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deepseek-harness/packages/ui/user-approval
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2026-08-05 13:09:53 +08:00
..

@deepseek-ai/dsh-user-approval

English | 中文

Channel-neutral one-shot approval seam. ctx.approval.request(req) returns allowed-once, rejected, cancelled, or unavailable; missing or failing answerers fail closed, and a grant applies only to the requested action. Exact event signatures live in the generated Cordis catalog.

Each request must belong to an open agent turn. The service appends a paired approval/asked and approval/decided audit record, while the model sees only the resulting logged tool outcome. An aborted request resolves cancelled; an audit append that fails before commit rejects rather than returning an unlogged decision.

Answerers are approval/request waterfall listeners. Return an outcome to answer for an owned agent or call next() to delegate. Agent-scoped listeners receive only that agent's requests; compose one terminal answerer per deployment because sibling listener order is not a policy priority mechanism. The ACP automation bridge supplies one-shot machine decisions for sessions it owns.

ApprovalPolicy is 'ask' or 'never'. The effective value is the last approval/policy event, falling back to config; setApprovalPolicy() is the write path. 'never' rejects before interactive dispatch. Both policies contribute their complete current meaning to the cache-safe runtime-context snapshot.

The tools pipeline routes ask decisions through this seam and fails closed when it is absent; the sandboxed bash tool also uses it for escalated retries. The ACP automation bridge answers calls for its own agents through the client's machine policy. Audit events remain log-only, so the model sees only the asking consumer's result. See the approval-seam Agent Note and sandbox Agent Note.

Model Experience

Current approval policy context

What the model sees

The first request and each effective policy change append a full runtime-context snapshot after retained history. Under ask, the approval contribution states that configured answerers may be consulted and absence fails closed. Under never, it states the deterministic rejection and non-escalation consequence. Unchanged requests retain the earlier snapshot without adding another message.

Ask-policy contribution
Approval policy: ask. Operations that require approval may ask through the configured answerers; without an available answerer, the request fails closed.
Never-policy contribution
Approval prompts are disabled in this session: actions that require approval are rejected automatically — do not request sandbox escalation (do not set `sandbox_permissions`).

Token effect

One concise context message on the first request and on an effective change; unchanged requests add no duplicate policy tokens.

KV Cache effect

Append-only after retained history. An ask/never switch preserves the stable system and conversation prefix instead of rewriting the first wire message.

Tool outcome

What the model sees

approval/asked and approval/decided are log-only. The model sees only the asking consumer's eventual allowed, rejected, cancelled, or unavailable tool outcome; the human permission UI is not context.

Token effect

Zero duplicate audit tokens. A rejection may replace a normal tool result with a small retained error, while an allowance leaves the consumer's ordinary result.

KV Cache effect

Append-only; newly visible content follows the reusable request prefix and does not invalidate existing KV-cache entries.

Known Limitations and Deferred Work

  • Requests are valid only inside an open turn — an idle or between-turn caller throws before auditing; a durable out-of-turn approval workflow is deferred.
  • Only one-shot grants exist — the outcome vocabulary has allowed-once but no allow-always, remembered rule, revocation, or grant store; session policy is only ask / never.
  • The request carries no tool arguments — an answerer sees the tool name, reason, and optional call id; the ACP machine channel requires a call id and delegates requests without one.
  • No built-in answerer — headless or incompletely composed deployments resolve unavailable and fail closed; the service itself never prompts a human.