Agent skill

Kafka

by aspectrr in aspectrr/deer

Kafka topic management, consumer group monitoring, message production/consumption, and cluster health diagnostics.

MITAuto-check passedBackend & APIs

Install Kafka

skills CLI
$ npx skills add aspectrr/deer --skill kafka -a claude-code

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

GitHub CLI
$ gh skill install aspectrr/deer kafka --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/aspectrr/deer.git skills-src && mkdir -p .claude/skills && cp -r skills-src/deer-cli/internal/skill/defaults/kafka .claude/skills/kafka && 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
kafka
GitHub stars
405
Token cost
~946 tokens
SKILL.md length
229 words
Files
1
Skills in repo
14
Repo updated
First seen
Licence
MIT

At a glance

Kafka topic management, consumer group monitoring, message production/consumption, and cluster health diagnostics.

  • Works in 4 steps: Check lag: kafka-consumer-groups… → Check consumer is running: systemctl… → Check topic end offsets: GetOffsetShell… → …
  • Working with Kafka brokers
  • SKILL.md covers When to Use, Common Commands, Deer Sandbox Integration and Diagnostic Patterns
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Kafka is an agent skill from aspectrr/deer. Kafka topic management, consumer group monitoring, message production/consumption, and cluster health diagnostics. Use when working with Kafka brokers, topics, consumer lag, or debugging pipeline issues.

Its SKILL.md is about 950 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 Backend & APIs, covering Event-driven systems. It works with Apache Kafka. The repository describes itself as: 🦌 The AI Elasticsearch Engineer. The licence is MIT.

When your agent uses it

  • Working with Kafka brokers
  • Debugging pipeline issues

Example prompts

  • “/kafka”

Workflow steps

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

  1. Check lag: kafka-consumer-groups --describe --group
  2. Check consumer is running: systemctl status
  3. Check topic end offsets: GetOffsetShell --topic
  4. Common causes: slow consumer, network latency, too few partitions, consumer crashes

What it can do on your machine

Read from SKILL.md and the folder at commit e4f9845. 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 bash).

    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

Kafka loads about 946 tokens when it runs. Until then it costs about 52 tokens; SKILL.md has 229 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~52
When it runs · the whole SKILL.md, loaded when a task matches
~946

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 aspectrr/deer at commit e4f9845, republished under its MIT licence (© aspectrr). 229 words, ~946 tokens.

Download SKILL.mdSave it as .claude/skills/kafka/SKILL.md (or your agent's skills folder).
name
kafka
description
Kafka topic management, consumer group monitoring, message production/consumption, and cluster health diagnostics. Use when working with Kafka brokers, topics, consumer lag, or debugging pipeline issues.
version
1.0.0

Kafka Operations

When to Use

  • Managing Kafka topics (create, describe, delete, list)
  • Monitoring consumer group lag
  • Producing or consuming messages for testing
  • Diagnosing broker connectivity issues
  • Checking partition offsets and health
  • Debugging logstash pipelines that read from or write to Kafka

Common Commands

Cluster Status
bash
# Check broker health
kafka-broker-api-versions --bootstrap-server localhost:9092

# List topics with partition counts
kafka-topics --bootstrap-server localhost:9092 --list

# Describe a topic (partitions, replicas, ISR)
kafka-topics --bootstrap-server localhost:9092 --describe --topic <topic>
Topic Management
bash
# Create topic
kafka-topics --bootstrap-server localhost:9092 --create --topic <name> --partitions 3 --replication-factor 1

# Delete topic
kafka-topics --bootstrap-server localhost:9092 --delete --topic <name>

# Increase partitions
kafka-topics --bootstrap-server localhost:9092 --alter --topic <name> --partitions <count>
Consumer Groups
bash
# List all consumer groups
kafka-consumer-groups --bootstrap-server localhost:9092 --list

# Show consumer group lag (key debugging command)
kafka-consumer-groups --bootstrap-server localhost:9092 --describe --group <group>

# Reset consumer group offsets (use with caution)
kafka-consumer-groups --bootstrap-server localhost:9092 --group <group> --topic <topic> --reset-offsets --to-earliest --execute
Produce and Consume
bash
# Produce a message with key
echo "key:value" | kafka-console-producer --bootstrap-server localhost:9092 --topic <topic> --property "parse.key=true" --property "key.separator=:"

# Consume messages from beginning
kafka-console-consumer --bootstrap-server localhost:9092 --topic <topic> --from-beginning --max-messages 10

