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/fatihkan/badiWrote 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/fatihkan/badi/market)<a href="https://agentmods.dev/commands/fatihkan/badi/market"><img src="https://agentmods.dev/badge/commands/fatihkan/badi/market.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00789 |
| Opus 5 | $0.00000 | $0.00394 |
| Sonnet 5 | $0.00000 | $0.00158 |
| Haiku 4.5 | $0.00000 | $0.00079 |
Grade A, and why
market 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 yesterday.
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 — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Market & demand research command. Discovers niches, sizes opportunity, and reads competitor/demand signals BEFORE you build — via the market-researcher agent, with the badi market CLI for App Store data.
Required Tools
- Read (context, memory, prior research)
- Grep / Glob (find related notes and prior decisions)
- Bash (
badi marketfor App Store discover/reviews/difficulty) - Agent (delegate to market-researcher)
When to Use
Before committing to a product, feature, or niche — when the question is "is there demand, who is it for, and is the space winnable?". Pairs with /ceo-review (should we build it) and /aso + /seo (once you're in-market). For pure App Store metrics, badi market alone is enough; use /market when you want a synthesized opportunity read.
Procedure
Step 1: Frame the Question
- State the niche/keyword/category and the decision it informs in one sentence.
- Read
memory.md/ prior research notes for what's already known.
Step 2: Pull Hard Data (optional, App Store)
- Run
badi market discover <keyword>,badi market reviews <appId>, and/orbadi market difficulty <keyword>for concrete App Store signals (ratings, review themes, ranking difficulty, wishlist/gaps). - Capture the raw numbers so the agent reasons from data, not vibes.
Step 3: Delegate to Market Researcher
Launch the market-researcher agent (read-only; WebSearch/WebFetch + the data from Step 2). Ask it to:
- Size the opportunity — read search/category volume as a FLOOR (2026 zero-click + AI query fan-out undercount latent demand), triangulated with TikTok trend velocity, community pain-points, and marketplace purchase-intent search; note the trend direction.
- Identify the target user and the job-to-be-done.
- Map competitors and find the gap (under-served segment, weak incumbents, unmet need) — and check AI-answer citation presence (ChatGPT/Gemini/Perplexity), not just SERP rank: the two diverge in 2026.
- Surface the risks and what would tell us to walk away.
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.
- yesterday First seen · 49 lines · 0 tokens per session scan A 2a22b8967735
market is a command published in the GitHub repository fatihkan/badi (7 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 789 tokens. 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 2026-09-06.
Other commands, from other repositories
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check-cache-bugs
Audit Claude Code setup for cache bugs (CC#40524) — sentinel, --resume/--continue, attribution header + ArkNill B3/B4/B5.
land-and-deploy
Merge PR, wait for CI, verify deploy, run canary — the complete landing pipeline.
qa
Systematic QA testing of a web application — diff-aware, tiered, with fix-and-verify loop.
review-pr
Perform a comprehensive code review of a pull request.
security-audit
Comprehensive security audit with scored posture assessment.