-observability"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/qa-observability.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.04118 |
| Opus 5 | $0.00018 | $0.02059 |
| Sonnet 5 | $0.00007 | $0.00824 |
| Haiku 4.5 | $0.00004 | $0.00412 |
Grade A, and why
qa-observability 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 9d 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 — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QA Observability
Use telemetry as a QA signal and a debugging substrate. Treat logs, metrics, traces, and profiles as evidence for test outcomes, release readiness, and production regressions.
Core references live in data/sources.json. Prefer primary docs and re-check volatile external facts before recommending versions, pricing, or vendor features.
Quick Start (Default)
If key context is missing, ask for: critical user journeys, service/dependency inventory, environments (local/staging/prod), current telemetry stack, and current SLO/SLA commitments.
- Establish the minimum bar: correlation IDs, structured logs, traces, and golden metrics (latency, traffic, errors, saturation).
- Verify propagation: confirm
traceparentand your request ID flow across boundaries end-to-end. - Make failures diagnosable: every integration or E2E failure should capture a trace link or trace ID plus correlated logs, and critical degraded paths should expose structured error metadata such as rate-limit codes, retry hints, and state-transition markers.
- Define SLIs/SLOs and an error budget policy; wire multi-window burn-rate alerts.
- Produce artifacts: a readiness checklist, an SLO definition, and alert rules using
assets/checklists/template-observability-readiness-checklist.md,assets/monitoring/slo/slo-definition.yaml, andassets/monitoring/slo/prometheus-alert-rules.yaml.
Default QA stance
- Treat telemetry as acceptance criteria, especially for integration and E2E flows.
- Require correlation: request ID plus trace ID across service boundaries.
- For critical journeys, make auth redirects, rate limits, and state-sync lag diagnosable with structured codes or attributes instead of opaque text-only errors.
- Prefer SLO-based release gates and burn-rate alerts over raw infrastructure thresholds.
- Treat sampling, cardinality, retention, and cost as quality constraints.
- Redact PII and secrets by default in logs, spans, and attributes.
- Treat logs and profiles as ecosystem-dependent in OpenTelemetry: confirm language and backend support before promising a vendor-neutral implementation.
- The OTel Span Events API (
Span.AddEvent,Span.RecordException) is being deprecated in favour of log-based events (announced March 2026). Write new event instrumentation via the Logs API; existing span event data remains functional during the gradual transition.
What ships with it
39 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 337 B
- assets/checklists/template-observability-readiness-checklist.md 2.3 KB
- assets/load-testing/load-testing-k6.js 7.2 KB runs code
- assets/load-testing/template-load-test-artillery.yaml 3.4 KB
- assets/monitoring/grafana/grafana-dashboard-slo.json 9.1 KB
- assets/monitoring/grafana/template-grafana-dashboard-observability.json 9.5 KB
- assets/monitoring/slo/prometheus-alert-rules.yaml 10 KB
- assets/monitoring/slo/slo-definition.yaml 8.6 KB
- assets/observability/template-logging-setup.md 4.6 KB
- assets/opentelemetry/nodejs/opentelemetry-nodejs-setup.md 4.9 KB
- assets/opentelemetry/python/opentelemetry-python-setup.md 4.0 KB
- assets/performance/backend/template-nodejs-profiling-config.js 9.0 KB runs code
- assets/performance/frontend/template-lighthouse-ci.json 2.0 KB
- data/sample-observability-profile.json 2.4 KB
- data/sample-slo-data.json 2.1 KB
- data/sources.json 13 KB
- learnings.consolidated.md 592 B
- learnings.md 365 B
- references/alerting-strategies.md 21 KB
- references/anti-patterns-best-practices.md 14 KB
- references/control-theory-applied.md 30 KB
- references/core-analysis-loop.md 9.2 KB
- references/core-observability-patterns.md 5.1 KB
- references/dashboard-design-patterns.md 18 KB
- references/distributed-tracing-patterns.md 4.9 KB
- references/information-theory-applied.md 33 KB
- references/log-aggregation-patterns.md 3.6 KB
- references/methods-red-use-golden.md 3.6 KB
- references/observability-maturity-model.md 14 KB
- references/opentelemetry-best-practices.md 12 KB
- references/performance-profiling-guide.md 18 KB
- references/queueing-theory-applied.md 37 KB
- references/reliability-theory-applied.md 40 KB
- references/sampling-strategies.md 15 KB
- references/slo-design-guide.md 25 KB
- references/tools-ebpf-apm.md 7.4 KB
- scripts/observability_scorer.py 30 KB runs code
- scripts/README.md 5.2 KB
- scripts/test_observability_scorer.py 2.7 KB runs code
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.
- 9d ago First seen · 224 lines · 37 tokens per session scan A b057ebd38c50
qa-observability is a skill published in the GitHub repository vasilyu1983/AI-Agents-public (87 stars, last pushed 10d ago), licensed MIT. It adds 37 tokens to every session and 4,118 once invoked, about $0.0002 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 2026-09-03.
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