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 SigNoz/agent-skills --skill signoz-setting-up-observabilitygit clone --depth 1 https://github.com/SigNoz/agent-skillsWrote 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/signoz/agent-skills/signoz-setting-up-observability)<a href="https://agentmods.dev/skills/signoz/agent-skills/signoz-setting-up-observability"><img src="https://agentmods.dev/badge/skills/signoz/agent-skills/signoz-setting-up-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/signoz/agent-skills/signoz-setting-up-observability"><img src="https://agentmods.dev/badge/skills/signoz/agent-skills/signoz-setting-up-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 | $0.00224 | $0.05952 |
| Opus 5 | $0.00112 | $0.02976 |
| Sonnet 5 | $0.00045 | $0.01190 |
| Haiku 4.5 | $0.00022 | $0.00595 |
Grade A, and why
signoz-setting-up-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 7d 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 — 456 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Setting Up Observability After Ingestion
Take a service from "telemetry is flowing into SigNoz" to "I have a
dashboard, alerts, saved views, and a tuning loop." This skill is an
orchestration layer, not a standalone reference: the mechanical
work lives in the sibling SigNoz skills and the MCP tools/resources hold
the current payload schemas. This skill sequences them and supplies the
judgment calls (scope, SLOs, thresholds, what to skip) that no single
skill owns; it deliberately does not restate payload schemas or field
rules, so read the relevant signoz://… resource before composing any
payload.
Use this when traces, logs, or metrics are already landing in SigNoz and you want an opinionated, SLO-aware setup, not when you're still wiring up the SDK. Audience: two consumers, an autonomous AI SRE agent that runs without a human in the loop (e.g. an in-product SigNoz assistant), and an engineer at a Claude Code / Codex / Cursor prompt. Both follow the same flow; where a step needs a human decision (Phase 1 triage, Phase 5 sign-off), the host decides how to surface it, and an autonomous host fills the gap from upstream context instead of blocking.
Prerequisites
This skill calls SigNoz MCP server tools (signoz_list_services,
signoz_list_dashboards, signoz_get_field_keys,
signoz_execute_builder_query, signoz_create_dashboard,
signoz_create_alert, signoz_create_view, etc.) and
delegates to sibling skills. Before running the workflow, confirm the
signoz_* tools are available. If they are not, the SigNoz MCP
server is not installed or configured; run signoz-mcp-setup first. Do
not fall back to raw HTTP calls or fabricate payloads.
When to use
Use this skill when the user wants the whole post-ingestion setup: SLI/SLO → exploration → dashboard → views → alerts → tuning, in any combination of those deliverables, sequenced as one workflow.
Do NOT use this skill when the user wants a single artifact; hand off directly:
- Just a dashboard →
signoz-creating-dashboards. - Just one static / threshold alert or notification rule →
signoz-creating-alerts. (But SLO / burn-rate / error-budget alerting, even with no dashboard, stays here: it needs the SLI/SLO capture and burn-rate judgment in the phases below.) - Just a saved Explorer view →
signoz-managing-views. - A one-off exploratory query →
signoz-generating-queries. - A concept/doc lookup (SRE methods, OTel conventions, burn-rate math)
→
signoz-searching-docs/signoz_search_docs.
What ships with it
1 file 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.
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.
- 7d ago Changed 864c9f91a464
- 11d ago First seen · 456 lines · 224 tokens per session scan A 7761c62bb4be
signoz-setting-up-observability is a skill published in the GitHub repository SigNoz/agent-skills (16 stars, last pushed 8d ago), licensed MIT. It adds 224 tokens to every session and 5,952 once invoked, about $0.0011 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 2026-08-30.
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