TapPass governance for DeepSeek Harness

The authority layer for agentic AI, as a DeepSeek Harness plugin.

Everything in DeepSeek Harness is a plugin. This is the one that decides what
your agents are allowed to do.

Guardrails and safety classifiers ask "is this output harmful?" That is a
property of the model. TapPass asks a different question: "is this agent
allowed to do this, under our rules, right now?" That is a property of
your business, and no model level tool can answer it, because the answer lives
in your organisation, not in the weights.

This plugin intercepts every tool call at the harness's tools/pre-execute
seam, sends it to the TapPass policy decision point (POST /v1/govern), and
allows, denies, or escalates it for human approval.

Why it is different

• Business rules, not model safety. Write the rule once, in your language:
  "refunds over 500 need a human", "no customer PII leaves the EU region", "this
  agent may read the CRM, never write it". It is enforced on every tool call, on
  every harness, under every model. A prompt is a suggestion. A policy is a fact.
• Authority is earned. The plugin ships in observe mode: from the first
  minute it watches and records every call, and blocks nothing. You see what
  your agents do before you enforce a single deny. Then you turn on enforcement
  for what matters. Autonomy is a track record, not a checkbox.
• Harness and model agnostic. The same rules that govern an agent here
  govern it in Claude Code, in Codex, behind LiteLLM. The harness is
  interchangeable. The authority is not.
• EU hosted, EU AI Act ready.

Install

# create a profile if you do not have one, then add the plugin
dsh plugin --profile default add @tappass/dsh-governance

# point it at your TapPass workspace
export TAPPASS_API_KEY="tp_dev_..."      # a TapPass developer key

# verify the layer without booting, then run
dsh --profile default --dump-config
dsh --profile default

Get a developer key from your TapPass dashboard (Settings, Developer keys) or
POST /api/agents/{agent}/developer-keys. The key is bound to one agent and one
org; TapPass records the audit trail against it.

Configure

Every tool call is governed once it is installed. Configuration is optional; the
defaults are safe.

Set them in your profile's patch, for example to enforce:

# $DSH_HOME/profiles/default/cordis.patch.yml
- tappass-governance:
    config:
      mode: enforce

How a verdict becomes a decision

In observe mode every call returns next(), but a would-be block or approval
is still recorded server side and logged locally, so you can size your policy
against real traffic before enforcing.

The plugin sends its mode with each call (enforcement.mode), so the audit
trail can show an observe-mode block distinctly from an enforced one.

Honest limitations

• No argument rewriting. DeepSeek Harness makes tool arguments read only at
  tools/pre-execute by design (they are already logged and shown to the
  model), so a TapPass modify verdict cannot be applied in place. This plugin
  fails such a call closed in enforce mode with a clear reason rather than
  silently running the unmodified request. Redaction obligations are surfaced,
  not applied.
• Approval needs an open turn. A needs_approval verdict maps to the
  harness ask decision, which routes to whatever approval answerer your
  profile mounts. With no approver configured, ask fails closed to a denial,
  which is the safe default.
• Developer preview. DeepSeek Harness and its plugin API are pre-release and
  may change. This plugin is deliberately thin: it is a bridge to /v1/govern,
  so if the harness API shifts the fix is a small shim, not a rewrite.

Develop

npm install --legacy-peer-deps   # dsh rc packages have skewed peer ranges
npm run build
node --test

The verdict mapping and the /v1/govern client are covered by
test/plugin.test.mjs and run against a local mock server, no TapPass instance
required.

Links

• TapPass: https://tappass.ai
• The authority layer for agentic AI. Authority is earned. Even by AI.

License

MIT © Cogniqor BV (TapPass)