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Analyze Php Logs

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dykyi-roman
analyze-php-logs

Parses and analyzes PHP application logs in PSR-3/Monolog, Laravel, Symfony, and plain error_log formats. Extracts exceptions, stack traces, request context, error frequency, and correlates related errors.

Overview

Publisherdykyi-roman
Repositoryawesome-claude-code
Skill nameanalyze-php-logs
Stars
98
Forks
25
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by dykyi-roman on GitHub. Read the source before you install it.

Installation

Install the Analyze Php Logs AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/dykyi-roman/awesome-claude-code.git /tmp/awesome-claude-code
mkdir -p .claude/skills
cp -r /tmp/awesome-claude-code/skills/analyze-php-logs .claude/skills/analyze-php-logs
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Analyze Php Logs in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Analyze Php Logs on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Analyze Php Logs is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

PHP Log Analyzer

Parses PHP application logs across multiple formats, extracts structured data, identifies error patterns, and correlates related issues.

Supported Log Formats

1. PSR-3 / Monolog (JSON)

json
{"message":"Connection refused","context":{"exception":"PDOException","file":"/app/src/Infrastructure/Repository/OrderRepository.php","line":45,"trace":"..."},"level":500,"level_name":"CRITICAL","channel":"app","datetime":"2025-01-15T14:30:00+00:00","extra":{"url":"/api/orders","method":"POST","ip":"10.0.0.1"}}

Detection: Line starts with { and contains "level_name" or "channel"

Extraction pattern:

JSON decode each line
Fields: message, context.exception, context.file, context.line, level_name, datetime, extra.*
Stack trace: context.trace (string or array)

2. PSR-3 / Monolog (Line Format)

[2025-01-15T14:30:00+00:00] app.CRITICAL: Connection refused {"exception":"PDOException","file":"/app/src/Infrastructure/Repository/OrderRepository.php","line":45} {"url":"/api/orders"}

Detection: Line matches \[\d{4}-\d{2}-\d{2}T.+\] \w+\.\w+:

Extraction pattern:

Regex: /^\[(.+?)\] (\w+)\.(\w+): (.+?)(\s+\{.+\})?\s*(\{.+\})?$/
Groups: datetime, channel, level, message, context_json, extra_json

3. Laravel Log Format

[2025-01-15 14:30:00] production.ERROR: SQLSTATE[HY000] [2002] Connection refused {"exception":"[object] (PDOException(code: 2002): SQLSTATE[HY000] [2002] Connection refused at /app/vendor/laravel/framework/src/Illuminate/Database/Connectors/Connector.php:70)
[stacktrace]
#0 /app/vendor/laravel/framework/src/Illuminate/Database/Connectors/Connector.php(70): PDO->__construct()
#1 /app/src/Infrastructure/Repository/OrderRepository.php(45): Illuminate\\Database\\Connectors\\Connector->createPdoConnection()
"}

Detection: Line matches \[\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}\] \w+\.(ERROR|CRITICAL|WARNING|INFO|DEBUG):

Extraction pattern:

Regex: /^\[(\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2})\] (\w+)\.(\w+): (.+)/
Groups: datetime, environment, level, message+context
Stack trace: Lines starting with #N after [stacktrace]
Exception: object class and message from context JSON

4. Symfony Log Format

[2025-01-15T14:30:00+00:00] request.CRITICAL: Uncaught PHP Exception PDOException: "Connection refused" at /app/src/Infrastructure/Repository/OrderRepository.php line 45 {"exception":"[object] (PDOException(code: 2002): Connection refused at /app/src/Infrastructure/Repository/OrderRepository.php:45)"}

Detection: Same as Monolog line format, channel often request, doctrine, security

Extraction pattern: Same as Monolog line format.

5. Plain PHP error_log

[15-Jan-2025 14:30:00 UTC] PHP Fatal error:  Uncaught PDOException: Connection refused in /app/src/Infrastructure/Repository/OrderRepository.php:45
Stack trace:
#0 /app/src/Infrastructure/Repository/OrderRepository.php(45): PDO->__construct()
#1 /app/src/Application/UseCase/CreateOrder.php(32): App\Infrastructure\Repository\OrderRepository->save()
#2 {main}
  thrown in /app/src/Infrastructure/Repository/OrderRepository.php on line 45

Detection: Line matches \[\d{2}-\w{3}-\d{4}.*\] PHP (Fatal error|Warning|Notice|Deprecated):

Extraction pattern:

Regex: /^\[(.+?)\] PHP (\w[\w ]+):\s+(.+) in (.+):(\d+)$/
Groups: datetime, severity, message, file, line
Stack trace: Lines starting with #N until blank line

6. PHP-FPM Slow Log

[15-Jan-2025 14:30:00]  [pool www] pid 1234
script_filename = /app/public/index.php
[0x00007f...] sleep() /app/src/Infrastructure/ExternalApi/PaymentGateway.php:89
[0x00007f...] App\Infrastructure\ExternalApi\PaymentGateway->charge() /app/src/Application/UseCase/ProcessPayment.php:34
[0x00007f...] App\Application\UseCase\ProcessPayment->execute() /app/src/Presentation/Api/Action/PaymentAction.php:28

Detection: Contains [pool and script_filename

Extraction pattern:

Entry starts with: /^\[\d{2}-\w{3}-\d{4}.*\]\s+\[pool/
Script: line after "script_filename = "
Stack frames: [address] function_call file:line
Top of stack = slowest function (bottleneck)

Analysis Capabilities

Exception Extraction

For each exception found:

markdown
| Field | Value |
|-------|-------|
| Exception | PDOException |
| Message | Connection refused |
| File | src/Infrastructure/Repository/OrderRepository.php |
| Line | 45 |
| Level | CRITICAL |
| Time | 2025-01-15 14:30:00 |

Stack Trace Analysis

Separate application frames from vendor frames:

markdown
### Application Frames (actionable)
#1 src/Infrastructure/Repository/OrderRepository.php:45 → PDO->__construct()
#2 src/Application/UseCase/CreateOrder.php:32 → OrderRepository->save()
#3 src/Presentation/Api/Action/CreateOrderAction.php:28 → CreateOrder->execute()

### Vendor Frames (context only)
#0 vendor/laravel/framework/src/Illuminate/Database/Connectors/Connector.php:70

Heuristic: Frame is "application" if path does NOT contain vendor/, var/cache/, or framework internals.

