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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 qu
Vue d’ensemble
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.
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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, saturation, data gaps, or query cost issues |
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:
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.yamlmanually with your Prometheus host (and credentials if needed). Seereferences/installation.mdfor 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
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
- 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. - 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.
- 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.
- For histograms, keep
lein thebyclause beforehistogram_quantile()— the function needs alllebuckets to interpolate percentiles; droppingleearly producesNaNor wrong results. - Prefer
--output graphfor range queries — ASCII sparklines convey trend direction (rising, falling, spiking) in a compact format that LLMs parse well; raw timestamp tables require mental modeling. Never send thousands of raw JSON/CSV rows into the LLM context — use--output graphinstead, or run--output graphfirst and--output tableonly to inspect a narrow window. - Store credentials in
~/.promql-cli.yamland~/.promql_token, chmod 600 — passing tokens as CLI args exposes them in shell history and process listings.
Query Cost Rules
Always apply these before and during any query session:
- Always use the promql CLI — never call the Prometheus HTTP API from Python scripts or shell
curl. The CLI handles auth, formatting, and output consistently; Python API calls bypass all of that and produce raw JSON that must be parsed, inflating context and masking the graph output that models interpret best. - Check cardinality first — before querying an unfamiliar metric, count its time series (
count(metric_name)). High-cardinality metrics without label filters time out or flood the output. Seereferences/debugging.mdfor patterns. - Confirm the time window upfront — always ask before running range queries. Large intervals are expensive; prefer multiple short-interval queries over one long one.
- Clarify past vs. recent — for new investigations, ask whether the user wants a past event (specific timestamp) or a recent trend. If recent, offer concrete choices: last hour, last day, last week, last month.
- Aggregate in Prometheus — never pull raw series to aggregate in Python or shell. Push
sum by(...),avg by(...), ortopk()into the PromQL expression — Prometheus collapses series server-side. - Timeout = query too broad — if a query takes >15s, reduce scope: add label filters, shorten
--start, or add an aggregation wrapper. Apply the same narrowed scope to all subsequent queries in the session. - Data gaps → check
up— when a metric shows missing data, runup{job="...", instance="..."}before diagnosing the application. A0value confirms the exporter was down. Seereferences/debugging.md.
This skill is not exhaustive. Please refer to the official promql-cli documentation 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.
Métadonnées du fichier
name: promql-cli
description: 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.
license: MIT
compatibility: Requires promql-cli and jq
user-invocable: true
metadata:
author: samber
version: "1.2.0"
openclaw:
emoji: "📊"
homepage: https://github.com/samber/cc-skills
install:
- kind: go
package: github.com/nalbury/promql-cli
bins: [promql]
- kind: brew
formula: jq
bins: [jq]
requires:
bins:
- promql
- jq
skill-library-version: "0.3.0"
allowed-tools: Read Edit Write Glob Grep Agent Bash(promql:*) mcp__context7__resolve-library-id mcp__context7__query-docs AskUserQuestionVoir le texte original
---
name: promql-cli
description: 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.
license: MIT
compatibility: Requires promql-cli and jq
user-invocable: true
metadata:
author: samber
version: "1.2.0"
openclaw:
emoji: "📊"
homepage: https://github.com/samber/cc-skills
install:
- kind: go
package: github.com/nalbury/promql-cli
bins: [promql]
- kind: brew
formula: jq
bins: [jq]
requires:
bins:
- promql
- jq
skill-library-version: "0.3.0"
allowed-tools: Read Edit Write Glob Grep Agent Bash(promql:*) mcp__context7__resolve-library-id mcp__context7__query-docs AskUserQuestion
---
# 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, saturation, data gaps, or query cost issues |
| `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. Never send thousands of raw JSON/CSV rows into the LLM context — use `--output graph` instead, or run `--output graph` first and `--output table` only to inspect a narrow window.
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.
## Query Cost Rules
Always apply these before and during any query session:
0. **Always use the promql CLI** — never call the Prometheus HTTP API from Python scripts or shell `curl`. The CLI handles auth, formatting, and output consistently; Python API calls bypass all of that and produce raw JSON that must be parsed, inflating context and masking the graph output that models interpret best.
1. **Check cardinality first** — before querying an unfamiliar metric, count its time series (`count(metric_name)`). High-cardinality metrics without label filters time out or flood the output. See `references/debugging.md` for patterns.
2. **Confirm the time window upfront** — always ask before running range queries. Large intervals are expensive; prefer multiple short-interval queries over one long one.
3. **Clarify past vs. recent** — for new investigations, ask whether the user wants a past event (specific timestamp) or a recent trend. If recent, offer concrete choices: last hour, last day, last week, last month.
4. **Aggregate in Prometheus** — never pull raw series to aggregate in Python or shell. Push `sum by(...)`, `avg by(...)`, or `topk()` into the PromQL expression — Prometheus collapses series server-side.
5. **Timeout = query too broad** — if a query takes >15s, reduce scope: add label filters, shorten `--start`, or add an aggregation wrapper. Apply the same narrowed scope to all subsequent queries in the session.
6. **Data gaps → check `up`** — when a metric shows missing data, run `up{job="...", instance="..."}` before diagnosing the application. A `0` value confirms the exporter was down. See `references/debugging.md`.
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).
Examiner la source
Prix et coûts d’utilisation
- Obtenir le skill
- Prix non confirmé
- L’utiliser
- Prérequis non confirmés. Consultez les frais d’agent, d’API et de services à la source.
- Licence
- MIT
- Prix non confirmé
- Le prix n’est pas confirmé. Les liens existants vers les sources et l’installation restent disponibles.
