Analyzes application logs: classifies errors, checks log quality, maps stack traces to source. Use when logs need review after test runs or during development.
Scanned 9/4/2026
Install to Claude Code
npx -y skills add boisenoise/skills-collections --skill levn-ln-514-test-log-analyzer --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Levn Ln 514 Test Log Analyzer?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/boisenoise-levn-ln-514-test-log-analyzer)More formats (shields.io, HTML) on the badges page.
---
name: ln-514-test-log-analyzer
description: "Analyzes application logs: classifies errors, checks log quality, maps stack traces to source. Use when logs need review after test runs or during development."
license: MIT
model: claude-sonnet-4-6
---
> **Paths:** File paths (`shared/`, `references/`, `../ln-*`) are relative to skills repo root. If not found at CWD, locate this SKILL.md directory and go up one level for repo root. If `shared/` is missing, fetch files via WebFetch from `https://raw.githubusercontent.com/levnikolaevich/claude-code-skills/master/skills/{path}`.
# Test Log Analyzer
**Type:** L3 Worker
**Category:** 5XX Quality
Two-layer analysis of application logs. Node.js script handles collection and quantitative analysis; AI handles classification, quality assessment, and fix recommendations.
## Inputs
No required inputs. Runs in current project directory, auto-detects log sources.
Optional `args` — caller instructions (natural language): time window, expected errors, test context. Example: `"review logs for last 30min, auth 401 errors expected from negative tests"`.
## Purpose & Scope
- Analyze application logs (after test runs, during development, or on demand)
- Classify errors into 4 categories: Real Bug, Test Artifact, Expected Behavior, Operational Warning
- Assess log quality: noisiness, completeness, level correctness, format, structured logging
- Map stack traces to source files; provide fix recommendations
- Report findings for quality verdict (only Real Bugs block)
- **No status changes or task creation** — report only
## When to Use
- Analyze application logs in any project (default: last 1h)
- After test runs to classify errors and assess log quality
- Can be invoked with context instructions: `Skill(skill: "ln-514-test-log-analyzer", args: "review last 30min, 401 errors expected")`
## Workflow
### Phase 0: Parse Instructions
If `args` provided — extract: time window (default: 1h), expected errors list, test context.
If no `args` — use defaults (last 1h, no expected errors).
### Phase 1: Log Source Detection and Script Execution
Read target project files if they exist: `docs/project/infrastructure.md`, `docs/project/runbook.md`
1) Check if `scripts/analyze_test_logs.mjs` exists in target project. If missing, copy from `references/analyze_test_logs.mjs`.
2) Detect log source mode (auto-detection priority: docker → file → loki):
| Mode | Detection | Source |
|------|-----------|--------|
| `docker` | `docker compose ps` returns running containers | `docker compose logs --since {window}` |
| `file` | `.log` files exist, or `tests/manual/results/` has output | File paths from infrastructure.md or `*.log` glob |
| `loki` | `LOKI_URL` env var or `environment_state.json` observability section | Loki HTTP query_range API |
3) Run script: `node scripts/analyze_test_logs.mjs --mode {detected} [options]`
4) If no log sources found → return `NO_LOG_SOURCES` status, skip to Phase 5.
**Level-based error detection (CRITICAL):**
When constructing Loki queries or grep commands to scan for errors, ALWAYS filter by the **parsed level field**, NOT by text matching the word "error" in the full log line. Logger names like `uvicorn.error` contain "error" as part of the name but log at INFO level — text matching produces false positives.
| Log format | Correct error filter | Wrong filter |
|------------|---------------------|--------------|
| Pipe-delimited (`ts \| LEVEL \| ...`) | `\| ERROR` or `\| CRITICAL` (match level field position) | `grep -i error` (matches logger names) |
| Loki structured | `{service_name="X"} \| level="ERROR"` or `\| pattern` extraction | `{service_name="X"} \|= "error"` |
| Key=value (`level=ERROR msg=...`) | `level=ERROR` or `level=FATAL` | `\|~ "(?i)error"` |
| Docker logs (local) | `grep -E '\| ERROR \| \| CRITICAL '` | `grep -iE 'error\|exception'` |
The `analyze_test_logs.mjs` script handles this correctly via structured regex parsers. These rules apply to **ad-hoc Loki/grep queries** constructed during analysis.
