remember

Agent Skills › H-mmer/pentest-agents › remember

remember

GitHub

将漏洞发现或模式记录到持久化大脑记忆中。自动填充会话上下文，支持确认、拒绝或部分结果，并同步至全局大脑以积累跨目标的技术知识，防止重复工作。

.claude/skills/remember/SKILL.md H-mmer/pentest-agents

Trigger Scenarios

用户希望保存当前发现的漏洞或安全模式需要记录被拒绝的测试用例或阻塞原因

Install

npx skills add H-mmer/pentest-agents --skill remember -g -y

More Options

Non-standard path

npx skills add https://github.com/H-mmer/pentest-agents/tree/main/.claude/skills/remember -g -y

Use without installing

npx skills use H-mmer/pentest-agents@remember

指定 Agent (Claude Code)

npx skills add H-mmer/pentest-agents --skill remember -a claude-code -g -y

安装 repo 全部 skill

npx skills add H-mmer/pentest-agents --all -g -y

预览 repo 内 skill

npx skills add H-mmer/pentest-agents --list

SKILL.md

Frontmatter

{
    "name": "remember",
    "description": "Log a finding or pattern to persistent brain memory. Auto-fills from session context. Usage: \/remember",
    "disable-model-invocation": false
}

Save current finding/pattern to brain memory.

Flow

Read current session context — what target, endpoint, vuln class
Ask user to confirm or edit:
- Target: (auto-detected)
- Endpoint: (from session)
- Vuln class: (from session)
- Result: confirmed / rejected / partial
- Severity: critical / high / medium / low
- Bounty: $___
- Notes: ___
Write to brain:
- If confirmed: uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py record <target> confirmed "<description>" "<details>"
- If rejected: uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py record <target> exhausted "<what failed>" "<why>"
Sync to global brain: uv run python3 $CLAUDE_PROJECT_DIR/tools/global_brain.py learn technique "<pattern>"
Track response if submitted: uv run python3 $CLAUDE_PROJECT_DIR/tools/response_tracker.py log <id> <status>

Why This Matters

/resume shows which endpoints you've tested and which remain
Cross-target learning: patterns from target A inform hunting on target B
Global brain accumulates technique knowledge across all engagements

Top-Tier Recall Standard

Before writing memory, make it useful to a future agent that has no conversation context.

Use this shape:

target:
surface:
vuln_class:
primitive:
accounts_or_roles:
evidence_path:
request_summary:
response_marker:
impact:
status:
next_action:

If the item is rejected, preserve the blocker with the same care as a finding. High-quality negative memory prevents duplicate work and false confidence.