logql-generator — скилл для Claude Code: что делает и как установить

---
name: logql-generator
description: Generate LogQL queries, log stream selectors, metric queries, and alerting rules for Grafana Loki.
---

# LogQL Query Generator

## Overview

Interactive workflow for generating production-ready LogQL queries. LogQL is Grafana Loki's query language with indexed label selection, line filtering, parsing, and metric aggregation.

## Trigger Hints

- "Write a LogQL query for error rate by service."
- "Help me build a Loki alert query."
- "Convert this troubleshooting requirement into LogQL."
- "I need step-by-step LogQL query construction."

Use this skill for query generation, dashboard queries, alerting expressions, and troubleshooting with Loki logs.

## Execution Flow (Deterministic)

Always run stages in order. Do not skip required stages.

### Stage 1 (Required): Capture Intent

Use `AskUserQuestion` to collect goal and use case.

Template:
- "What is your primary goal: debugging, alerting, dashboard metric, or investigation?"
- "Do you need a log query (raw lines) or a metric query (numeric output)?"
- "What time window should this cover (example: last 15m, 1h, 24h)?"

Fallback if `AskUserQuestion` is unavailable:
- Ask the same questions in plain text and continue.

### Stage 2 (Required): Capture Log Source Details

Collect:
1. Labels for stream selectors (`job`, `namespace`, `app`, `service_name`, `cluster`)
2. Log format (JSON, logfmt, plain text, mixed)
3. Known fields to filter/aggregate (`status`, `level`, `duration`, `path`, `trace_id`)

Ambiguity and partial-answer handling:
1. If a required field is missing, ask one focused follow-up question.
2. If still missing, proceed with explicit assumptions.
3. Prefix assumptions with `Assumptions:` in the output so the user can correct them quickly.

### Stage 3 (Required): Discover Loki and Grafana Versions

Collect or infer:
- Loki version (example: `2.9.x`, `3.0+`, unknown)
- Grafana version (example: `10.x`, `11.x`, unknown)
- Deployment context (self-hosted Loki, Grafana Cloud, unknown)

Version compatibility policy:
1. If versions are known, use the newest compatible syntax only.
2. If versions are unknown, use compatibility-first syntax and avoid 3.x-only features by default.
3. For unknown versions, provide an optional "3.x optimized variant" separately.

Avoid by default when version is unknown:
- Pattern match operators `|>` and `!>`
- `approx_topk`
- Structured metadata specific behavior (`detected_level`, accelerated metadata filtering assumptions)

### Stage 4 (Required): Plan Confirmation and Output Mode

Present a plain-English plan, then ask the user to choose output mode.

Plan template:
```text
LogQL Query Plan
Goal: <goal>
Query type: <log or metric>
Streams: <selector>
Filters/parsing: <filters + parser>
Aggregation window: <function and [range]>
Compatibility mode: <version-aware or compatibility-first>
```

Mode selection template:
- "Do you want `final query only` (default) or `incremental build` (step-by-step)?"

If user does not choose, default to `final query only`.

### Stage 5 (Conditional, Blocking): Reference Checkpoint for Complex Queries

Complex query triggers:
- Nested aggregations (`topk(sum by(...))`, multiple `sum by`, percentiles)
- Performance-sensitive queries (high volume streams, long ranges)
- Alerting expressions
- Template functions (`line_format`, `label_format`)
- Regex-heavy extraction, IP matching, pattern parsing
- Loki 3.x feature usage

Blocking checkpoint rule:
1. Read relevant files before generation using explicit file-open/read actions.
2. Minimum file set:
   - `examples/common_queries.logql` for syntax and query patterns
   - `references/best_practices.md` for performance and alerting guidance
3. Do not generate the final query until this checkpoint is complete.

Fallback when file-read tools are unavailable:
1. State that reference files could not be read in this environment.
2. Generate a conservative query (compatibility-first, simpler operators).
3. Mark result as `Unverified against local references`.