### Phase 2: 4-Category Error Classification
Classify each error group from script JSON output:
| Category | Action | Criteria |
|----------|--------|----------|
| **Real Bug** | Fix | Unexpected crash, data loss, broken pipeline |
| **Test Artifact** | Skip | From test scripts, deliberate error-path validation |
| **Expected Behavior** | Skip | Rate limiting, input validation, auth failures from invalid tokens |
| **Operational Warning** | Monitor | Clock drift, resource pressure, temporary unavailability |
**Test artifact detection heuristics:**
- Test name contains: `invalid`, `error`, `fail`, `reject`, `unauthorized`, `forbidden`, `not_found`, `bad_request`, `timeout`
- Test asserts non-2xx status codes (4xx, 5xx)
- Test uses `pytest.raises`, `expect(...).rejects`, `assertThrows`, `should.throw`
- Errors correlate with test execution timestamps from regression test output
- Patterns matching `tests/manual/` scripts
**Error taxonomy per** `references/error_taxonomy.md` **(9 categories: CRASH, TIMEOUT, AUTH, DB, NETWORK, VALIDATION, CONFIG, RESOURCE, UNSUPPORTED_API).**
### Phase 3: Log Quality Assessment
**MANDATORY READ:** Load `references/error_taxonomy.md` (per-level criteria table + level correctness reference)
**Step 1: Detect configured log level.** Check in order:
1. `LOG_LEVEL` / `LOGLEVEL` env var (`.env`, `docker-compose.yml`, `infrastructure.md`)
2. Framework config: Python `logging.conf` / Django `LOGGING` / Node `LOG_LEVEL`
3. Default: assume `INFO` if not detected
Configured level determines WHICH levels appear in logs, but each level has its own noise threshold regardless.
**Step 2: Assess 6 quality dimensions:**
| Dimension | What to Check | Signal |
|-----------|---------------|--------|
| **Noisiness** | Per-level noise thresholds from `error_taxonomy.md` section 4: TRACE (zero in prod), DEBUG (>50% monopoly), INFO (>30%), WARNING (>1% of total), ERROR (>0.1% of total) | `NOISY: {level} template "{msg}" at {ratio}%` |
| **Completeness & Traceability** | Critical operations missing log entries + traceability gaps (see table below) | `MISSING: No log for {operation}` / `TRACEABILITY_GAP: {type} in {file}:{line}` |
| **Level correctness** | Per-level criteria from `error_taxonomy.md` section 4: content, anti-patterns, library rule | `WRONG_LEVEL: should be {level}` |
| **Structured logging** | Missing trace_id/request_id/user context; unstructured plaintext | `UNSTRUCTURED: lacks {field}` |
| **Sensitivity** | PII/secrets/tokens/passwords in log messages | `SENSITIVE: {type} exposure` |
| **Context richness** | Errors without actionable context (order_id, user_id, operation) | `LOW_CONTEXT: lacks context` |
**Traceability gap detection** — scan source code for operations without INFO-level logging:
| Operation Type | Expected Log | Where to Add |
|---------------|-------------|--------------|
| Incoming request handling | Request received + response status | Entry/exit of route handler |
| External API call | Request sent + response status + duration | Before/after HTTP client call |
| DB write (INSERT/UPDATE/DELETE) | Operation + affected entity + count | Before/after ORM/query call |
| Auth decision | Result (allow/deny) + reason | After auth check |
| State transition | Old state → new state + trigger | At transition point |
| Background job | Start + complete/fail + duration | Entry/exit of job handler |
| File/resource operation | Open/close + path + size | At I/O operation |
**Log Format Quality** (10-criterion checklist per `references/log_analysis_output_format.md`):
| # | Criterion | Check |
|---|-----------|-------|
| 1 | Dual format | JSON in prod, readable in dev |
| 2 | Timestamp | Consistent, timezone-aware |
| 3 | Level field | Present, uppercase |
| 4 | Trace/Correlation ID | Present in every entry, async-safe |
| 5 | Service name | Identifies source service |
| 6 | Source location | module:line + function |
| 7 | Extra context | Structured fields, not string interpolation |
| 8 | PII redaction | Passwords, API keys, emails handled |
| 9 | Noise suppression | Duplicate filters, third-party suppressed |
| 10 | Parseability | Dev: pipe-delimited; prod: valid JSON per line |
Score: passed criteria / 10.
