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 agentmods add commands/deepfusionlabs/deep-init/fastgit clone --depth 1 https://github.com/deepfusionlabs/deep-initWhat 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 | $0.00026 | $0.00152 |
| Opus 5 | $0.00013 | $0.00076 |
| Sonnet 5 | $0.00005 | $0.00030 |
| Haiku 4.5 | $0.00003 | $0.00015 |
Grade A, and why
fast 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.
What it actually says
Run the deep-init skill for a full analysis in fast review mode (0 review cycles + the token-saving heuristics). Load skills/deep-init/SKILL.md, read references/global-rules.md first, then execute the pipeline (Detect → Plan → Extract → Filter → Redact → Verify → Emit, with the report-only issue pass). Equivalent to deep-init fast: only the review-cycle count is turned down — everything else keeps the max-quality defaults (issue detection + report + SARIF on). Honour any additional flags the user passes.
$ARGUMENTS
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 · 8 lines · 26 tokens per session scan A b6c71502e438
fast is a command published in the GitHub repository deepfusionlabs/deep-init (6 stars, last pushed 12d ago), licensed MIT. It adds 26 tokens to every session and 152 once invoked, about $0.0001 per session on Opus 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 2026-08-31.
Other commands, from other repositories
fleet-conformance
Scan every repo on the machine for guardrails, testing, and observability conformance; audit the deltas semantically; produce a fleet report; and propose canary-first remediation.
claude-md-migrate
Rewrite a bloated or stale CLAUDE.md into a lean, verified "map, not wishes" file — nothing invented, hard rules preserved verbatim.
claude-md-new
Scaffold a CLAUDE.md for this repo from battle-tested templates, filled in with the project's real commands.
implement-review
One agent implements a task, then reviews its own work behind a hard verification gate before finalizing.
project-init
Stand up the context layers for a project — a thin pointer-style AGENTS.md plus seed compass maps — without touching the memory layer.
claude-md-audit
Grade this repo's CLAUDE.md / AGENTS.md (0–100) and return a worst-first fix list.