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 AnastasiyaW/codex-claude-code-config --skill observability-monitoringgit clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-configWrote 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/anastasiyaw/codex-claude-code-config/observability-monitoring)<a href="https://agentmods.dev/skills/anastasiyaw/codex-claude-code-config/observability-monitoring"><img src="https://agentmods.dev/badge/skills/anastasiyaw/codex-claude-code-config/observability-monitoring/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/anastasiyaw/codex-claude-code-config/observability-monitoring"><img src="https://agentmods.dev/badge/skills/anastasiyaw/codex-claude-code-config/observability-monitoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 190 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00109 | $0.03485 |
| Opus 5 | $0.00055 | $0.01742 |
| Sonnet 5 | $0.00022 | $0.00697 |
| Haiku 4.5 | $0.00011 | $0.00348 |
Grade A, and why
observability-monitoring 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 12d 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 — 243 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Observability Monitoring
Use this skill to turn vague "is it working?" questions into evidence-backed monitoring, alerting, and incident workflows. Start from user or business impact, then move down through the system layers and choose the signal that can prove the current hypothesis.
Operating rule
Do not treat a green dashboard as proof of health. A monitoring claim is complete only when it names:
- the observed scope and time window;
- the user, business, or operator outcome being protected;
- the signal and exact query/probe that supports the claim;
- the threshold or SLO that defines bad;
- the next human action and its runbook/evidence link.
Keep code review, live runtime proof, UI/render proof, and release readiness as separate verdicts.
Investigation is read-only by default. A restart, alert suppression, metric-schema/label change, sampling or retention change, or vendor reconfiguration is a production mutation: involve the responsible owner or incident authority, preserve the relevant evidence first, capture the exact config/command diff, state the rollback condition, and verify the user probe plus SLI after the change.
Workflow
1. Freeze scope and collect live facts
Before changing a monitor, alert, host, or service:
- Read the repository
AGENTS.md, relevant rules, runbooks, and deployment docs. - Establish the actual checkout/branch, deployment, process, host, port, proxy/tunnel, and data source.
- Record the observation time, environment, query/probe, and whether the result is current or historical.
- Inspect the source code/config that emits or consumes the signal before changing it.
- Never infer health from an old screenshot, a stale handoff, a single PID, or a dashboard with no successful user probe.
For infrastructure fixes, document the traffic path (DNS, proxy, tunnel, ingress, service, backend) before touching a surprising value such as 127.0.0.1, a non-default port, or a disabled check.
2. Define the outcome before the metric
What ships with it
2 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.
- 12d ago First seen · 243 lines · 109 tokens per session scan A 164724027cf4
observability-monitoring is a skill published in the GitHub repository AnastasiyaW/codex-claude-code-config (150 stars, last pushed 4d ago), licensed MIT. It adds 109 tokens to every session and 3,485 once invoked, about $0.0005 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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