### Phase 4: Stack Trace Mapping + Fix Recommendations
For each Real Bug:
1) Extract stack trace frames; identify origin frame (first frame in project code, not in node_modules/site-packages)
2) Map to source file:line
3) Generate fix recommendation: what to change, where, effort estimate (S/M/L)
**Prioritize using Sentry-inspired dimensions:**
- High-volume (occurrence count), Post-test regression (new errors), High-impact path (auth/payment/DB), Correlated traces (trace_id across services)
### Phase 5: Generate Report
**MANDATORY READ:** Load `references/log_analysis_output_format.md`
Output report to chat with header `## Test Log Analysis`. Include:
- Signals table (Real Bugs count, Test Artifacts filtered, Log Noise status, Log Format score, Log Quality score)
- Real Bugs table (priority, category, error, source, fix recommendation)
- Filtered table (category, count, examples)
- Log Quality Issues table (dimension, service, issue, recommendation)
- Noise Report table (count, ratio, service, level, template, action)
- Machine-readable block `<!-- LOG-ANALYSIS-DATA ... -->` for programmatic consumption
### Phase 6: Meta-Analysis
**MANDATORY READ:** Load `shared/references/meta_analysis_protocol.md`
Skill type: `execution-worker`. Run after all phases complete.
## Verdict Contribution
Quality coordinator normalization matrix component:
| Status | Maps To | Penalty |
|--------|---------|---------|
| CLEAN | -- | 0 |
| WARNINGS_ONLY | -- | 0 |
| REAL_BUGS_FOUND | FAIL | -20 |
| SKIPPED / NO_LOG_SOURCES | ignored | 0 |
Log quality/format issues are INFORMATIONAL — do not affect quality verdict. Only Real Bugs block.
## Critical Rules
- No status changes or task creation; report only.
- Test Artifacts and Expected Behavior are ALWAYS filtered — never count as bugs.
- Log quality issues are advisory — inform, don't block.
- Script must handle gracefully: no Docker, no log files, no Loki → `NO_LOG_SOURCES`.
- Language preservation in comments (EN/RU).
## Runtime Summary Artifact
**MANDATORY READ:** Load `shared/references/quality_summary_contract.md`, `shared/references/quality_worker_runtime_contract.md`
Runtime profile:
- family: `quality-worker`
- worker: `ln-514`
- summary kind: `quality-worker`
- payload fields used by coordinators: `worker`, `status`, `verdict`, `issues`, `warnings`, `artifact_path`
Invocation rules:
- standalone: omit `runId` and `summaryArtifactPath`
- managed: pass both `runId` and exact `summaryArtifactPath`
- always write the validated summary before terminal outcome
## Definition of Done
- [ ] Script deployed to target project `scripts/` (or already exists)
- [ ] Log source detected and script executed (or NO_LOG_SOURCES returned)
- [ ] Errors classified into 4 categories; Real Bugs identified
- [ ] Log quality assessed (6 dimensions + 10-criterion format checklist)
- [ ] Stack traces mapped to source files for Real Bugs
- [ ] Report output to chat with signals table + machine-readable block
## Reference Files
- **Error taxonomy:** `references/error_taxonomy.md`
- **Output format:** `references/log_analysis_output_format.md`
- **Analysis script:** `references/analyze_test_logs.mjs`
---
**Version:** 1.0.0
**Last Updated:** 2026-03-13
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!