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Skill

/resume

Resume a previous hunt. Shows hunt history, untested endpoints, memory-informed suggestions. Usage: /resume target.com

From plugin
pentest-agents
79439 skills50 agents3 hooks2 MCP
Install
$ npx -y skills add H-mmer/pentest-agents --skill resume --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/resume

Context preview

The summary Claude sees to decide when to auto-load this skill.

Resume a previous hunt. Shows hunt history, untested endpoints, memory-informed suggestions. Usage: /resume target.com

SKILL.md

resume.SKILL.md
name: resume
description: "Resume a previous hunt. Shows hunt history, untested endpoints, memory-informed suggestions. Usage: /resume target.com"
disable-model-invocation: false

Resume hunt on: $ARGUMENTS

What This Does

1. Read brain for target: `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py brief $ARGUMENTS` 2. Read brain exhausted: `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py exhausted $ARGUMENTS` 3. **Read chain-pending advisory**: `cat .claude/agent-memory-local/chain-pending.md 2>/dev/null` — feeder findings from prior session waiting for chain dispatch. SURFACE THESE FIRST — they have proven dollar value if chained, vs untested surface which is speculative. 4. **Generate / refresh chain plan**: `uv run python3 $CLAUDE_PROJECT_DIR/tools/chain_plan.py $ARGUMENTS` — writes `evidence/<target>/CHAIN_PLAN.md` with 3-5 candidate next-links per pending feeder finding plus the agent to dispatch for each. Read this BEFORE picking the next vuln class — proven feeders trump speculative untested surface. 5. Read recon data from recon/ directory 6. Show what's been tested vs what remains 7. Suggest next techniques based on brain patterns

Output

RESUME: target.com
═══════════════════

Brain Status:
  Confirmed findings: N
  Exhausted techniques: N
  Effective techniques: N

Untested Surface:
  1. /api/v2/users/{id}/export — not tested
  2. /api/v2/users/{id}/share — not tested
  ...

Suggestions:
  - Tech stack [X] matches pattern where IDOR was found before
  - Sibling endpoints of confirmed finding not yet tested

Actions:
  [h] /hunt target.com — resume hunting
  [s] /surface target.com — re-rank attack surface
  [r] /recon target.com — re-run recon (surface may have changed)
  [m] /monitor check — check for target changes since last session

Top-Tier Resume Logic

Resume by value, not chronology.

Priority order: 1. `chain-pending` confirmed feeders with clear next link 2. validated partials needing one proof artifact 3. changed assets from `/monitor` 4. untested P1 crown-jewel endpoints 5. high-confidence class hypotheses from prior wins 6. stale recon refresh

Show what not to redo. If an area is exhausted, include the exact blocker and matrix coverage. A resumed hunt should start with a single best command, not a menu of every possible command.

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Bug bounty agent framework for Claude Code, Codex, Gemini, Cursor, Windsurf, Copilot, and OpenClaw — 48 agents, 26 commands, 19 CLI tools, 2 MCP servers, autonomous hunt loops, exploit chain builder.

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