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 agentmods add skills/aiops-tools/observability-aiops/observability-aiopsnpx skills add AIops-tools/Observability-AIops --skill observability-aiopsgit clone --depth 1 https://github.com/AIops-tools/Observability-AIopsWrote 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/aiops-tools/observability-aiops/observability-aiops)<a href="https://agentmods.dev/skills/aiops-tools/observability-aiops/observability-aiops"><img src="https://agentmods.dev/badge/skills/aiops-tools/observability-aiops/observability-aiops.svg" alt="Measured on agentmods" 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 | $0.00484 | $0.04925 |
| Opus 5 | $0.00242 | $0.02462 |
| Sonnet 5 | $0.00097 | $0.00985 |
| Haiku 4.5 | $0.00048 | $0.00492 |
Grade A, and why
observability-aiops 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 5d 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 — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Observability AIops
Disclaimer: Community-maintained open-source project, not affiliated with, endorsed by, or sponsored by the Prometheus or Grafana projects, Grafana Labs, or the CNCF. Prometheus, Alertmanager and Grafana are trademarks of their respective owners. Source at github.com/AIops-tools/Observability-AIops under the MIT license.
Governed self-hosted observability operations — 39 MCP tools across
Prometheus (HTTP API + PromQL), Alertmanager (alerts + silences),
Grafana (dashboards, datasources, folders), and Grafana Loki (bounded
LogQL log reads + log RCA, read-only), every one wrapped with the bundled
@governed_tool harness: a local unified audit log under
~/.observability-aiops/, token/runaway budget guard, undo-token
recording, and descriptive risk-tier labels. One config can span the whole
stack. Bearer tokens are stored encrypted (~/.observability-aiops/secrets.enc,
Fernet + scrypt) — never plaintext on disk.
This is the self-hosted-observability complement to enterprise monitoring suites: it speaks the open Prometheus/Grafana APIs an SRE actually runs.
Standalone: the governance harness is bundled in the package (
observability_aiops.governance) — no external skill-family dependency. Beyond the mock suite, the Prometheus/Alertmanager/Grafana surfaces have been exercised against a live Prometheus 3.x + Alertmanager + Grafana 13 stack; the Loki surface has not yet been exercised live (seedocs/VERIFICATION.md).
What This Skill Does
| Group | Platform | Tools | Count | R/W |
|---|---|---|---|---|
| Metrics | Prometheus | instant_query, range_query, label_values, series_metadata | 4 | read |
| Targets & status | Prometheus | list_targets, target_scrape_health, dropped_targets, prometheus_config_status, prometheus_tsdb_status | 5 | read |
| Rules | Prometheus | list_rules, rule_health | 2 | read |
| Alerts | Prometheus/Alertmanager | firing_alerts, pending_alerts, alertmanager_alerts, list_silences | 4 | read |
| Grafana | Grafana | list_dashboards, get_dashboard, list_datasources, datasource_health, list_folders | 5 | read |
| Loki | Loki | loki_labels, loki_label_values, loki_query, loki_tail_errors | 4 | read |
| Overview + analyses | all | observability_overview + firing_alert_rca, target_scrape_health_analysis, alert_noise_and_flap_analysis | 4 | read |
| Log analyses + cross-signal | Loki (+ Prometheus) | log_error_burst_rca, log_volume_analysis, alert_log_context | 3 | read |
| Writes | Alertmanager/Grafana/Prometheus | create_silence, expire_silence (med) · create_annotation (med) · update_dashboard (med) · delete_dashboard (high) · reload_prometheus_config (med) | 6 | write |
What ships with it
4 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.
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.
- 5d ago First seen · 255 lines · 484 tokens per session scan A 22cf0b9745b8
observability-aiops is a skill published in the GitHub repository AIops-tools/Observability-AIops (0 stars, last pushed 3d ago), licensed MIT. It adds 484 tokens to every session and 4,925 once invoked, about $0.0024 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 2026-08-31.
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