Collect Apify debug evidence for support tickets and troubleshooting.

MITAuto-check: notesSales & Support

Install Apify Debug Bundle

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill apify-debug-bundle -a claude-code

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

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace apify-debug-bundle --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/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/apify-debug-bundle .claude/skills/apify-debug-bundle && 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
apify-debug-bundle
GitHub stars
2.8k
Token cost
~1.3k tokens
SKILL.md length
502 words
Files
3 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Collect Apify debug evidence for support tickets and troubleshooting.

  • Works in 4 steps: Investigate the failed run — pull run… → Create the debug bundle — run… → Compare against a good run (optional) —… → …
  • An Actor run has failed
  • SKILL.md covers Overview, Prerequisites, Authentication and Instructions, plus 7 more sections
  • Needs APIFY_TOKEN

What it does

Apify Debug Bundle is an agent skill from jeremylongshore/tons-of-skills-marketplace. Collect Apify debug evidence for support tickets and troubleshooting. Use when an Actor run has failed, is stuck, or produced empty output and you need to gather run metadata, logs, dataset samples, and environment info before opening a support ticket. Trigger with "apify debug", "apify support bundle", "collect apify logs", "apify diagnostic", "apify run failed why".

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/examples.md` and `references/implementation.md`). Compatibility notes: Designed for Claude Code

It sits in Sales & Support, covering Web scraping and Customer support. It works with Apify. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • An Actor run has failed
  • Produced empty output and you need to gather run metadata
  • Dataset samples
  • Environment info before opening a support ticket

Example prompts

  • “apify debug”
  • “apify support bundle”
  • “collect apify logs”
  • “/apify-debug-bundle”

Requirements

  • A credential in APIFY_TOKEN
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Bash(curl:*), Bash(npm:*), Bash(node:*), Bash(tar:*), Bash(apify:*), Grep

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Investigate the failed run — pull run summary, dataset stats, and the log
  2. Create the debug bundle — run apify-debug-bundle.sh . It
  3. Compare against a good run (optional) — diff a successful and failed run
  4. Live-tail a running Actor (optional) — stream logs when the final log is

What it can do on your machine

Read from SKILL.md and the folder at commit 23ea8d4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Bash(curl:*)
    • Bash(npm:*)
    • Bash(node:*)
    • Bash(tar:*)
    • Bash(apify:*)
    • Grep

    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 and bash).

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

  • Network

    Links to these hosts (documentation or services it may open):

    • console.apify.com
    • docs.apify.com
    • status.apify.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • APIFY_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Apify Debug Bundle loads about 1.3k tokens when it runs, and up to ~3.3k if it reads all its reference files. Until then it costs about 97 tokens; SKILL.md has 502 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~97
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.3k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:40
    script redacts any local `.env` before packaging, and the platform auto-redacts
  • NoteMentions a .env fileSKILL.md:59
    key-value store keys, a redacted `.env`, and platform health, then packages
  • NoteMentions a .env fileSKILL.md:83
    | `env-redacted.txt` | Local `.env` with all values redacted |

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 jeremylongshore/tons-of-skills-marketplace at commit 23ea8d4, republished under its MIT licence (© jeremylongshore). 502 words, ~1,328 tokens.

Download SKILL.mdSave it as .claude/skills/apify-debug-bundle/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
apify-debug-bundle
description
Collect Apify debug evidence for support tickets and troubleshooting. Use when an Actor run has failed, is stuck, or produced empty output and you need to gather run metadata, logs, dataset samples, and environment info before opening a support ticket. Trigger with "apify debug", "apify support bundle", "collect apify logs", "apify diagnostic", "apify run failed why".
allowed-tools
Read, Bash(curl:*), Bash(npm:*), Bash(node:*), Bash(tar:*), Bash(apify:*), Grep
compatibility
Designed for Claude Code
version
1.5.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, scraping, automation, apify

Apify Debug Bundle

Overview

Collect all diagnostic information needed to troubleshoot failed Actor runs and prepare Apify support tickets. Pulls run metadata, logs, dataset samples, and environment info into a single bundle so a support engineer (or you) can diagnose the failure without live access to your account.

Prerequisites

  • apify-client installed
  • APIFY_TOKEN configured
  • A failed or problematic run ID to investigate

Authentication

All API calls authenticate with the APIFY_TOKEN as a Bearer header (Authorization: Bearer $APIFY_TOKEN), and the SDK reads the same token from process.env.APIFY_TOKEN. Get the token from the Apify Console under Settings → Integrations → Personal API tokens. Never commit it — the bundle script redacts any local .env before packaging, and the platform auto-redacts secrets inside run logs.

Instructions

The workflow has four steps. The skeleton below is enough to run it; each step's full implementation lives in implementation.md.

  1. Investigate the failed run — pull run summary, dataset stats, and the log tail via the SDK. The core call:

    typescript
    const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
    const run = await client.run(runId).get();
    const log = await client.run(runId).log().get();
  2. Create the debug bundle — run apify-debug-bundle.sh <RUN_ID>. It collects environment info, run details, log, a 5-item dataset sample, key-value store keys, a redacted .env, and platform health, then packages everything into a timestamped .tar.gz. Full script in implementation.md.

  3. Compare against a good run (optional) — diff a successful and failed run field-by-field to spot the delta (compareRuns(successId, failId)).