Request Context Extraction

Look for these fields in log context/extra:

URL: extra.url, context.request_uri, context.path
Method: extra.method, context.request_method
User: extra.user_id, context.user, extra.username
Correlation ID: extra.correlation_id, extra.request_id, extra.trace_id, context.X-Request-Id
IP: extra.ip, extra.client_ip, context.ip
Session: extra.session_id

Error Frequency Analysis

Group errors by exception class + message pattern:

markdown
## Error Frequency (last 24h)

| Exception | Message Pattern | Count | First | Last | Trend |
|-----------|----------------|-------|-------|------|-------|
| PDOException | Connection refused | 47 | 14:00 | 14:30 | ↑ spike |
| InvalidArgumentException | Invalid order status * | 12 | 08:15 | 14:28 | → steady |
| TimeoutException | Gateway timeout * | 3 | 14:25 | 14:30 | ↑ new |

Spike detection: If error count in last hour > 3x average hourly rate → flag as spike.

Error Correlation

Group related errors by:

  1. Time proximity — errors within 1-second window likely from same request
  2. Correlation ID — same request_id/trace_id across log entries
  3. Causal chain — Exception A causes Exception B (e.g., PDOException → QueryException → HttpException)
  4. File proximity — errors in same class/namespace within short timeframe
markdown
## Correlated Error Group

**Trigger:** PDOException: Connection refused (14:30:00)
**Cascade:**
  → QueryException: Could not execute query (14:30:00)
  → HttpException: 500 Internal Server Error (14:30:01)

**Root Cause:** Database connection failure
**Affected Endpoint:** POST /api/orders
**Impact:** 47 failed requests in 30 minutes

Reading Strategy

For Large Log Files

File size < 10KB   → Read entire file
File size 10KB-1MB → Read last 500 lines (most recent errors)
File size > 1MB    → Read last 1000 lines
                     + Grep for specific exception class or timestamp range

Targeted Extraction

When looking for specific errors:

# By exception class
Grep: /PDOException|QueryException/ in log file

# By severity
Grep: /\.(CRITICAL|ERROR|EMERGENCY):/ in log file

# By time range (last hour)
Grep: /\[2025-01-15 14:/ in log file

# By file reference
Grep: /OrderRepository\.php/ in log file

Multi-File Analysis

When multiple log files exist (e.g., daily rotation):

1. Start with most recent file (highest score from discovery)
2. If error pattern needs historical context → check previous day's file
3. Cross-reference application log with PHP-FPM slow log for performance
4. Cross-reference application log with web server error log for HTTP errors

Output Format

markdown
# Log Analysis Report

**Log File:** storage/logs/laravel.log
**Period:** 2025-01-15 14:00 — 14:30
**Lines Analyzed:** 1,247

## Summary

| Metric | Value |
|--------|-------|
| Total Errors | 62 |
| Unique Exceptions | 3 |
| Critical | 47 |
| Error | 12 |
| Warning | 3 |

## Top Exceptions

### 1. PDOException: Connection refused (47 occurrences)

**Severity:** 🔴 Critical
**First:** 14:00:12 | **Last:** 14:30:01 | **Trend:** ↑ Spike
**File:** `src/Infrastructure/Repository/OrderRepository.php:45`

**Application Stack:**

#1 OrderRepository.php:45 → PDO->__construct() #2 CreateOrder.php:32 → OrderRepository->save() #3 CreateOrderAction.php:28 → CreateOrder->execute()


**Request Context:**
- URL: POST /api/orders
- Correlation IDs: [req-abc123, req-def456, ...]

**Likely Cause:** Database server unreachable or connection pool exhausted

### 2. [Next exception...]

## Correlated Groups

[Correlation analysis...]

## Recommendations

1. **Immediate:** Check database connectivity and connection pool settings
2. **Investigation:** Review `OrderRepository` database configuration
3. **Prevention:** Add circuit breaker pattern for database connections

Integration Notes

  • This skill is read-only — it analyzes and reports, never modifies files
  • Works with Read, Grep tools available to all agents
  • Use discover-project-logs first to find log file locations
  • For bug diagnosis: focus on exception extraction and stack trace analysis
  • For performance review: focus on PHP-FPM slow log and error frequency
  • For Docker debugging: focus on PHP-FPM logs and error correlation

Frequently asked questions

What does the Analyze Php Logs AI skill do?

Parses and analyzes PHP application logs in PSR-3/Monolog, Laravel, Symfony, and plain error_log formats. Extracts exceptions, stack traces, request context, error frequency, and correlates related errors.

Why use Analyze Php Logs on TypingMind?

Because you install it once and use it with any model. Analyze Php Logs is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Analyze Php Logs in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dykyi-roman/awesome-claude-code/tree/master/skills/analyze-php-logs. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Analyze Php Logs?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Analyze Php Logs?

As many as you like. As long as a model supports skills, you can use Analyze Php Logs with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Analyze Php Logs AI skill free?

Yes. It is published on GitHub by dykyi-roman under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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