### Stage 6 (Conditional): External Docs Lookup Policy (Context7 Before WebSearch)

Use external lookup only for version-specific behavior, unclear syntax, or advanced features not covered in local references.

Decision order:
1. Context7 first:
   - `mcp__context7__resolve-library-id` with `libraryName="grafana loki"`
   - `mcp__context7__query-docs` for the exact topic
2. WebSearch second (fallback only) when:
   - Context7 is unavailable
   - Context7 does not provide required version-specific detail
   - You need latest release/deprecation confirmation

WebSearch fallback constraints:
- Prefer official Grafana/Loki docs and release notes.
- Note which statement came from fallback search.

### Stage 7 (Required): Generate Query

#### Stage 7A (Default): Final Query Only

Return one production-ready query plus short explanation.

#### Stage 7B (Optional): Incremental Build Mode

Use this when requested or when debugging complex pipelines.

Step-by-step template:
1. Stream selector
2. Line filter
3. Parser
4. Parsed-field filter
5. Aggregation/window

### Stage 8 (Required): Deliver Usage and Checks

Always include:
1. Final query or incremental sequence
2. How to run it (Grafana Explore/panel or `logcli`)
3. Tunables (labels, thresholds, range)
4. Any assumptions and compatibility notes

## AskUserQuestion Templates

### Intake Template
- "What system/service should this query target?"
- "Which labels are reliable for stream selection?"
- "What defines a match (error text, status code, latency threshold, user path)?"
- "Should output be raw logs or a metric for alert/dashboard?"

### Version Template
- "What Loki version are you running?"
- "What Grafana version are you using?"
- "If unknown, should I generate a compatibility-first query and add an optional 3.x variant?"

### Ambiguity Follow-up Template
- "I am missing `<field>`. Should I assume `<default>` so I can continue?"

## Core Patterns

### Stream Selection and Filtering
```logql
{job="app"} |= "error" |= "timeout"
{job="app"} |~ "error|fatal|critical"
{job="app"} != "debug"
```

### Parsing
```logql
{app="api"} | json | level="error" | status_code >= 500
{app="api"} | logfmt | caller="database.go"
{job="nginx"} | pattern "<ip> - - [<_>] \"<method> <path>\" <status> <size>"
```

### Metric Aggregation
```logql
rate({job="app"} | json | level="error" [5m])
sum by (app) (count_over_time({namespace="prod"} | json [5m]))
sum(rate({app="api"} | json | level="error" [5m])) / sum(rate({app="api"}[5m])) * 100
quantile_over_time(0.95, {app="api"} | json | unwrap duration [5m])
topk(10, sum by (error_type) (count_over_time({job="app"} | json | level="error" [1h])))
```

### Formatting and IP Matching
```logql
{job="app"} | json | line_format "{{.level}}: {{.message}}"
{job="app"} | json | label_format env=`{{.environment}}`
{job="nginx"} | logfmt | remote_addr = ip("192.168.4.0/24")
```

## Query Construction Rules

1. Use specific stream selectors (indexed labels first).
2. Prefer filter order: line filter -> parse -> parsed-field filter.
3. Prefer parser cost order: `pattern` > `logfmt` > `json` > `regexp`.
4. For unknown Loki version, stay on compatibility-first syntax.
5. For complex/critical queries, complete Stage 5 checkpoint before final output.

## Advanced Techniques

### Multiple Parsers
```logql
{app="api"} | json | regexp "user_(?P<user_id>\\d+)"
```

### Unwrap for Numeric Metrics
```logql
sum(sum_over_time({app="api"} | json | unwrap duration [5m]))
```

### Pattern Match Operators (Loki 3.0+, 10x faster than regex)
```logql
{service_name=`app`} |> "<_> level=debug <_>"
```

### Logical Operators
```logql
{app="api"} | json | (status_code >= 400 and status_code < 500) or level="error"
```

### Offset Modifier
```logql
sum(rate({app="api"} | json | level="error" [5m])) - sum(rate({app="api"} | json | level="error" [5m] offset 1d))
```

### Label Operations
```logql
{app="api"} | json | keep namespace, pod, level
{app="api"} | json | drop pod, instance
```

> **Note**: LogQL has no `dedup` or `distinct` operators. Use metric aggregations like `sum by (field)` for programmatic deduplication.