  4. Live-tail a running Actor (optional) — stream logs when the final log is not yet available.

For copy-pasteable code for every step, see implementation.md.

Output

A single timestamped tarball, apify-debug-YYYYMMDD-HHMMSS.tar.gz, containing:

FileContents
environment.txtNode/npm versions, installed Apify packages, CLI version
run-details.jsonRun status, options, stats, usage, cost
run-log.txtFull run log (secrets auto-redacted by the platform)
dataset-sample.jsonFirst 5 dataset items
kv-store-keys.jsonKey-value store key listing
env-redacted.txtLocal .env with all values redacted
platform-health.jsonApify platform health snapshot

Attach the tarball directly to an Apify support ticket.

Show full SKILL.md (196 more words)Show less

Sensitive Data Handling

Always redact before sharing:

  • API tokens (apify_api_*)
  • Proxy passwords
  • PII (emails, names, IPs)
  • Custom environment variables

Safe to include:

  • Run IDs, Actor IDs, dataset IDs
  • Error messages and stack traces
  • Run configuration (memory, timeout)
  • Platform health status

Escalation Path

  1. Check run log for stack trace
  2. Compare with a successful run
  3. Check Apify Status for outages
  4. Create debug bundle
  5. Submit to Apify Support with bundle attached

Error Handling

IssueCauseSolution
Run not foundInvalid run ID or expiredUnnamed runs expire after 7 days
Log unavailableRun still in progressWait for completion or stream live
Empty datasetActor produced no outputCheck failedRequestHandler in code
High CU usageMemory too high or slow executionReduce memory, optimize code

Examples

Four worked scenarios — a plain FAILED run, an "it worked yesterday" regression diff, an empty-dataset investigation, and live-tailing a hung run — are in examples.md. The quickest path:

bash
export APIFY_TOKEN="apify_api_..."
./apify-debug-bundle.sh abc123DEF          # → apify-debug-20260717-142530.tar.gz
tar -xzf apify-debug-*.tar.gz && tail -40 apify-debug-*/run-log.txt

See examples.md for the full walkthroughs, including reading the comparison output and interpreting a live tail.

Resources

Next Steps

For rate limit issues, see the apify-rate-limits skill.

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/.curated/apify-debug-bundle of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/examples.md
  • references/implementation.md

Open the folder on GitHubat commit 23ea8d4

Compare with similar skills

Apify Debug Bundle 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.

Apify Debug Bundle compared with similar skills
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Ops LeadgenLifecycle-Innovations-Limited/claude-ops540—~990Automated safety check: NotesMIT
Tech Stack Teardownmajiayu000/claude-skill-registry6662 repos~3.1kAutomated safety check: NotesMIT
Voice Of Customer Synthesizermajiayu000/claude-skill-registry6662 repos~2.4kAutomated safety check: PassMIT

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Works with

Questions about Apify Debug Bundle

What does Apify Debug Bundle do?

Collect Apify debug evidence for support tickets and troubleshooting. Apify Debug Bundle is an agent skill from jeremylongshore/tons-of-skills-marketplace. Collect Apify debug evidence for support tickets and troubleshooting.

When should I use Apify Debug Bundle?

Apify Debug Bundle fits situations like: an Actor run has failed; produced empty output and you need to gather run metadata; dataset samples; environment info before opening a support ticket.

How do I install Apify Debug Bundle in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill apify-debug-bundle -a claude-code`. Or copy the skill folder (skills/.curated/apify-debug-bundle in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/apify-debug-bundle in your project. Claude Code loads it when a task matches its description.

How do I install Apify Debug Bundle in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill apify-debug-bundle -a codex`. Or copy the skill folder (skills/.curated/apify-debug-bundle in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/apify-debug-bundle in your project. Codex loads it when a task matches its description.

Can I use Apify Debug Bundle 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 jeremylongshore/tons-of-skills-marketplace --skill apify-debug-bundle -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/apify-debug-bundle, .gemini/skills/apify-debug-bundle, .github/skills/apify-debug-bundle and .opencode/skills/apify-debug-bundle in your project.

What does Apify Debug Bundle need to run?

Going by SKILL.md and its folder, Apify Debug Bundle needs credentials named APIFY_TOKEN. Our summary lists: A credential in APIFY_TOKEN. Its frontmatter pre-approves these tools: Read, Bash(curl:*), Bash(npm:*), Bash(node:*), Bash(tar:*), Bash(apify:*), Grep. Compatibility (from SKILL.md): Designed for Claude Code.

Does Apify Debug Bundle access the network?

SKILL.md names 3 domains. As links in the text: console.apify.com, docs.apify.com and status.apify.com. This is read from the text; nothing was executed.

Is Apify Debug Bundle safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Apify Debug Bundle use?

Apify Debug Bundle 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 Apify Debug Bundle use?

About 1.3k tokens (SKILL.md is roughly 5.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2k tokens, read only when the agent opens those files.

What are the alternatives to Apify Debug Bundle?

Skills that share tags, products or a category with Apify Debug Bundle: Apify Ecommerce (majiayu000/claude-skill-registry, 666 stars), Etsy Shop Sales History (sickn33/agentic-awesome-skills, 47k stars), Ops Leadgen (Lifecycle-Innovations-Limited/claude-ops, 540 stars) and Tech Stack Teardown (majiayu000/claude-skill-registry, 666 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Apify Debug Bundle?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,821 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 8, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.