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 xobotyi/cc-foundry --skill promqlgit clone --depth 1 https://github.com/xobotyi/cc-foundryWrote 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/xobotyi/cc-foundry/promql)<a href="https://agentmods.dev/skills/xobotyi/cc-foundry/promql"><img src="https://agentmods.dev/badge/skills/xobotyi/cc-foundry/promql/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/xobotyi/cc-foundry/promql"><img src="https://agentmods.dev/badge/skills/xobotyi/cc-foundry/promql.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 | $0.00074 | $0.05256 |
| Opus 5.5 | $0.00030 | $0.02102 |
| Sonnet 5.5 | $0.00015 | $0.01051 |
| Haiku 4.5 | $0.00007 | $0.00526 |
Grade A, and why
promql 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 — 481 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PromQL
PromQL is a nested functional language for selecting and aggregating Prometheus time series. Every query is an expression tree: selectors at the leaves, functions and operators at the nodes, a single root value (scalar, instant vector, range vector, or string) at the top. Type discipline makes queries correct; cardinality awareness makes them fast.
Authoritative reference for writing PromQL queries — dashboards, alerts, recording rules, exploration. The companion
backend/prometheus skill covers instrumentation (metric types, naming, labels, exporters). When both apply, use
backend/prometheus for emitting metrics and this skill for querying them.
References
- Selectors and data types — [
${CLAUDE_SKILL_DIR}/references/selectors-and-types.md] Expression types, instant and range vector selectors, label matchers (=,!=,=~,!~), time durations, offset and@modifiers, staleness, instant vs range queries, string and float literals - Operators — [
${CLAUDE_SKILL_DIR}/references/operators.md] Arithmetic, comparison, logical/set, vector matching (on,ignoring,group_left,group_right), aggregation operators,by/without, fill modifiers, operator precedence - Functions — [
${CLAUDE_SKILL_DIR}/references/functions.md] Full function catalog: counter family, gauge functions, classic and native histograms,*_over_time, existence checks, label manipulation, math, time, type conversion, sorting, trigonometric - Native histograms — [
${CLAUDE_SKILL_DIR}/references/native-histograms.md] Native vs classic detection,histogram_quantileacross both forms, native-only functions (histogram_avg,histogram_count,histogram_sum,histogram_fraction,histogram_stddev,histogram_stdvar), aggregation withoutle, NHCB semantics, trim operators, migration patterns, function compatibility matrix, gotchas, annotations - Subqueries — [
${CLAUDE_SKILL_DIR}/references/subqueries.md] Syntax, resolution and alignment, nested subqueries, when to use subqueries vs recording rules, pitfalls - Optimization and pitfalls — [
${CLAUDE_SKILL_DIR}/references/optimization.md] Cardinality awareness, common pitfalls (rate-of-gauge, aggregate-then-rate, averaging ratios, averaging summary quantiles), counter resets, staleness, rate window sizing, native histograms, diagnostics - Recording and alerting rules — [
${CLAUDE_SKILL_DIR}/references/recording-alerting-rules.md] Rule file structure,level:metric:operationsnaming, ratio aggregation patterns, alert syntax,for/keep_firing_for, templating, alerting best practices, anti-patterns
What ships with it
8 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 · 481 lines · 74 tokens per session scan A a839f8a6229d
promql is a skill published in the GitHub repository xobotyi/cc-foundry (22 stars, last pushed 7d ago), licensed MIT. It adds 74 tokens to every session and 5,256 once invoked, about $0.0003 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 2026-08-30.
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