Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/hypnguyen1209/offensive-claudenpx agentmods add commands/hypnguyen1209/offensive-claude/engage.pickupWrote 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.pickup)<a href="https://agentmods.dev/commands/hypnguyen1209/offensive-claude/engage.pickup"><img src="https://agentmods.dev/badge/commands/hypnguyen1209/offensive-claude/engage.pickup/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/commands/hypnguyen1209/offensive-claude/engage.pickup"><img src="https://agentmods.dev/badge/commands/hypnguyen1209/offensive-claude/engage.pickup.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00017 | $0.00450 |
| Opus 5 | $0.00009 | $0.00225 |
| Sonnet 5 | $0.00003 | $0.00090 |
| Haiku 4.5 | $0.00002 | $0.00045 |
Grade A, and why
engage.pickup 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 10d 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.pickup
Resume an in-progress engagement. The autopilot engine writes an append-only trace
(<state>/trace.jsonl); pickup re-runs the workflow with --resume, so completed steps are
skipped and the run continues from the first unfinished step.
Usage
/engage.pickup [--workflow <name>] [--state .engage/engine]
Process
1. Locate prior run
Read <state>/trace.jsonl. Summarize: which phases/steps completed (step_done), whether the
prior run halted (budget/loop) or finished, and any operator_bump directives recorded.
2. Resume
python engine/engine.py run --workflow <name> --target <host> \
--scope .engage/scope/scope.json --state .engage/engine --resume
Completed step_ids are skipped (step_skipped_resume); the budget restarts for the new run, so
raise --max-steps/--max-seconds if the prior run halted on budget.
3. Re-orient
Before continuing manual work, reload context:
.engage/scope/scope.json— the enforced boundary.engage/recon/prior-intel.*— recalled patterns (run/engage.memory recallif stale)exploit/findings/— findings already recorded- the trace's last
step_done— where execution stopped
4. Operator bump (optional)
Drop a directive into <state>/bump.txt (e.g. "also test the staging host") before resuming; the
engine records and consumes it between steps.
Notes
- The trace is the resumable state — keep
<state>/with the engagement artifacts. - A
haltedprior run is normal (it means the budget/loop guard fired) — review the reason, adjust budget or pivot, then pick up.
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.
- 10d ago First seen · 45 lines · 17 tokens per session scan A b9e6f9b48dff
engage.pickup is a command published in the GitHub repository hypnguyen1209/offensive-claude (357 stars, last pushed 23d ago), licensed MIT. It adds 17 tokens to every session and 450 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.
Other commands, from other repositories
discover
Run a full product discovery cycle — from outcome definition through opportunity mapping, prioritisation, and experiment design. Use when the team isn't sure what to build next, or before writing a PRD for a complex feature space.
voice-compliance
Voice/telephony compliance check — invokes voice-ai-reviewer to produce TM-voice-{slug}.md with TCPA, STIR/SHAKEN, state recording-consent, EU AI Act Art. 50, and synth-voice deepfake-law gaps.
claude-tracker
List recent Claude Code sessions with live status.
qa
Smoke or browser-walk a running app. Report only. Do not implement. Do not merge.
esp-harden
Harden and inspect ESP32 firmware for field failures, crashes, memory, and security.
replication-package
Scaffold or audit a social-science replication package at a target directory, and audit the manuscript and its archived research objects against FAIR principles.