promql-cli
CLI for querying Prometheus and PromQL-compatible engines (Thanos, Cortex, VictoriaMetrics, Grafana Mimir, Grafana Tempo...) — instant queries, range queries, metric discovery (metrics/labels/meta subcommands), output formats (table/csv/json/graph). Apply when executing PromQL queries, troubleshooting performance issues on a software having observability, investigating latency/error rates/saturation, or analyzing time series data.
git clone --depth 1 https://github.com/samber/cc-skills /tmp/promql-cli && cp -r /tmp/promql-cli/skills/promql-cli ~/.claude/skills/promql-cliSKILL.md
# promql-cli — Prometheus Query CLI Skill `promql-cli` (github.com/nalbury/promql-cli) is a Go CLI for querying, analyzing, and visualizing Prometheus metrics, plus PromQL fundamentals. ## Reference Files Read the relevant reference file(s) before executing tasks: | File | When to read | | --- | --- | | `references/installation.md` | User needs to install promql-cli or set up configuration (hosts, auth, token, password, multi-host) | | `references/usage.md` | User wants to discover metrics/exporters/labels, run queries, or choose output formats | | `references/graphing.md` | User wants to visualize Prometheus data as an ASCII chart in the terminal | | `references/debugging.md` | User is investigating a performance issue, latency, errors, or saturation | | `references/promql-reference.md` | User needs help writing PromQL, understanding metric types, functions, or aggregations | For most tasks, read `references/usage.md`. For PromQL help, read `references/promql-reference.md`. When debugging, read both `references/debugging.md` and `references/promql-reference.md`. ## Setup Check Before running any query, verify that a host is configured: ```bash promql 'up' # succeeds if host is reachable; fails with connection error if not configured # or promql --host xxx 'up' ``` Recognize these errors as a configuration/auth problem and refer to `references/installation.md`: | Error | Cause | | --- | --- | | `dial tcp ... connection refused` | No host running at the configured address | | `dial tcp ... no such host` | Hostname not resolved — wrong host in config | | `error querying prometheus: ...401...` | Bearer token missing or invalid | | `error querying prometheus: ...403...` | Token valid but insufficient permissions | | `please specify an authentication type` | Auth flags partially set — use config file instead | If any of these appear, **do not create config files on behalf of the user** — config files may contain credentials (tokens, passwords) that must never pass through an LLM. Instead, guide the user to set it up themselves: > "Please create `~/.promql-cli.yaml` manually with your Prometheus host (and credentials if needed). See `references/installation.md` for the exact format. Let me know once it's ready." Only after the user confirms the config is in place should you proceed with queries. ## Quick Command Reference ```bash promql 'up' # instant query promql 'rate(http_requests_total[5m])' --start 1h # range query (ASCII graph) promql 'up' --output csv # CSV output promql 'up' --output json # JSON output promql metrics # list all metric names promql labels <metric> # list labels for a metric promql meta <metric> # show metric type and help promql --config ~/.promql-cli-prod.yaml 'up' # target a specific host ``` ## Key Principles 1. **Use `rate()` on counters, never raw values** — raw counters only ever increase; the absolute value is meaningless. `rate()` gives the per-second change rate, which is what you actually care about. 2. **When debugging, isolate a single instance** — aggregating across replicas masks per-instance anomalies. A single overloaded pod hidden behind healthy peers won't show up in averages. 3. **Filter early with label matchers in the innermost selector** — Prometheus evaluates selectors before functions, so filtering late means scanning all time series. Early filters reduce data scanned and query latency. 4. **For histograms, keep `le` in the `by` clause** before `histogram_quantile()` — the function needs all `le` buckets to interpolate percentiles; dropping `le` early produces `NaN` or wrong results. 5. **Prefer `--output graph` for range queries** — ASCII sparklines convey trend direction (rising, falling, spiking) in a compact format that LLMs parse well; raw timestamp tables require mental modeling. 6. **Store credentials in `~/.promql-cli.yaml` and `~/.promql_token`, chmod 600** — passing tokens as CLI args exposes them in shell history and process listings. This skill is not exhaustive. Please refer to the [official promql-cli documentation](https://github.com/nalbury/promql-cli) and examples for up-to-date information. Context7 can help as a discoverability platform. If you encounter a bug or unexpected behavior in promql-cli itself, open an issue at [https://github.com/nalbury/promql-cli/issues](https://github.com/nalbury/promql-cli/issues).
Comprehensive guide for building Chrome extensions with Manifest V3. Use this skill whenever the user mentions Chrome extension, browser extension, manifest.json, content script, service worker (in extension context), popup, side panel, chrome.runtime, chrome.tabs, chrome.storage, chrome.scripting, background script, MV3, Manifest V3, or any Chrome extension API. Also trigger when the user wants to inject scripts into web pages, communicate between page and background, bypass CSP from a content script, build an RPC layer over chrome messaging, or publish to the Chrome Web Store. Covers both new extension projects and adding features to existing ones. Do NOT use for framework-specific questions.
