CC Workflow Studio AI Editor
breaking-brake/cc-wf-studio
Creates and edits visual agent workflows in CC Workflow Studio through conversation, with the agent reading and writing the canvas over MCP.
Analyze application logs from the .evlog/logs/ directory. An agent skill from activepieces/activepieces.
Install Analyze Logs
$ npx skills add activepieces/activepieces --skill analyze-logs -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install activepieces/activepieces analyze-logs --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/activepieces/activepieces.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/analyze-logs .claude/skills/analyze-logs && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "analyze-logs" agent skill from https://github.com/activepieces/activepieces/tree/main/.agents/skills/analyze-logs into .claude/skills/analyze-logs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-logs", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/activepieces/activepieces/tree/main/.agents/skills/analyze-logsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add activepieces/activepieces --skill analyze-logs -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install activepieces/activepieces analyze-logs --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/activepieces/activepieces.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/analyze-logs .agents/skills/analyze-logs && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "analyze-logs" agent skill from https://github.com/activepieces/activepieces/tree/main/.agents/skills/analyze-logs into .agents/skills/analyze-logs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-logs", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add activepieces/activepieces --skill analyze-logs -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install activepieces/activepieces analyze-logs --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/activepieces/activepieces.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/analyze-logs .cursor/skills/analyze-logs && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "analyze-logs" agent skill from https://github.com/activepieces/activepieces/tree/main/.agents/skills/analyze-logs into .cursor/skills/analyze-logs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-logs", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/activepieces/activepieces.git --path .agents/skills/analyze-logs--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add activepieces/activepieces --skill analyze-logs -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install activepieces/activepieces analyze-logs --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/activepieces/activepieces.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/analyze-logs .gemini/skills/analyze-logs && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "analyze-logs" agent skill from https://github.com/activepieces/activepieces/tree/main/.agents/skills/analyze-logs into .gemini/skills/analyze-logs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-logs", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install activepieces/activepieces analyze-logsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add activepieces/activepieces --skill analyze-logs -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/activepieces/activepieces.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/analyze-logs .github/skills/analyze-logs && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "analyze-logs" agent skill from https://github.com/activepieces/activepieces/tree/main/.agents/skills/analyze-logs into .github/skills/analyze-logs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-logs", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add activepieces/activepieces --skill analyze-logs -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install activepieces/activepieces analyze-logs --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/activepieces/activepieces.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/analyze-logs .opencode/skills/analyze-logs && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "analyze-logs" agent skill from https://github.com/activepieces/activepieces/tree/main/.agents/skills/analyze-logs into .opencode/skills/analyze-logs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-logs", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
analyze-logs- GitHub stars
- 25k
- Used in
- 1 other repo
- Token cost
- ~1.6k tokens
- SKILL.md length
- 626 words
- Files
- 1
- Skills in repo
- 13
- Repo updated
- First seen
- Licence
- MIT
At a glance
Analyze application logs from the .evlog/logs/ directory. An agent skill from activepieces/activepieces.
- Works in 3 steps: Read the most recent log file → Identify the relevant events → Analyze and explain
- Debugging errors
- SKILL.md covers When to Use, Finding the logs, If no logs are found and Log format, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Analyze Logs is an agent skill from activepieces/activepieces. Analyze application logs from the .evlog/logs/ directory. Use when debugging errors, investigating slow requests, understanding request patterns, or answering questions about application behavior. Reads structured NDJSON wide events written by evlog's file system drain.
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development, covering MCP servers and Workflow automation. It works with Model Context Protocol. The repository describes itself as: AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents. The licence is MIT.
When your agent uses it
- Debugging errors
- Investigating slow requests
- Understanding request patterns
- Answering questions about application behavior
Example prompts
- “/analyze-logs”
Workflow steps
3 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 8656fb8. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are typescript).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Analyze Logs loads about 1.6k tokens when it runs. Until then it costs about 71 tokens; SKILL.md has 626 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from activepieces/activepieces at commit 8656fb8, republished under its MIT licence (© activepieces). 626 words, ~1,617 tokens.
Download SKILL.mdSave it as
.claude/skills/analyze-logs/SKILL.md (or your agent's skills folder).- name
- analyze-logs
- description
- Analyze application logs from the .evlog/logs/ directory. Use when debugging errors, investigating slow requests, understanding request patterns, or answering questions about application behavior. Reads structured NDJSON wide events written by evlog's file system drain.
- license
- MIT
- metadata.author
- HugoRCD
- metadata.version
- 0.1
Analyze application logs
Read and analyze structured wide-event logs from the local .evlog/logs/ directory to debug errors, investigate performance issues, and understand application behavior.
When to Use
- User asks to debug an error, investigate a bug, or understand why something failed
- User asks about request patterns, slow endpoints, or error rates
- User asks "what happened" or "what's going on" with their application
- User asks to analyze logs, check recent errors, or review application behavior
- User mentions a specific error message or status code they're seeing
Finding the logs
Logs are written by evlog's file system drain as .jsonl files, organized by date.
