Developer Listening

Community

jonathimer

developer-listening

Monitor what developers say about your brand, competitors, and the problems they're solving. Track mentions and conversations across GitHub, Hacker News, Reddit, Stack Overflow, Twitter, and Discord. Trigger phrases: "developer listening", "monitor developer conversations", "track developer mentions", "what are developers saying", "developer sentiment", "brand monitoring", "social listening for devtools", "find developer conversations", "monitor GitHub mentions", "track Hacker News mentions"

Overview

Publisher	jonathimer
Repository	`devmarketing-skills`
Skill name	`developer-listening`
Stars	87
Forks	6
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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 jonathimer on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
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.

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/jonathimer/devmarketing-skills.git /tmp/devmarketing-skills
mkdir -p .claude/skills
cp -r /tmp/devmarketing-skills/skills/developer-listening .claude/skills/developer-listening

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Developer Listening 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 Developer Listening 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 Developer Listening 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.

Developer Listening

Monitor developer conversations across platforms to understand sentiment, find engagement opportunities, and gather competitive intelligence.

Overview

Developer listening is the practice of systematically monitoring what developers say about your brand, competitors, and the problems your product solves. Unlike traditional social listening, developer listening requires monitoring technical platforms where developers actually spend time: GitHub, Hacker News, Reddit programming communities, Stack Overflow, Twitter/X, and Discord servers.

Effective developer listening helps you:

Understand how developers perceive your product
Find frustrated users who need help (and might churn)
Discover engagement opportunities before competitors
Gather unfiltered product feedback
Track competitive positioning in real conversations
Identify content gaps and documentation issues

Setting Up Your Monitoring Strategy

1. Define Your Keyword Categories

Before setting up monitoring, organize keywords into categories:

Brand Keywords:

Your product name and common misspellings
Your company name
Key team members' names (for attribution)
Your GitHub org/repos
Your Twitter handles

Competitor Keywords:

Direct competitor names
Competitor product features
Competitor pricing/plan names

Problem Keywords:

Pain points your product solves
Error messages you help with
Workflow descriptions ("deploy to kubernetes", "manage API keys")
"How do I..." phrases relevant to your space

Buy Intent Keywords:

"[category] recommendation"
"best [tool type] for [use case]"
"looking for [solution]"
"alternative to [competitor]"
"[competitor] vs"

2. Set Up Monitoring Tools

Choose a social listening tool that aggregates mentions across developer platforms (GitHub, Hacker News, Reddit, Stack Overflow, Twitter).

Recommended Keyword Structure:

Create separate keywords for brand, competitors, and problem spaces
Use exact match for brand names to reduce noise
Use broader matching for problem keywords
Set up negative keywords to filter irrelevant mentions

3. Platform-Specific Monitoring

GitHub:

Monitor issues mentioning your product in other repos
Track discussions in relevant GitHub Discussions
Watch for your product in awesome-lists and comparison repos
Monitor stars/forks of competitor repos for traction signals

Hacker News:

High-signal but low-volume
Comments often contain detailed technical feedback
"Show HN" and "Ask HN" posts reveal developer needs
Threads about competitors are engagement opportunities

Reddit:

r/programming, r/webdev, r/devops, r/selfhosted, etc.
Subreddit-specific cultures require tailored responses
Question threads are high-intent opportunities

Stack Overflow:

Monitor tags related to your product category
Questions reveal documentation gaps
Answers from competitors show their positioning

Twitter/X:

Real-time sentiment and virality
Developer influencer conversations
Conference and event discussions
Complaint threads often go viral

Discord:

Harder to monitor but high-signal
Join relevant community servers manually
Look for integration opportunities with popular servers

Sentiment Analysis and Prioritization

Prioritization Framework

Not all mentions deserve equal attention. Prioritize based on:

High Priority (Respond within hours):

Negative sentiment from existing users
Direct questions about your product
Complaints going viral
Competitor comparisons where you're losing
Buy-intent signals from ideal customer profiles

Medium Priority (Respond within 24-48 hours):

Neutral mentions seeking recommendations
Feature requests in public forums
Documentation confusion
Competitor criticism (potential switchers)

Low Priority (Monitor and aggregate):

General industry discussions
Competitor praise (learn from it)
Historical mentions for trend analysis

Sentiment Filtering

Most monitoring tools offer sentiment filtering. Key queries to set up:

