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.
git clone --depth 1 https://github.com/TechNickAI/ai-coding-configWrote 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/commands/technickai/ai-coding-config/product-intel)<a href="https://agentmods.dev/commands/technickai/ai-coding-config/product-intel"><img src="https://agentmods.dev/badge/commands/technickai/ai-coding-config/product-intel/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/commands/technickai/ai-coding-config/product-intel"><img src="https://agentmods.dev/badge/commands/technickai/ai-coding-config/product-intel.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 | $0.00016 | $0.01744 |
| Opus 5.5 | $0.00006 | $0.00698 |
| Sonnet 5.5 | $0.00003 | $0.00349 |
| Haiku 4.5 | $0.00002 | $0.00174 |
Grade A, and why
product-intel 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 25d 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 — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Intelligence Research
Run comprehensive product intelligence research on competitors, industry trends, and opportunities.
$ARGUMENTS
Actionability first: Every finding should answer "so what?" If it doesn't inform a decision, it doesn't belong.
Recency matters: Focus on the last 30-60 days. Archive older news.
Trust but verify: Cross-reference claims. Official sources over rumors.
Stay objective: Report what you find, not what you hope to find.
When creating this structure for the first time, create:
/product-intel/research-settings.md(with frontmatter for settings)/product-intel/competitors/(will be populated during discovery)/product-intel/topics/(will be populated during discovery)/product-intel/opportunities/(for tracking insights)
# [Company Name]
**Last Checked**: YYYY-MM-DD **Website**: [url] **Positioning**: One-sentence value prop
## Overview
Brief description of what they do and how they compete.
## Recent Activity
### YYYY-MM-DD: [Headline]
- **Source**: [link]
- **Impact**: High/Medium/Low
- **Details**: What happened and why it matters
## Feature Comparison
| Feature | Them | Us | Notes |
| ------- | ---- | --- | ----- |
| ... | ✅ | ❌ | ... |
## Strengths
- What they do well
## Weaknesses
- Where they fall short
## Opportunities for Us
- What we can learn or counter
Topic files (/product-intel/topics/[topic-slug].md):
# [Topic Name]
**Last Checked**: YYYY-MM-DD **Relevance**: Why this matters to the project
## Recent Developments
### YYYY-MM-DD: [Headline]
- **Source**: [link]
- **Impact**: High/Medium/Low
- **Summary**: What changed and implications
## Key Resources
- [Official spec](url)
- [Documentation](url)
## Action Items
- [ ] Things we should consider based on these developments
Understanding the product means extracting its essence from repository files. Read README, package.json, and project documentation to grasp what problem this solves, who it's for, and what technologies it uses. This context shapes everything else.
Finding competitors requires thinking like a product manager. Search for alternatives to the value proposition, comparison articles, and community discussions about similar tools. Prioritize companies with funding, active development, and real market presence. Create files for the top 5-8 most relevant competitors.
Discovering topics means identifying what technologies and trends matter to this product. Look at dependencies, protocols mentioned in docs, and industry-specific developments. Focus on 3-5 core topics that directly impact the product's strategy or technical direction.
Maintaining Intelligence:
Competitor research should uncover what they've shipped, how they're positioning themselves, and where they're strong or weak. Use official sources first (changelogs, blogs, docs), then community signals, then news. Look for changes that create opportunities or threats. Update files with dated, sourced findings that answer "so what?"
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.
- 25d ago First seen · 228 lines · 16 tokens per session scan A b4aace21c73f
product-intel is a command published in the GitHub repository TechNickAI/ai-coding-config (24 stars, last pushed 26d ago), licensed MIT. It adds 16 tokens to every session and 1,744 once invoked, about $0.0001 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 2026-09-22.
Other commands, from other repositories
destination
Set, clear, or show the workspace prompts destination — use this when running claude above multiple repos and you want all prompts to land in one shared store.
doctor
Diagnose Promptcellar — check hook binaries, plugin wiring, resolved config.
log
Show the last N captured prompts in this repo (git-log style, defaults to 10).
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.