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 cacheforge-ai/cacheforge-skills --skill prom-querygit clone --depth 1 https://github.com/cacheforge-ai/cacheforge-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/cacheforge-ai/cacheforge-skills/prom-query)<a href="https://agentmods.dev/skills/cacheforge-ai/cacheforge-skills/prom-query"><img src="https://agentmods.dev/badge/skills/cacheforge-ai/cacheforge-skills/prom-query/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/cacheforge-ai/cacheforge-skills/prom-query"><img src="https://agentmods.dev/badge/skills/cacheforge-ai/cacheforge-skills/prom-query.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00021 | $0.02035 |
| Opus 5.5 | $0.00008 | $0.00814 |
| Sonnet 5.5 | $0.00004 | $0.00407 |
| Haiku 4.5 | $0.00002 | $0.00203 |
Grade A, and why
prom-query 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 1mo 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 — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.
prom-query — Prometheus Metrics Query & Alert Interpreter
You have access to a Prometheus-compatible metrics server. Use this skill to query metrics, check alerts, inspect targets, and explore available metrics. You can query Prometheus, Thanos, Mimir, and VictoriaMetrics — they all share the same HTTP API.
Commands
| Command | Purpose | Example |
|---|---|---|
query <promql> |
Instant query (current value) | prom-query query 'up' |
range <promql> [--start=] [--end=] [--step=] |
Range query (timeseries over time) | prom-query range 'rate(http_requests_total[5m])' --start=-1h --step=1m |
alerts [--state=firing|pending|inactive] |
List active alerts | prom-query alerts --state=firing |
targets [--state=active|dropped|any] |
Scrape target health | prom-query targets |
explore [pattern] |
Search available metrics by name pattern | prom-query explore 'http_request' |
rules [--type=alert|record] |
Alerting & recording rules | prom-query rules --type=alert |
How to Translate Natural Language to PromQL
When the user asks a question about their system, translate it to PromQL using these patterns:
Error Rate
# "What's the error rate for the API?"
rate(http_requests_total{code=~"5.."}[5m]) / rate(http_requests_total[5m])
# "Error rate for the payments service"
rate(http_requests_total{service="payments", code=~"5.."}[5m])
# "4xx and 5xx errors per second"
sum(rate(http_requests_total{code=~"[45].."}[5m])) by (code)
Latency (Histograms)
# "P99 latency"
histogram_quantile(0.99, sum(rate(http_request_duration_seconds_bucket[5m])) by (le))
# "P50 latency by service"
histogram_quantile(0.50, sum(rate(http_request_duration_seconds_bucket[5m])) by (le, service))
# "Average request duration"
rate(http_request_duration_seconds_sum[5m]) / rate(http_request_duration_seconds_count[5m])
CPU Usage
# "CPU usage per instance"
100 - (avg by (instance) (rate(node_cpu_seconds_total{mode="idle"}[5m])) * 100)
# "CPU usage per pod (Kubernetes)"
sum(rate(container_cpu_usage_seconds_total{container!=""}[5m])) by (pod, namespace)
# "Which pods use the most CPU?"
topk(10, sum(rate(container_cpu_usage_seconds_total{container!=""}[5m])) by (pod, namespace))
What ships with it
6 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.
- 1mo ago First seen · 211 lines · 21 tokens per session scan A 54d15af58f05
prom-query is a skill published in the GitHub repository cacheforge-ai/cacheforge-skills (10 stars, last pushed 7mo ago), licensed MIT. It adds 21 tokens to every session and 2,035 once invoked, about $0.0001 per session on Opus 5.5. 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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