## Loki 3.x Key Features

### Structured Metadata
High-cardinality data without indexing (trace_id, user_id, request_id):
```logql
# Filter AFTER stream selector, NOT in it
{app="api"} | trace_id="abc123" | json | level="error"
```

### Query Acceleration (Bloom Filters)
Place structured metadata filters BEFORE parsers:
```logql
# ACCELERATED
{cluster="prod"} | detected_level="error" | logfmt | json
# NOT ACCELERATED
{cluster="prod"} | logfmt | json | detected_level="error"
```

### approx_topk (Probabilistic)
```logql
approx_topk(10, sum by (endpoint) (rate({app="api"}[5m])))
```

### vector() for Alerting
```logql
sum(count_over_time({app="api"} | json | level="error" [5m])) or vector(0)
```

### Automatic Labels
- **service_name**: Auto-populated from container name
- **detected_level**: Auto-detected when `discover_log_levels: true` (stored as structured metadata)

## Function Reference

### Log Range Aggregations
| Function | Description |
|----------|-------------|
| `rate(log-range)` | Entries per second |
| `count_over_time(log-range)` | Count entries |
| `bytes_rate(log-range)` | Bytes per second |
| `bytes_over_time(log-range)` | Total bytes in time range |
| `absent_over_time(log-range)` | Returns 1 if no logs |

Rule:
- Use `bytes_over_time(<log-range>)` for raw log-byte volume.
- Use `| unwrap bytes(field)` with unwrapped range aggregations for numeric byte fields extracted from log content.

### Unwrapped Range Aggregations
| Function | Description |
|----------|-------------|
| `sum_over_time`, `avg_over_time`, `max_over_time`, `min_over_time` | Aggregate numeric values |
| `quantile_over_time(φ, range)` | φ-quantile (0 ≤ φ ≤ 1) |
| `first_over_time`, `last_over_time` | First/last value in interval |
| `stddev_over_time` | Population standard deviation of unwrapped values |
| `stdvar_over_time` | Population variance of unwrapped values |
| `rate_counter` | Per-second rate treating values as a monotonically increasing counter |

### Aggregation Operators
`sum`, `avg`, `min`, `max`, `count`, `stddev`, `topk`, `bottomk`, `approx_topk`, `sort`, `sort_desc`

With grouping: `sum by (label1, label2)` or `sum without (label1)`

### Conversion Functions
| Function | Description |
|----------|-------------|
| `duration_seconds(label)` | Convert duration string |
| `bytes(label)` | Convert byte string (KB, MB) |

### label_replace()
```logql
label_replace(rate({job="api"} |= "err" [1m]), "foo", "$1", "service", "(.*):.*")
```

## Parser Reference

### logfmt
```logql
| logfmt [--strict] [--keep-empty]
```
- `--strict`: Error on malformed entries
- `--keep-empty`: Keep standalone keys

### JSON
```logql
| json                                           # All fields
| json method="request.method", status="response.status"  # Specific fields
| json servers[0], headers="request.headers[\"User-Agent\"]"  # Nested/array
```

### pattern
```logql
| pattern "<ip> - - [<timestamp>] \"<method> <path> <_>\" <status> <size>"
```
Named placeholders become extracted labels; `<_>` discards a field.

### regexp
```logql
| regexp "(?P<level>\\w+): (?P<message>.+)"
```
Uses named capture groups (`?P<name>`). Slower than `pattern`/`logfmt`/`json`.

### decolorize
```logql
| decolorize
```
Strips ANSI color escape codes. Apply before parsing when logs come from terminal output.