Format detection: The drain supports two modes:
- NDJSON (default,
pretty: false): One compact JSON object per line. Parse line-by-line. - Pretty (
pretty: true): Multi-line indented JSON per event. Parse by reading the entire file and splitting on top-level objects (e.g.JSON.parse('[' + content.replace(/\}\n\{/g, '},{') + ']')) or use a streaming JSON parser.
Always check the first few bytes of the file to detect the format: if the second character is a newline or ", it's NDJSON; if it's a space or newline followed by spaces, it's pretty-printed.
Search order — check these locations relative to the project root:
.evlog/logs/(default)- Any
.evlog/logs/inside app directories (monorepos:apps/*/.evlog/logs/)
Use glob to find log files:
.evlog/logs/*.jsonl
*/.evlog/logs/*.jsonl
apps/*/.evlog/logs/*.jsonlFiles are named by date: 2026-03-14.jsonl. Start with the most recent file.
If no logs are found
The file system drain may not be enabled. Guide the user to set it up:
import { createFsDrain } from 'evlog/fs'
// Nuxt / Nitro: server/plugins/evlog-drain.ts
export default defineNitroPlugin((nitroApp) => {
nitroApp.hooks.hook('evlog:drain', createFsDrain())
})
// Hono / Express / Elysia: pass in middleware options
app.use(evlog({ drain: createFsDrain() }))
// Fastify: pass in plugin options
await app.register(evlog, { drain: createFsDrain() })
// NestJS: pass in module options
EvlogModule.forRoot({ drain: createFsDrain() })
// Standalone: pass to initLogger
initLogger({ drain: createFsDrain() })After setup, the user needs to trigger some requests to generate logs, then re-analyze.
Log format
Each line is a self-contained JSON object (wide event). Key fields:
| Field | Type | Description |
|---|---|---|
timestamp | string | ISO 8601 timestamp |
level | string | info, warn, error, debug |
service | string | Service name |
environment | string | development, production, etc. |
method | string | HTTP method (GET, POST, etc.) |
path | string | Request path (/api/checkout) |
status | number | HTTP response status code |
duration | string | Request duration ("234ms") |
requestId | string | Unique request identifier |
error | object | Error details: name, message, stack, statusCode, data |
error.data.why | string | Human-readable explanation of what went wrong |
error.data.fix | string | Suggested fix for the error |
source | string | client for browser logs, absent for server logs |
userAgent | object | Parsed browser/OS/device info |
All other fields are application-specific context added via log.set() (e.g. user, cart, payment).
How to analyze
Show full SKILL.md (251 more words)Show less
Step 1: Read the most recent log file
Read the latest .jsonl file. Each line is one JSON event. Parse each line independently.
Step 2: Identify the relevant events
Filter based on the user's question:
- Errors: look for
"level":"error"orstatus >= 400 - Specific endpoint: match on
path - Slow requests: parse
duration(e.g."706ms") and filter high values - Specific user/action: match on application-specific fields
- Client-side issues: filter by
"source":"client" - Time range: compare
timestampvalues
Step 3: Analyze and explain
For each relevant event:
- What happened: summarize the
path,method,status,level - Why it failed (errors): read
error.message,error.data.why, and the stack trace - How to fix: check
error.data.fixfor suggested remediation - Context: examine application-specific fields for business context (user info, payment details, etc.)
- Patterns: look for recurring errors, degrading performance, or correlated failures
Analysis patterns
Find all errors
Filter: level === "error"
Group by: error.message or path
Look for: recurring patterns, common failure modesFind slow requests
Filter: parse duration string, compare > threshold (e.g. 1000ms)
Sort by: duration descending
Look for: specific endpoints, time-of-day patternsTrace a specific request
Filter: requestId === "the-request-id"
Result: single wide event with all context for that requestError rate by endpoint
Group events by: path
Count: total events vs error events per path
Look for: endpoints with high error ratiosClient vs server errors
Split by: source === "client" vs no source field
Compare: error patterns between client and server
Look for: client errors that don't have corresponding server errors (network issues)Important notes
- Each line is a complete, self-contained event. Unlike traditional logs, you don't need to correlate multiple lines — one line has all the context for one request.
- The
error.data.whyanderror.data.fixfields are evlog-specific structured error fields. When present, they provide the most actionable information. - Duration values are strings with units (e.g.
"706ms"). Parse the numeric part for comparisons. - Events with
"source":"client"originated from browser-side logging and were sent to the server via the transport endpoint. - Log files are
.gitignore'd automatically — they exist only on the local machine or server where the app runs.
© activepieces, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in .agents/skills/analyze-logs of activepieces/activepieces.
Open the folder on GitHubat commit 8656fb8
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in activepieces/activepieces, which our catalogue first saw on October 8, 2026.