Negative sentiment mentions from the last 30 days
High-relevance mentions that haven't been engaged with yet
Platform-specific filters (Hacker News, Reddit, Twitter)

Finding Engagement Opportunities

Types of Engagement Opportunities

Frustrated Users:

Complaining about your product = urgent support opportunity
Complaining about competitors = potential conversion
Complaining about the problem space = thought leadership opportunity

Questions and Recommendations:

Direct questions about your product
"What tool should I use for X" threads
Comparison requests

Buy Intent Signals:

"Looking for a [your category]"
"Evaluating [competitor] vs [competitor]"
"Need to migrate from [competitor]"
"Budget approved for [solution]"

Engagement Best Practices

Be helpful first, promotional second - Answer the question before mentioning your product
Disclose affiliation - "I work at [company]" builds trust
Match the platform culture - HN hates marketing speak, Reddit values authenticity
Provide value even if they don't convert - Good advice builds reputation
Don't argue with critics - Acknowledge, fix if valid, move on

Competitive Intelligence from Conversations

What to Track

Competitor Mentions:

Praise (what are they doing right?)
Criticism (opportunities for you)
Feature requests (what's missing?)
Churn signals ("migrating away from")

Positioning Shifts:

How competitors describe themselves
Which use cases they emphasize
Pricing and packaging discussions

Community Sentiment:

Overall vibe toward competitors
Developer trust levels
Support quality perception

Extracting Insights

Track trends over time using your monitoring tool's analytics:

Sentiment trends for competitors over 90 days
Mention volume comparison between your brand and top competitors
Platform breakdown (where are conversations happening?)

Tools

Social Listening

Use a monitoring tool that tracks developer platforms. Key capabilities to look for:

Multi-platform coverage (GitHub, HN, Reddit, Stack Overflow, Twitter)
Sentiment analysis
Keyword alerts and filtering
Analytics and trend tracking

Platform-Specific Tools

GitHub Search:

Use gh search issues and gh search repos for GitHub-specific monitoring
Track issues mentioning your product in other repositories

Twitter/X Search:

Advanced search operators for precise monitoring
Track specific accounts and hashtags
Tools like Typefully, TweetDeck, or Hootsuite for monitoring

Reddit:

Native Reddit search with subreddit filters
Third-party tools like Syften or F5Bot for alerts

Related Skills

competitor-tracking - Systematic competitor analysis beyond conversation monitoring
alternatives-pages - Convert competitive insights into comparison content
community-engagement - Best practices for responding to developer conversations

Frequently asked questions

What does the Developer Listening AI skill do?

Why use Developer Listening on TypingMind?

Because you install it once and use it with any model. Developer Listening 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 Developer Listening in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jonathimer/devmarketing-skills/tree/main/skills/developer-listening. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Developer Listening?

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 Developer Listening?

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

Is the Developer Listening AI skill free?

Yes. It is published on GitHub by jonathimer 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.

View all

Mem Setup

thedotmack

CommunityPopular

This skill should be used when the user asks to "set up claude-mem", "pair claude-mem", "connect cmem", "add my cmem key", "set up cloud sync in Cowork", or provides cmem.ai Connect values (sync…

Wizard

Generate an interactive bash wizard that walks a human through steps only they can perform. Use when provisioning infrastructure, setting up credentials or CI secrets, walking an unfamiliar…

Deployment Patterns

Flujos de trabajo de despliegue, patrones de pipeline CI/CD, contenedorización Docker, health checks, estrategias de rollback y listas de verificación de preparación para producción de aplicaciones…

Docker Patterns

Patrones de Docker y Docker Compose para desarrollo local, seguridad de contenedores, networking, estrategias de volúmenes y orquestación de múltiples servicios.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Developer Listening

Overview

Setting Up Your Monitoring Strategy

1. Define Your Keyword Categories

2. Set Up Monitoring Tools

3. Platform-Specific Monitoring

Sentiment Analysis and Prioritization

Prioritization Framework

Sentiment Filtering

Finding Engagement Opportunities

Types of Engagement Opportunities

Engagement Best Practices

Competitive Intelligence from Conversations

What to Track

Extracting Insights

Tools

Social Listening

Platform-Specific Tools

Related Skills

Frequently asked questions

Related AI Skills

Set up your own AI workspace now