MCPInstall

deepsec

by vercel-labs OfficialDevOps & Cloud

Run DeepSec against a Vercel project checkout from dev3000. Use for one-click DeepSec setup, project context bootstrapping, bounded first-pass processing, and report generation.

Installs
87
Last 24h
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Trending rank
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Security
Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/vercel-labs/dev3000 --skill deepsec
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads deepsec automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

DeepSec Dev3000 Runbook

Use this skill to turn the manual DeepSec workflow into a repeatable dev3000 run against the current Vercel project checkout.

Operating Policy

  • Work from the real project checkout at /workspace/repo.
  • Do not write AI credentials into .deepsec/.env.local or any tracked file. The dev3000 runtime passes AI Gateway credentials through the process environment.
  • Default dev3000 runs are a bounded first pass. Do not run an unbounded process or revalidate command unless the user explicitly asks for a full DeepSec scan in run-specific instructions.
  • Keep generated scan state in the locations DeepSec already gitignores. Commit only the durable setup/context files and human-readable findings report.
  • Treat DeepSec as a coding agent with shell access. Do not run it on untrusted source inputs.

Default Flow

  1. Inspect the project shape:
    • Read README.md if present.
    • Read AGENTS.md or CLAUDE.md if present.
    • Skim representative files for auth, middleware, request handlers, data access, billing, webhooks, and security-sensitive boundaries.
  2. Initialize DeepSec if needed:
    • If .deepsec/ is absent, run npx --yes deepsec@latest init.
    • If .deepsec/ already exists, do not force overwrite it.
  3. Install DeepSec workspace dependencies:
    • Run corepack pnpm install from .deepsec/.
    • Ensure the Claude Agent SDK native binary that DeepSec actually uses is available. Do not run a Claude Code postinstall; DeepSec uses @anthropic-ai/claude-agent-sdk.
    • If corepack pnpm is unavailable, run pnpm install only after confirming pnpm exists.
  4. Fill the generated project context:
    • Read .deepsec/node_modules/deepsec/SKILL.md.
    • Read .deepsec/data/<id>/SETUP.md.
    • Replace .deepsec/data/<id>/INFO.md with concise project-specific context.
    • Keep INFO.md to roughly 50-100 lines.
    • Use 3-5 examples per section. Name local primitives such as auth helpers, middleware, database clients, webhook handlers, and privileged APIs.
    • Do not include line numbers, generic CWE lists, or broad framework summaries.
  5. Run the scan:
    • Run corepack pnpm deepsec scan from .deepsec/.
  6. Run bounded AI processing:
    • Default command: corepack pnpm deepsec process --limit 25 --concurrency 2 --batch-size 3.
    • If the candidate set is below the limit, state that all discovered candidates were processed.
    • If the user explicitly requested a full run, use the requested limit/concurrency or omit --limit.
    • If the process command fails, stop and report the failure. Do not generate a manual fallback report from regex candidates.
  7. Generate the findings report:
    • Run corepack pnpm deepsec export --format md-dir --out ./findings.
    • If there are no findings, create .deepsec/findings/README.md summarizing that this bounded pass found no findings and include the exact commands that were run.
  8. Summarize the run:
    • Include commands run, project id, limit/concurrency, and whether the report contains findings.
    • Do not include a "Next Steps - Full Scan" section by default.
    • Only include a follow-up scan section if DeepSec reports unprocessed candidates or the user explicitly asked about deeper coverage. Label it "Optional Deeper Follow-Up" and explain exactly how it differs from the completed run.

Validation

  • Prefer DeepSec's own command output, corepack pnpm deepsec status, and generated finding files as validation.
  • Do not start a dev server or browser unless the user explicitly asks for visual/runtime verification.
  • Before finishing, check git diff --stat and make sure no secrets, node_modules, .env.local, or raw scan state are staged by accident.

FAQ

What does the deepsec skill do?

Run DeepSec against a Vercel project checkout from dev3000. Use for one-click DeepSec setup, project context bootstrapping, bounded first-pass processing, and report generation.

How do I install deepsec?

Run npx skills add https://github.com/vercel-labs/dev3000 --skill deepsec in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/deepsec/ (personal) or .claude/skills/deepsec/ (project).

Which AI agents can use deepsec?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is deepsec safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains deepsec?

It is published by vercel-labs in vercel-labs/dev3000, and it is an official skill from the maker of the technology it covers. It has 87 recorded installs.

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