# Consume with key and value
kafka-console-consumer --bootstrap-server localhost:9092 --topic <topic> --from-beginning --property print.key=true --property key.separator="|"
Offset Inspection
bash
# Show earliest and latest offsets
kafka-run-class kafka.tools.GetOffsetShell --broker-list localhost:9092 --topic <topic>

Deer Sandbox Integration

When debugging Kafka-dependent services in a deer sandbox with kafka_stub=true:

  • Redpanda runs at localhost:9092 inside the sandbox
  • Use rpk topic list --brokers localhost:9092 for topic management
  • Use rpk topic produce <topic> --brokers localhost:9092 to send test messages
  • Use rpk topic consume <topic> --brokers localhost:9092 to read messages
  • Use rpk group list --brokers localhost:9092 for consumer groups

Diagnostic Patterns

High Consumer Lag
  1. Check lag: kafka-consumer-groups --describe --group <group>
  2. Check consumer is running: systemctl status <consumer-service>
  3. Check topic end offsets: GetOffsetShell --topic <topic>
  4. Common causes: slow consumer, network latency, too few partitions, consumer crashes
Broker Connectivity Issues
  1. Verify broker is listening: ss -tlnp | grep 9092
  2. Check advertised.listeners in server.properties
  3. Test connectivity: kafka-broker-api-versions --bootstrap-server <host>:9092
  4. Check logs: journalctl -u kafka --no-pager -n 100
Logstash Kafka Input Issues
  1. Verify topic exists and has data
  2. Check consumer group lag
  3. Verify bootstrap_servers config in logstash pipeline
  4. Check logstash logs for connection errors: journalctl -u logstash --no-pager -n 100
  5. In sandbox: replace bootstrap address with localhost:9092

© aspectrr, 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 deer-cli/internal/skill/defaults/kafka of aspectrr/deer.

Open the folder on GitHubat commit e4f9845

Compare with similar skills

Kafka 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.

Kafka compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Kafka this skillaspectrr/deer405—~946Automated safety check: PassMIT
Windmill Trigger Type Checklistwindmill-labs/windmill18k—~4.7kAutomated safety check: PassCustom licence
FoundatioFoundatioFx/Foundatio2.1k—~3.9kAutomated safety check: PassApache-2.0
Opensource Guide Coachcalf-ai/calfkit-sdk1491 repos~2.1kAutomated safety check: PassApache-2.0
Create Environmentgodatadriven/whirl205—~1.9kAutomated safety check: PassApache-2.0
Monstermq Graphql Configvogler75/monster-mq143—~2.3kAutomated safety check: PassGPL-3.0

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Works with

Categories

Questions about Kafka

What does Kafka do?

Kafka topic management, consumer group monitoring, message production/consumption, and cluster health diagnostics. Kafka is an agent skill from aspectrr/deer. Kafka topic management, consumer group monitoring, message production/consumption, and cluster health diagnostics.

When should I use Kafka?

Kafka fits situations like: working with Kafka brokers; debugging pipeline issues.

How do I install Kafka in Claude Code?

Run `npx skills add aspectrr/deer --skill kafka -a claude-code`. Or copy the skill folder (deer-cli/internal/skill/defaults/kafka in aspectrr/deer) into .claude/skills/kafka in your project. Claude Code loads it when a task matches its description.

How do I install Kafka in Codex?

Run `npx skills add aspectrr/deer --skill kafka -a codex`. Or copy the skill folder (deer-cli/internal/skill/defaults/kafka in aspectrr/deer) into .agents/skills/kafka in your project. Codex loads it when a task matches its description.

Can I use Kafka 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 aspectrr/deer --skill kafka -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/kafka, .gemini/skills/kafka, .github/skills/kafka and .opencode/skills/kafka in your project.

What does Kafka need to run?

SKILL.md names no scripts, command-line tools or credentials: Kafka is instructions for the agent only.

Does Kafka 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 Kafka 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 Kafka use?

Kafka is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Kafka use?

About 946 tokens (SKILL.md is roughly 3.8k 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 Kafka?

Skills that share tags, products or a category with Kafka: Windmill Trigger Type Checklist (windmill-labs/windmill, 18k stars), Foundatio (FoundatioFx/Foundatio, 2.1k stars), Opensource Guide Coach (calf-ai/calfkit-sdk, 149 stars) and Create Environment (godatadriven/whirl, 205 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Kafka?

aspectrr (a GitHub user) maintains it in aspectrr/deer, which has 405 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on April 21, 2026.

Source: aspectrr/deer on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.