Borrowing it
Nothing to install: this file belongs to AkaraChen/aghub. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/AkaraChen/aghub/main/.claude/skills/init-deep/SKILL.mdgit clone --depth 1 https://github.com/AkaraChen/aghubWrote 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/akarachen/aghub/init-deep)<a href="https://agentmods.dev/skills/akarachen/aghub/init-deep"><img src="https://agentmods.dev/badge/skills/akarachen/aghub/init-deep/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/akarachen/aghub/init-deep"><img src="https://agentmods.dev/badge/skills/akarachen/aghub/init-deep.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00087 | $0.03911 |
| Opus 5.5 | $0.00035 | $0.01564 |
| Sonnet 5.5 | $0.00017 | $0.00782 |
| Haiku 4.5 | $0.00009 | $0.00391 |
Grade A, and why
init-deep 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 — 389 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/init-deep
Generate hierarchical AGENTS.md files. Ensure every AGENTS.md has a paired CLAUDE.md (and vice versa) via symlinks. Root + complexity-scored subdirectories + all monorepo packages.
Usage
/init-deep # Update mode: modify existing + create new where warranted
/init-deep --create-new # Read existing → remove all → regenerate from scratch
/init-deep --max-depth=2 # Limit directory depth (default: 3)
Workflow (High-Level)
- Discovery + Analysis (concurrent)
- Fire background explore agents immediately
- Main session: bash structure + LSP codemap + read existing AGENTS.md and CLAUDE.md
- Score & Decide - Determine AGENTS.md/CLAUDE.md locations from merged findings
- Generate - Root first, then subdirs in parallel
- Review - Deduplicate, trim, validate, ensure pairs
Phase 1: Discovery + Analysis (Concurrent)
Mark "discovery" as in_progress.
Fire Background Explore Agents IMMEDIATELY
Don't wait—these run async while main session works.
// Fire all at once, collect results later
task(subagent_type="explore", load_skills=[], description="Explore project structure", run_in_background=true, prompt="Project structure: PREDICT standard patterns for detected language → REPORT deviations only")
task(subagent_type="explore", load_skills=[], description="Find entry points", run_in_background=true, prompt="Entry points: FIND main files → REPORT non-standard organization")
task(subagent_type="explore", load_skills=[], description="Find conventions", run_in_background=true, prompt="Conventions: FIND config files (.eslintrc, pyproject.toml, .editorconfig) → REPORT project-specific rules")
task(subagent_type="explore", load_skills=[], description="Find anti-patterns", run_in_background=true, prompt="Anti-patterns: FIND 'DO NOT', 'NEVER', 'ALWAYS', 'DEPRECATED' comments → LIST forbidden patterns")
task(subagent_type="explore", load_skills=[], description="Explore build/CI", run_in_background=true, prompt="Build/CI: FIND .github/workflows, Makefile → REPORT non-standard patterns")
task(subagent_type="explore", load_skills=[], description="Find test patterns", run_in_background=true, prompt="Test patterns: FIND test configs, test structure → REPORT unique conventions")
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 · 389 lines · 87 tokens per session scan A d1f38e516475
init-deep is a skill published in the GitHub repository AkaraChen/aghub (272 stars, last pushed yesterday), licensed MIT. It adds 87 tokens to every session and 3,911 once invoked, about $0.0003 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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