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/hypnguyen1209/offensive-claudeWrote 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/hypnguyen1209/offensive-claude/engage.init)<a href="https://agentmods.dev/commands/hypnguyen1209/offensive-claude/engage.init"><img src="https://agentmods.dev/badge/commands/hypnguyen1209/offensive-claude/engage.init.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 | $0.00010 | $0.00326 |
| Opus 5 | $0.00005 | $0.00163 |
| Sonnet 5 | $0.00002 | $0.00065 |
| Haiku 4.5 | $0.00001 | $0.00033 |
Grade A, and why
engage.init 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 8d 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.
What it actually says
/engage.init
Initializes a new engagement project with the selected workflow preset.
Usage
/engage.init <workflow-type> --client <client-name> [--date YYYY-MM-DD]
Workflow Types
web-app— Web application pentest (OWASP-focused)network— Internal network pentestred-team— Full red team engagement (all 9 phases)cloud— Cloud security audit (AWS/Azure/GCP)mobile— Mobile application pentest (Android/iOS)ad-domain— Active Directory domain assessmentbug-bounty— Bug bounty hunting
Process
- Load the selected workflow YAML from
workflows/<type>.yml - Create engagement directory:
engagement-<client>-<date>/ - Create
.engage/state.jsonwith engagement metadata - Copy phase templates from
templates/<phase>/based on workflow - Create
evidence/subdirectories (screenshots, pcaps, logs) - Print status and suggest
/engage.scopeas next step
State File Structure
The .engage/state.json tracks:
- Engagement metadata (client, date, workflow type)
- Current phase (0-8)
- Phase completion status
- Gate validation results
- Findings count per phase
Next Steps
After initialization, run /engage.scope to begin Phase 0 (Scope Definition).
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.
- 8d ago First seen · 44 lines · 10 tokens per session scan A 60dbb4e1fa3d
engage.init is a command published in the GitHub repository hypnguyen1209/offensive-claude (357 stars, last pushed 21d ago), licensed MIT. It adds 10 tokens to every session and 326 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 2026-08-30.
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