Compare with similar skills
Analyze Logs next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Analyze Logs this skillactivepieces/activepieces | 25k | 1 repos | ~1.6k | Automated safety check: Pass | MIT | |
| CC Workflow Studio AI Editorbreaking-brake/cc-wf-studio | 5.4k | — | ~561 | Automated safety check: Pass | Custom licence | |
| ObservalObserval/Observal | 4.2k | — | ~2.2k | Automated safety check: Pass | Apache-2.0 | |
| Zapier Statuszapier/zapier-mcp | 428 | — | ~1.8k | Automated safety check: Pass | MIT | |
| n8n Multi-Instance Targetingczlonkowski/n8n-skills | 6.4k | — | ~3.2k | Automated safety check: Pass | MIT | |
| Agents Onboardingfazer-ai/agents | 118 | — | ~4.4k | Automated safety check: Pass | Apache-2.0 |
Similar skills
Observal
Observal/Observal
A skill your agent uses when starting any task the organization may already have an approved skill, prompt, MCP server, or Agent for: reviewing code, a commit, a diff, or a pull request; writing…
- Official
Zapier Status
zapier/zapier-mcp
Check the health of your Zapier MCP setup. An agent skill from zapier/zapier-mcp.
n8n Multi-Instance Targeting
czlonkowski/n8n-skills
Keeps an n8n MCP session pointed at the right n8n instance, with rules for discovering, switching and verifying the target before credential writes and for recovering from misroutes.
Agents Onboarding
fazer-ai/agents
Conduz a jornada de onboarding 'do zero ao agente de atendimento' do fazer.ai agents num VPS, escolhendo o orquestrador de deploy (Tier A Coolify, B Portainer, C compose genérico para VM crua ou…
Project Pull Request
swimmwatch/cloakbrowser-mcp
Create, update, prepare, or review a cloakbrowser-mcp GitHub Pull Request only when the user explicitly requests PR work.
More from activepieces/activepieces
All 13 skills in this repoActivepieces Design System
activepieces/activepieces
Design system for Activepieces (open-source AI automation platform, "open source replacement for Zapier").
Piece Builder
activepieces/activepieces
Build and edit Activepieces pieces (integrations) — creating new pieces, adding actions or triggers, or fixing bugs in existing ones.
Profile App Cpu
activepieces/activepieces
Find what is burning CPU in a live app container without restarting it: separate the JS thread from GC and libuv, open the V8 inspector in place with SIGUSR1, take a CPU profile over CDP, and…
Profile Worker Memory
activepieces/activepieces
Diagnose a worker that is growing memory or being OOM-killed: separate a JS-heap leak from native growth, take a V8 heap snapshot of a live worker in place (never uploading it), and walk the…
Triage Dependabot Alerts
activepieces/activepieces
Triage Dependabot dependency vulnerability alerts for the Activepieces repo — pull open alerts, dedupe to distinct (package, advisory), confirm the vulnerable package + API is actually used, and…
Triage Image Cves
activepieces/activepieces
Scan an Activepieces Docker image with grype for OS/base-image (deb) and application (npm) CVEs of High/Critical severity.
Related
Works with
Questions about Analyze Logs
What does Analyze Logs do?
Analyze application logs from the .evlog/logs/ directory. An agent skill from activepieces/activepieces. Analyze Logs is an agent skill from activepieces/activepieces.evlog/logs/ directory.
When should I use Analyze Logs?
Analyze Logs fits situations like: debugging errors; investigating slow requests; understanding request patterns; answering questions about application behavior.
How do I install Analyze Logs in Claude Code?
Run `npx skills add activepieces/activepieces --skill analyze-logs -a claude-code`. Or copy the skill folder (.agents/skills/analyze-logs in activepieces/activepieces) into .claude/skills/analyze-logs in your project. Claude Code loads it when a task matches its description.
How do I install Analyze Logs in Codex?
Run `npx skills add activepieces/activepieces --skill analyze-logs -a codex`. Or copy the skill folder (.agents/skills/analyze-logs in activepieces/activepieces) into .agents/skills/analyze-logs in your project. Codex loads it when a task matches its description.
Can I use Analyze Logs in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add activepieces/activepieces --skill analyze-logs -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analyze-logs, .gemini/skills/analyze-logs, .github/skills/analyze-logs and .opencode/skills/analyze-logs in your project.
What does Analyze Logs need to run?
SKILL.md names no scripts, command-line tools or credentials: Analyze Logs is instructions for the agent only.
Does Analyze Logs access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Analyze Logs safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Analyze Logs use?
Analyze Logs is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Analyze Logs use?
About 1.6k tokens (SKILL.md is roughly 6.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Analyze Logs?
Skills that share tags, products or a category with Analyze Logs: CC Workflow Studio AI Editor (breaking-brake/cc-wf-studio, 5.4k stars), Observal (Observal/Observal, 4.2k stars), Zapier Status (zapier/zapier-mcp, 428 stars) and n8n Multi-Instance Targeting (czlonkowski/n8n-skills, 6.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Analyze Logs?
activepieces (a GitHub organization) maintains it in activepieces/activepieces, which has 24,941 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on October 8, 2026.
Source: activepieces/activepieces on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.