T3MP3ST Team Preview

July 2, 2026 ยท View on GitHub

This preview is for prompt engineers, red-teamers, bug bounty operators, cyber researchers, and builders who want to pressure-test T3MP3ST before a broader release.

The useful mental model: T3MP3ST is an evidence-first adversarial AI command center. It is not only a scanner UI. It routes a mission into specialist agent lanes, binds tool output to evidence, promotes evidence into findings, retests claims, and only then proposes durable learning.

Ten-Minute First Run

npm install
npm run doctor
npm run server

Open http://127.0.0.1:3333/ui/.

In the UI:

  1. Click preflight.
  2. Click sync arsenal.
  3. Click activation.
  4. Pick a guided start.
  5. Run plan tools.
  6. Log one evidence item, seed a hypothesis, and use the Watch Loop pulse to see what is missing.
  7. Click Watch Loop nudge to split the hypothesis into work orders, complete one task, promote it, and queue one retest.
  8. Run gate and bundle.
  9. Run review run in the Learning Capsule.

Expected state on a fresh machine:

  • The UI should load even without an LLM key.
  • LLM calls should fail closed with a clear message.
  • The arsenal should distinguish catalog tools, wired adapters, and locally installed tools.
  • Missing binaries should be shown as activation work, not hidden as success.

What Is Real Today

  • Express API server and static command-center UI.
  • Mission drafts, route previews, mission bundles, and mission gates.
  • Resource packs, agent prompt packs, operator runbooks, and forefront pressure lanes.
  • Tool adapter catalog with execution modes, evidence kinds, install hints, and receipt gates.
  • ScopeGuard approvals for active or networked operations.
  • Evidence, hypothesis graph, hunt queue work orders, findings, retests, and accepted-memory proposal flow.
  • Watch Loop pulses that surface stale hypotheses, receipt gates, missing disproof, open work orders, retest gaps, and learning proposals.
  • Full local smoke scripts for API, arsenal, field drills, exploit-chain simulation, and prompt packs.

What Is Preview

  • Specialist agents are represented by route contracts, prompt packs, runbooks, and orchestration surfaces; production multi-agent execution still needs provider configuration and deeper harness hardening.
  • Some Pliny Specials endpoints use synthetic payloads or local-safe demos to validate orchestration shape.
  • Catalog-only tools are intentionally modeled but not executable through generic command dispatch.
  • Installed tool readiness depends on the local workstation; see docs/ARSENAL_ACTIVATION_PLAN.md.

Demo Missions

Run all local-safe demos:

npm run field:drill
npm run exploit:smoke
npm run arsenal:smoke
npm run prompt:audit

Run one focused field drill:

npm run field:drill -- --scenario=local-web-api
npm run field:drill -- --scenario=repo-supply-chain
npm run field:drill -- --scenario=ai-agent-boundary

Use examples/demo-missions.json for plain-language mission seeds that can be copied into the Mission Contract box.

Feedback We Want

  • Where does the UI make the operator feel uncertain?
  • Which mission family needs the next real adapter?
  • Which prompt pack has the strongest or weakest evidence contract?
  • Which hypothesis, work-order, finding, retest, or learning states feel ambiguous?
  • Which Watch Loop signals are actionable, noisy, or missing from the always-on hunt?
  • Which features look real but should be labeled as preview?
  • Which workflow should be one click easier for nontechnical operators?

Ship Gate For Team Builds

Before pushing a team preview branch, run:

npm run typecheck
npm test
npm run doctor
npm run arsenal:smoke

If the API is not running, doctor still checks local files and commands. If the API is running, it also checks health, preflight, arsenal status, and activation metadata.