### unpack
```logql
| unpack
```
Unpacks log entries that were packed by Promtail's `pack` pipeline stage. Restores the original log line and any embedded labels.

## Template Functions

Common functions for `line_format` and `label_format`:

**String**: `trim`, `upper`, `lower`, `replace`, `trunc`, `substr`, `printf`, `contains`, `hasPrefix`
**Math**: `add`, `sub`, `mul`, `div`, `addf`, `subf`, `floor`, `ceil`, `round`
**Date**: `date`, `now`, `unixEpoch`, `toDate`, `duration_seconds`
**Regex**: `regexReplaceAll`, `count`
**Other**: `fromJson`, `default`, `int`, `float64`, `__line__`, `__timestamp__`

See `examples/common_queries.logql` for detailed usage.

## Alerting Rules

```logql
# Alert when error rate exceeds 5%
(sum(rate({app="api"} | json | level="error" [5m])) / sum(rate({app="api"}[5m]))) > 0.05

# With vector() to avoid "no data"
sum(rate({app="api"} | json | level="error" [5m])) or vector(0) > 10
```

## Error Handling

| Issue | Solution |
|-------|----------|
| No results | Check labels exist, verify time range, test stream selector alone |
| Query slow | Use specific selectors, filter before parsing, reduce time range |
| Parse errors | Verify log format matches parser, test JSON validity |
| High cardinality | Use line filters not label filters for unique values, aggregate |

## Documentation Lookup

Use Stage 6 policy. Trigger external docs for:

| Trigger | Topic to Search | Tool to Use |
|---------|-----------------|-------------|
| User mentions Loki 3.x features | `structured metadata`, `bloom filters`, `detected_level` | Context7 first |
| `approx_topk` function needed | `approx_topk probabilistic` | Context7 first |
| Pattern match operators (`\|>`, `!>`) | `pattern match operator` | Context7 first |
| `vector()` function for alerting | `vector function alerting` | Context7 first |
| Recording rules configuration | `recording rules loki` | Context7 first |
| Unclear syntax or edge cases | Specific function/operator | Context7 first |
| Version-specific behavior questions | Version + feature | WebSearch fallback |
| Grafana Alloy integration | `grafana alloy loki` | WebSearch fallback |

## Resources

- `examples/common_queries.logql`: Query patterns, template function examples
- `references/best_practices.md`: Optimization, anti-patterns, alerting guidance

## Example Flows

### Example A: Final Query Only (Default)
1. User asks for 5xx rate by service over 15m.
2. Capture labels and format (`json`).
3. Confirm version and mode (`final query only`).
4. Generate one query:
```logql
sum by (service) (rate({namespace="prod", app="api"} | json | status_code >= 500 [15m]))
```

### Example B: Incremental Build (Optional)
1. User asks to debug login failures and requests step-by-step mode.
2. Provide staged build:
```logql
{app="auth"}
{app="auth"} |= "login failed"
{app="auth"} |= "login failed" | json
sum(count_over_time({app="auth"} |= "login failed" | json [5m]))
```
3. Explain where to stop if any step returns zero results.

## Done Criteria

Mark task done only when all checks pass:
1. Required stages (1, 2, 3, 4, 7, 8) were completed.
2. Stage 5 checkpoint was completed for any complex query.
3. Stage 6 lookup order followed Context7 before WebSearch when external docs were needed.
4. Output mode was explicitly selected or defaulted (`final query only`).
5. Loki/Grafana compatibility assumptions were stated when versions were unknown.
6. Final output includes query text, usage note, tunables, and assumptions.

## Version Notes

- **Loki 3.0+**: Bloom filters, structured metadata, pattern match operators (`|>`, `!>`)
- **Loki 3.3+**: `approx_topk` function
- **Loki 3.5+**: Promtail deprecated (use Grafana Alloy)
- **Loki 3.6+**: Horizontally scalable compactor, Loki UI as Grafana plugin

> **Deprecations**: Promtail (use Alloy), BoltDB store (use TSDB with v13 schema)