Gratuit à obtenir ne signifie pas gratuit à utiliser. Le prix ne constitue pas une évaluation de sécurité. Soumettre un prix →
Source du skill enregistrée
Un chemin vers les instructions est enregistré. Cela ne constitue pas un test, une garantie de sécurité ou de compatibilité.
Réviser avant installation: Éviter l’installation automatique
Licence: MIT
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- No Windows support mentioned in installation instructions (only macOS/Linux).
- The skill description mentions 'promql-cli' but the actual binary is 'promql' — minor naming inconsistency.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Stars/forks activity: 203 stars, 15 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
Les outils sont des indications de métadonnées, pas une compatibilité testée. Les prompts sont des suggestions.
Commencer par une petite tâche
- 1Lisez la source et confirmez entrées, résultats, dépendances et permissions.
- 2Demandez un plan à l’agent. Approuvez la configuration et les coûts avant un test isolé.
- 3Vérifiez résultats et fichiers modifiés. Signalez uniquement ce qui a été exécuté et conservez la révision source.
Vérifiez les dépendances, clés API et frais externes dans la source. Un dépôt public ne rend pas tous les services gratuits.
Source et conseils d’utilisation
Métadonnées et examens sont indicatifs. Popularité, découverte et exécution réussie sont des faits distincts.
- Dépôt source
- samber/cc-skills
- Licence
- MIT
- Version
- 1.0.0
- Dernier push GitHub
- 5 sept. 2026
- Registre mis à jour
- 6 sept. 2026
- Chemin des instructions
- skills/promql-cli/SKILL.md @ aece46382ba7
Version déclarée dans le registre ; vérifiez les versions de la source.
Qualité
67/100
Prometteur
Confiance
57/100
Do not auto-install
Audit
73/100
Revue nécessaire
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- No Windows support mentioned in installation instructions (only macOS/Linux).
- The skill description mentions 'promql-cli' but the actual binary is 'promql' — minor naming inconsistency.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Stars/forks activity: 203 stars, 15 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- Verified installs
- —
- Résultats
- —
Copier ne signifie pas installer. Les compteurs nécessitent un rapport de réussite et ne garantissent pas la qualité globale.
Accès agent
L’API Registry fournit les signaux de décision, confiance, audit, cas d’usage et installation sans analyser l’interface.
Plus de détails
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"score": 73,
"risk_level": "needs_review",
"risk_label": "Needs review",
"warnings": [
"Dependency or permission surface needs review",
"Permission surface may require sandboxing",
"No Windows support mentioned in installation instructions (only macOS/Linux).",
"The skill description mentions 'promql-cli' but the actual binary is 'promql' — minor naming inconsistency.",
"Quality score needs review",
"Permission surface needs review: secrets or environment access, shell or command execution",
"Stars/forks activity: 203 stars, 15 forks; issue activity unavailable in current metadata",
"Dependency/runtime risk: command execution surface, credential or environment access"
]
},
"safety_gate": {
"tier": "blocked",
"label": "Blocked for auto-install",
"auto_install_policy": "block",
"auto_install_allowed": false,
"human_review_required": true,
"blocked": true,
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
},
"quality": {
"score": 67,
"label": "Promising"
},
"supply": {
"track": "Data, BI, and analytics",
"scenario": "Data analysis",
"maintenance": "1mo since push",
"risk": "Needs review"
},
"alternative_skills": [],
"do_not_use_when": [
"teams that need a vendor-supported SLA",
"production agents without a repository review",
"No Windows support mentioned in installation instructions (only macOS/Linux).",
"High-risk permission hints: Shell or command execution, Secrets or environment access",
"Dependency or permission surface needs review",
"Permission surface may require sandboxing",
"The skill description mentions 'promql-cli' but the actual binary is 'promql' — minor naming inconsistency.",
"Quality score needs review"
],
"agent_contract": {
"task_input": "Use promql-cli in an agent workflow",
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
"install_policy": "block",
"minimum_review_before_use": [
"Trust: 65/100 Manual review",
"Audit: 73/100 Needs review",
"Safety: 29/100 Avoid automatic install",
"Review repository, license, install command, and permission surface before production use."
],
"expected_agent_output": {
"selected_skill": "samber-promql-cli (promql-cli)",
"install_command": "npx skills add samber/cc-skills --skill promql-cli",
"risk_summary": "Needs review; Blocked for auto-install; Review before production",
"verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
}
},
"outcome_feedback": {
"endpoint": "https://www.openagentskill.com/api/agent/outcome",
"method": "POST",
"requires_resolve_event_id": true,
"event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
"expected_outcomes": [
"success",
"failed",
"not_relevant",
"blocked_by_risk",
"setup_required"
],
"payload_template": {
"event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
"skill_slug": "samber-promql-cli",
"task": "Use promql-cli in an agent workflow",
"agent": "codex",
"outcome": "success",
"install_used": true,
"risk_blocked": false,
"setup_required": false,
"task_success": true,
"output_quality": 4,
"error_type": null,
"human_review_required": false,
"workspace": "sandbox",
"time_to_useful_ms": 120000,
"notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
}
},
"endpoints": {
"web": "https://www.openagentskill.com/skills/samber-promql-cli",
"api": "https://www.openagentskill.com/api/agent/skills/samber-promql-cli",
"audit": "https://www.openagentskill.com/skills/samber-promql-cli/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=samber-promql-cli&task=Use%20promql-cli%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20promql-cli%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20promql-cli%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/samber-promql-cli/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/samber-promql-cli"
}
}Pour le créateur
Source de la fiche
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- samber
- Source
- samber/cc-skills
- Indexé par
- Index communautaire OpenAgentSkill
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