Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add jonathimer/devmarketing-skills --skill developer-listeninggit clone --depth 1 https://github.com/jonathimer/devmarketing-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jonathimer/devmarketing-skills/developer-listening)<a href="https://agentmods.dev/skills/jonathimer/devmarketing-skills/developer-listening"><img src="https://agentmods.dev/badge/skills/jonathimer/devmarketing-skills/developer-listening/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jonathimer/devmarketing-skills/developer-listening"><img src="https://agentmods.dev/badge/skills/jonathimer/devmarketing-skills/developer-listening.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00096 | $0.01548 |
| Opus 5.5 | $0.00038 | $0.00619 |
| Sonnet 5.5 | $0.00019 | $0.00310 |
| Haiku 4.5 | $0.00010 | $0.00155 |
Grade A, and why
developer-listening scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 224 lines · 96 tokens per session scan A 27ff98538391
developer-listening is a skill published in the GitHub repository jonathimer/devmarketing-skills (87 stars, last pushed 7mo ago), licensed MIT. It adds 96 tokens to every session and 1,548 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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