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/onboard)<a href="https://agentmods.dev/commands/fatihkan/badi/onboard"><img src="https://agentmods.dev/badge/commands/fatihkan/badi/onboard.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 | $0.00746 |
| Opus 5 | $0.00000 | $0.00373 |
| Sonnet 5 | $0.00000 | $0.00149 |
| Haiku 4.5 | $0.00000 | $0.00075 |
Grade A, and why
onboard 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 today.
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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project onboarding command. For adapting to a new project quickly and thoroughly.
Required Tools
- Glob (file structure scan)
- Read (file reading)
- Grep (code search)
- Bash (git history, dependencies)
- Write (onboarding report)
Procedure (6 Steps)
Step 1: Project Verification
- Verify the project root directory
- Check for
README.md,CONTRIBUTING.md,CHANGELOG.md - Check the license file
- Review
.gitignoreand.editorconfig
Step 2: 3 Parallel Scans
Scan A: Structure Analysis
- Extract the directory tree (2 levels deep)
- Identify the source directories (src, lib, app, etc.)
- Find the test directories (test, tests, spec, etc.)
- List the configuration files
- Find CI/CD files (.github, .gitlab-ci, Jenkinsfile, etc.)
- Detect Docker files
Scan B: Technology Detection
- Read the manifest files (package.json, Cargo.toml, pyproject.toml, go.mod, etc.)
- List frameworks and libraries
- Collect version information
- Identify the dev tooling (linter, formatter, bundler)
- Detect the database technology (migration files, ORM configuration)
Scan C: Documentation Scan
- Find all markdown files
- Look for API documentation (OpenAPI, Swagger, etc.)
- Comment density analysis (JSDoc, docstrings, etc.)
- Environment variable documentation (.env.example)
- Are there Architecture Decision Records (ADRs)?
Step 3: Dependency Analysis
- List direct dependencies
- Separate the dev dependencies
- Detect outdated dependencies
- Check security advisories (npm audit, cargo audit, etc.)
- Sketch the dependency graph (relationships between main modules)
Step 4: Code Patterns
Detect the patterns in use:
- Architectural pattern (MVC, MVVM, Clean Architecture, Hexagonal, etc.)
- Error-handling approaches (try-catch patterns, Result types, etc.)
- Logging strategy
- Test strategy (unit, integration, e2e ratios)
- Naming conventions
- Import/export patterns
- State-management approaches
Step 5: Git Archaeology
- Find the most-changed files (last 3 months)
- Identify the main contributors
- Analyze the branch strategy (main, develop, feature, etc.)
- Detect the commit message format (conventional commits, etc.)
- Find the last release date and version
- Determine the merge/rebase strategy
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.
- today First seen · 120 lines · 0 tokens per session scan A 1f2eb6582884
onboard is a command published in the GitHub repository fatihkan/badi (7 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 746 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
plan-start
5-phase planning command: PRD analysis, design review, technical decisions, dynamic research team, metrics. Produces a complete implementation plan + ADRs before any code is written.
plan-ceo-review
Strategic product gate — challenge the brief, find the 10-star product hiding inside the request, before writing any code.
routines-discover
Analyzes the current project to surface high-value Routines use cases across the three trigger types (schedule, API, GitHub events). Usage: /routines-discover.
check-cache-bugs
Audit Claude Code setup for cache bugs (CC#40524) — sentinel, --resume/--continue, attribution header + ArkNill B3/B4/B5.
review-pr
Perform a comprehensive code review of a pull request.
git-worktree-clean
Clean up stale git worktrees with merged branch detection and disk usage report.