Conventional Commits v1.0.0 branch naming, worktree naming, and commit message standards for GitHub and GitLab projects. Use when creating branches, naming worktrees, writing commits, generating commit messages, reviewing branch conventions, or setting up changelog automation. Apply when your project needs consistent git history, SemVer-driven releases, parseable changelog generation, or automatic issue closing. Trigger when the user asks how to name a worktree, create a git worktree, or organize worktrees alongside branches.
Design end-of-article CTAs (calls-to-action placed at the bottom of blog posts, newsletters, essays, articles, or any long-form content). Use this skill whenever the user asks to write, design, review, or improve a CTA at the bottom of an article, blog post, or essay; mentions "end-of-post CTA", "bottom of the article", "call-to-action", "signup box", "newsletter CTA", "subscribe block", "what should I put at the bottom", "how do I get readers to subscribe / share / book a call / buy / follow / join / download"; or asks how to convert article readers into subscribers, leads, customers, community members, or supporters. Also trigger when the user wants A/B testing guidance or accessibility review for a CTA block. Covers independent / personal writing, newsletter publications, and brand / content-marketing blogs across any topic — tech, finance, food, climate, design, lifestyle, B2B, B2C. Produces both the copy (content) and the structural / visual design (form), matched to the user's objective and audience.
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Codifies how someone or a brand writes — prose mechanics (lexicon, syntax, rhythm, structure, signature moves) independent of emotional tone. Output: PROSE.md. Three modes: BUILD a fresh guide from SOUL.md + TONE.md + discovery interview; ADAPT an existing guide to a new channel; AUDIT a corpus for prose patterns before codification. Use when: writing rules for a content factory, codifying ghostwriting voice for multi-writer consistency, defining banned words and sentence-length targets, building a house style guide, reverse-engineering prose from a corpus, porting style across channels. Trigger on: PROSE.md, writing style guide, prose guide, house style, ghostwriter style, writing playbook, brand writing mechanics, signature moves. NOT for: writing actual content (→ linkedin-ghostwriting, technical-article-writer, press-release-writer), removing AI patterns (→ humanizer), tone decisions (→ copywriting-tone-of-voice), hooks (→ copywriting-hooks), CTAs (→ copywriting-cta).
Build a brand tone of voice guide (TONE.md) via discovery, voice definition, and channel modulation. Outputs voice attributes with do's/don'ts, NN/g positioning, tone modulation matrix, lexicon, mechanics, and channel rules — consumed by downstream content skills writing on-brand copy. Covers B2B SaaS, B2C/D2C, NGO, public sector, consulting, industrial, product-led, personal, and volunteering brands; researches uncovered contexts (politics, regulated niches, religious orgs, gaming) on demand. Also adapts an existing TONE.md to a new channel (blog → LinkedIn, web → Twitter/X, in-product UI). Optionally consumes SOUL.md to pre-fill brand identity. Apply when the user wants to create a TONE.md, define brand voice, port voice to a new channel, refresh an outdated voice, or set up a content factory writing across many supports. Not for writing individual posts, articles, emails, or UI strings (→ dedicated writing skills), nor SOUL.md, PROSE.md, DESIGN.md.
CRXJS Chrome extension development — true HMR for popup, options, content scripts, side panels, manifest-driven builds, dynamic content script imports (`?script`, `?script&module`), and `defineManifest` for type-safe manifests. Uses Vite as its build tool. Use when the user mentions CRXJS, crxjs, @crxjs/vite-plugin, 'extension with hot reload', 'HMR for chrome extension', or wants to set up a CRXJS-based Chrome extension project with any framework (React, Vue, Svelte, Solid, Vanilla). Also trigger when the user has an existing CRXJS project and wants to add features, fix HMR issues, or configure content scripts with CRXJS. For general Chrome extension architecture (messaging, CSP, storage, permissions) -> See `samber/cc-skills@chrome-extension` skill.
Deep research skill — broad parallel web searches, multi-source validation, confidence tracking, cited Markdown report. Supports 11 research types: market (TAM/SAM, segments, pricing, trends), domain (industry structure, ecosystem, regulatory landscape), technical (architecture, tools, benchmarks), competitive (competitor teardown, positioning, win/loss), product (feature analysis, reviews, roadmap signals), academic (literature survey, citation networks, key authors), person/org (due diligence on a company or public figure), financial (funding rounds, valuation multiples, revenue signals), legal (IP, patents, litigation, compliance), trend (emerging signals, foresight, scenario mapping), community (ecosystem health, key voices, governance, fragmentation). Use when asked to: 'research <topic>', 'deep dive on X', 'analyze the landscape', 'competitive analysis', 'compare these options', 'who are the players in Z', 'literature review', 'background on Y', 'what papers exist on X', 'product teardown', 'technology evaluation', 'regulatory overview', 'funding landscape', 'what trends are emerging in X', 'patent landscape', 'community health', or any request requiring scanning many sources and producing a cited written analysis. Apply whenever the deliverable is a thorough, sourced report rather than a quick answer. Trigger even when phrased casually: 'look into X', 'what's the deal with Y', 'dig into Z', 'I need to understand the space', 'catch me up on X'.