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monitoring-graphs

monitoring-graphs is a skill for Claude Code, Codex from gemini-cli-extensions/sre. It costs 46 tokens per session (1,494 once invoked), scanned A, original, Apache-2.0.

A Python-based workflow for creating annotated graphs from real monitoring data. The graphs can show error rates, outages, and the timing of incident milestones.

In plain words
What is it for?
Selecting useful metrics, retrieving them from Cloud Monitoring, handling blackout periods, and producing UTC-timestamped incident graphs.
Why use it?
It keeps postmortem charts tied to measured data instead of invented or guessed numbers, including during periods when monitoring data is missing.

Skill for Claude CodeCodex

Part of the sre-extension plugin — 16 skills shipped together

not rated 83 yesterday A scan 46 tokens original Apache-2.0
View the source file gemini-cli-extensions/sre
Install

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.

agentmods
npx agentmods add skills/gemini-cli-extensions/sre/monitoring-graphs
Any agent
npx skills add gemini-cli-extensions/sre --skill monitoring-graphs
Clone the repo
git clone --depth 1 https://github.com/gemini-cli-extensions/sre

Made for: Claude Code, Codex.

Or install sre-extension, the plugin that ships this one along with the rest of its 16 skills.

Wrote 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.

agentmods badge for monitoring-graphs

README.md
[![agentmods](https://agentmods.dev/badge/skills/gemini-cli-extensions/sre/monitoring-graphs.svg)](https://agentmods.dev/skills/gemini-cli-extensions/sre/monitoring-graphs)
Your own site
<a href="https://agentmods.dev/skills/gemini-cli-extensions/sre/monitoring-graphs"><img src="https://agentmods.dev/badge/skills/gemini-cli-extensions/sre/monitoring-graphs.svg" alt="Measured on agentmods" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,494 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00046 $0.01494
Opus 5 $0.00023 $0.00747
Sonnet 5 $0.00009 $0.00299
Haiku 4.5 $0.00005 $0.00149

Measured 4d ago against content hash 1f90280800d0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

monitoring-graphs 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 4d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/csv_to_sparkline.py, scripts/plot_archetype.py, scripts/reference_dual_plot.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/monitoring-graphs/SKILL.md · 97 lines

How it starts

The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.

📈 Monitoring & Incident Graphing Skill 📊

This skill guides the agent through identifying high-signal metrics, extracting data efficiently, and creating professional annotated graphs.

🚨 DATA INTEGRITY: NEVER MAKE UP NUMBERS

  • ONLY REAL DATA: Absolutely NEVER fake data, interpolate guesses, or hard-code values (like forcing a firewall block period to exactly 0) just to make a graph look "correct" or align with a narrative.
  • The Data Is The Source Of Truth: If there is an outage, the raw metrics or the absence of metrics must prove it. Show the real raw availability.
  • Handling Complete Blackouts: If a full blackout causes missing data points from the API, do not invent data. Instead, use Pandas reindex to fill the missing continuous time intervals with 0s.

🚀 Workflow

1. Metric Selection & Efficient Extraction 🕵️‍♀️

  • Standard Time: Always use UTC for all timestamps by default. 🌐
  • Performance Tip: Cloud Monitoring can be VERY SLOW for high-res data. 🐢
  • Execution:
    1. Use Monitoring MCP to find relevant metrics for the incident time window.
    2. Download the data as CSV (e.g., out/incident/metric.csv) or directly parse JSON.
    3. Use a sub-agent (generalist) for large datasets to keep the main session history lean.
  • Reference: See archetypes.md for "Apple-to-Apple" strategies and granularity tables.

2. Baseline Graph (Draft) 🖼️

  • Rule: Always generate a raw "Draft" graph first to confirm the data shows a clear signal.
  • Command: 
    uv run ./scripts/plot_archetype.py --csv data.csv --out draft.png --title "Title"
  • Verification: Ensure the graph is not "flat." The X-axis must explicitly show "Time (UTC)" so there is no ambiguity! 🕰️

3. Annotated Graph (Final) 🔴

  • Requirement: Only proceed after the user confirms the draft is "good."
  • Command: 
    # Times are assumed to be UTC unless --timezone is specified
uv run ./scripts/plot_archetype.py \
  --csv data.csv \
  --out final.png \
  --final \
  --start "YYYY-MM-DD HH:MM:SS" \
  --detect "YYYY-MM-DD HH:MM:SS" \
  --mitigate "YYYY-MM-DD HH:MM:SS" \
  --end "YYYY-MM-DD HH:MM:SS"
  • Styling Guidelines (Annotations):
    • Red (#d93025): Breakages, outages, faults, or incident start/end. Use different line thicknesses (linewidth=1 to 3) or styles (:, --, -.) to denote severity.
    • Yellow (#f9ab00): Human detection or alert triggered.
    • Green (#1e8e3e): Fix, mitigation, or resolution applied.

Read the full file on GitHub · 97 lines

Files

What ships with it

14 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.

Changes

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.

  1. 4d ago First seen · 97 lines · 46 tokens per session scan A 1f90280800d0

Subscribe to this mod's changes

monitoring-graphs is a skill published in the GitHub repository gemini-cli-extensions/sre (83 stars, last pushed yesterday), licensed Apache-2.0. It adds 46 tokens to every session and 1,494 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 2026-08-30.

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