Agent skill

Profile Worker Memory

by activepieces in 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…

Custom licenceAuto-check passedProductivity & Automation

Install Profile Worker Memory

skills CLI
$ npx skills add activepieces/activepieces --skill profile-worker-memory -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install activepieces/activepieces profile-worker-memory --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/activepieces/activepieces.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/profile-worker-memory .claude/skills/profile-worker-memory && rm -rf skills-src

Use ~/.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/

Facts

Skill name
profile-worker-memory
GitHub stars
25k
Token cost
~1.7k tokens
SKILL.md length
789 words
Files
1
Skills in repo
14
Repo updated
First seen
Licence
Custom licence

At a glance

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…

  • Works in 5 steps: Confirm it is actually OOM, and find… → JS heap or native? Decide before you… → Snapshot in place → …
  • A self-hoster reports memory correlates with pod age
  • SKILL.md covers 1. Confirm it is actually OOM,…, 2. JS heap or native? Decide…, 3. Snapshot in place and 4. Parse it off the worker…, plus 3 more sections
  • Calls docker and node

What it does

Profile Worker Memory is an agent skill from 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 retainer path back to the code that holds the memory. Use when a self-hoster reports 'memory correlates with pod age', workers restart on their own, or a container sits near its limit.

Its SKILL.md is about 1.7k 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 Productivity & Automation, 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.

When your agent uses it

  • A self-hoster reports memory correlates with pod age
  • Workers restart on their own
  • A container sits near its limit

Example prompts

  • “memory correlates with pod age”
  • “/profile-worker-memory”

Requirements

  • Docker

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Confirm it is actually OOM, and find what is dying
  2. JS heap or native? Decide before you snapshot
  3. Snapshot in place
  4. Parse it off the worker process
  5. Walk the retainer path — this is the answer

What it can do on your machine

Read from SKILL.md and the folder at commit 566f00e. 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

    Shell commands in SKILL.md call:

    • docker
    • node

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use docker, which can reach the network depending on how they are called.

    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

Profile Worker Memory loads about 1.7k tokens when it runs. Until then it costs about 99 tokens; SKILL.md has 789 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~99
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

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

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 789 words (~1,731 tokens).

“Never ask anyone to upload a heap snapshot. It contains connection tokens, API keys, and customer step data verbatim — a customer will refuse, and they are right to. This procedure keeps the snapshot on their box and moves only…”

— opening of SKILL.md by activepieces, Custom licence
name
profile-worker-memory

Read the full SKILL.md on GitHub

Files

Just SKILL.md in .agents/skills/profile-worker-memory of activepieces/activepieces.

Open the folder on GitHubat commit 566f00e

Compare with similar skills

Profile Worker Memory 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.

Profile Worker Memory compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Profile Worker Memory this skillactivepieces/activepieces25k—~1.7kAutomated safety check: PassCustom licence
Zapier Statuszapier/zapier-mcp430—~1.8kAutomated safety check: PassMIT
n8n Multi-Instance Targetingczlonkowski/n8n-skills6.4k—~3.2kAutomated safety check: PassMIT
Agents Onboardingfazer-ai/agents118—~4.4kAutomated safety check: PassApache-2.0
N8n MCP Tools Expertdavila7/claude-code-templates32k8 repos~3.2kAutomated safety check: PassMIT
n8n MCP Tools Expertczlonkowski/n8n-skills6.4k—~7.6kAutomated safety check: PassMIT

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Questions about Profile Worker Memory

What does Profile Worker Memory do?

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…. Profile Worker Memory is an agent skill from 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 retainer path back to the code that holds the memory.

When should I use Profile Worker Memory?

Profile Worker Memory fits situations like: A self-hoster reports memory correlates with pod age; workers restart on their own; A container sits near its limit.

How do I install Profile Worker Memory in Claude Code?

Run `npx skills add activepieces/activepieces --skill profile-worker-memory -a claude-code`. Or copy the skill folder (.agents/skills/profile-worker-memory in activepieces/activepieces) into .claude/skills/profile-worker-memory in your project. Claude Code loads it when a task matches its description.

How do I install Profile Worker Memory in Codex?

Run `npx skills add activepieces/activepieces --skill profile-worker-memory -a codex`. Or copy the skill folder (.agents/skills/profile-worker-memory in activepieces/activepieces) into .agents/skills/profile-worker-memory in your project. Codex loads it when a task matches its description.

Can I use Profile Worker Memory 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 profile-worker-memory -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/profile-worker-memory, .gemini/skills/profile-worker-memory, .github/skills/profile-worker-memory and .opencode/skills/profile-worker-memory in your project.

What does Profile Worker Memory need to run?

Going by SKILL.md and its folder, Profile Worker Memory needs the command-line tools its instructions call (docker and node). Our summary lists: Docker.

Does Profile Worker Memory access the network?

SKILL.md contains no URLs. Its commands use docker, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Profile Worker Memory 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 Profile Worker Memory use?

Profile Worker Memory has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Profile Worker Memory use?

About 1.7k tokens (SKILL.md is roughly 6.9k 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 Profile Worker Memory?

Skills that share tags, products or a category with Profile Worker Memory: Zapier Status (zapier/zapier-mcp, 430 stars), n8n Multi-Instance Targeting (czlonkowski/n8n-skills, 6.4k stars), Agents Onboarding (fazer-ai/agents, 118 stars) and N8n MCP Tools Expert (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Profile Worker Memory?

activepieces (a GitHub organization) maintains it in activepieces/activepieces, which has 24,961 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on October 9, 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.