/quickscan
Run a quick security scan on a target. Consults the Brain first, validates scope, runs passive recon + vuln scan in parallel.
$ npx -y skills add H-mmer/pentest-agents --skill quickscan --agent claude-codeHow 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
/quickscan
Context preview
The summary Claude sees to decide when to auto-load this skill.
Run a quick security scan on a target. Consults the Brain first, validates scope, runs passive recon + vuln scan in parallel.
SKILL.md
quickscan.SKILL.mdname: quickscan
description: "Run a quick security scan on a target. Consults the Brain first, validates scope, runs passive recon + vuln scan in parallel."
disable-model-invocation: false
ALL agents dispatched by this command MUST use `model: "inherit"` in the Agent tool call.
Run a quick security assessment on: $ARGUMENTS
Workflow: 1. **Brain**: `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py brief $ARGUMENTS` — check what we already know. Note exhausted areas. 2. **Scope**: `uv run python3 $CLAUDE_PROJECT_DIR/tools/scope_check.py $ARGUMENTS` — if out of scope, STOP. 3. Launch IN PARALLEL (skip areas the brain marks EXHAUSTED):
- `recon` agent with passive-only depth, passing brain context about known subdomains/tech
- `config-auditor` agent for headers, CSP, CORS, TLS, cookies
4. Record results: for each new finding, run `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py record <target> <status> <technique> <details>` 5. Log session: `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py log "quickscan completed on $ARGUMENTS"` 6. Summarize: separate NEW findings from KNOWN, recommend next steps.
Top-Tier Quickscan Loop
Quickscan should answer "is there obvious money or obvious risk here in 30 minutes?"
1. Spend the first five minutes on scope, policy headers, brain, and live host sanity. 2. Spend the next ten on high-signal passive recon: JS routes, exposed APIs, auth flows, cloud/storage names, source maps, security headers, and known vendor panels. 3. Spend ten on two targeted probes only: the best config/information leak candidate and the best auth/tenant-boundary candidate. 4. Spend five on triage: new, known, killed, or needs full hunt.
Never report from quickscan alone unless the proof is already complete. Promote strong leads to `/hunt`, `/validate`, or `/chain`.
Read more
name: quickscan description: "Run a quick security scan on a target. Consults the Brain first, validates scope, runs passive recon + vuln scan in parallel." disable-model-invocation: false
ALL agents dispatched by this command MUST use `model: "inherit"` in the Agent tool call.
Run a quick security assessment on: $ARGUMENTS
Workflow: 1. **Brain**: `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py brief $ARGUMENTS` — check what we already know. Note exhausted areas. 2. **Scope**: `uv run python3 $CLAUDE_PROJECT_DIR/tools/scope_check.py $ARGUMENTS` — if out of scope, STOP. 3. Launch IN PARALLEL (skip areas the brain marks EXHAUSTED):
- `recon` agent with passive-only depth, passing brain context about known subdomains/tech
- `config-auditor` agent for headers, CSP, CORS, TLS, cookies
4. Record results: for each new finding, run `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py record <target> <status> <technique> <details>` 5. Log session: `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py log "quickscan completed on $ARGUMENTS"` 6. Summarize: separate NEW findings from KNOWN, recommend next steps.
Top-Tier Quickscan Loop
Quickscan should answer "is there obvious money or obvious risk here in 30 minutes?"
1. Spend the first five minutes on scope, policy headers, brain, and live host sanity. 2. Spend the next ten on high-signal passive recon: JS routes, exposed APIs, auth flows, cloud/storage names, source maps, security headers, and known vendor panels. 3. Spend ten on two targeted probes only: the best config/information leak candidate and the best auth/tenant-boundary candidate. 4. Spend five on triage: new, known, killed, or needs full hunt.
Never report from quickscan alone unless the proof is already complete. Promote strong leads to `/hunt`, `/validate`, or `/chain`.
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.
Repo: H-mmer/pentest-agents
Other skills on pentest-agents.
- /analyze
Analyze recon output with AI to suggest high-value targets and attack strategies. Usage: /analyze <target>
Open skill - /autopilot
Autonomous hunt orchestrator. INSATIABLE in --autonomous mode: enforces an EXHAUSTION CONTRACT (26 canonical hunter classes, surface probe A-I, depth-engine ≥25 attempts/class, wall-clock floor 90 min/target, PRE-COMPLETION GATE before any summary). No early stops, no clarifying
Open skill - /brain
Manage the engagement brain. Subcommands: 'init' to set up, 'brief <target>' for pre-flight, 'status' for overview, 'exhausted [target]' to see dead ends.
Open skill - /chain
Build deep exploit chains — dispatches chain-builder agent. Given bug A, recursively walks the chain graph. Usage: /chain (then describe bug A)
Open skill - /correlate
Run the finding correlation engine to discover attack chains from individual findings.
Open skill - /cost
Show cost tracking and ROI for this engagement.
Open skill

