feat(goal): add human goal command
This commit is contained in:
Tianyi Cui
@@ -1,5 +1,5 @@
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{"jsonrpc":"2.0","id":1,"result":{"protocolVersion":1,"agentInfo":{"name":"deepseek-harness-acp","version":"0.0.1"},"agentCapabilities":{"loadSession":true,"promptCapabilities":{"image":false,"audio":false,"embeddedContext":false}},"authMethods":[]}}
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{"jsonrpc":"2.0","method":"session/update","params":{"sessionId":"{{sessionId}}","update":{"sessionUpdate":"available_commands_update","availableCommands":[]}}}
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{"jsonrpc":"2.0","method":"session/update","params":{"sessionId":"{{sessionId}}","update":{"sessionUpdate":"available_commands_update","availableCommands":[{"name":"goal","description":"set or view the goal for a long-running task","input":{"hint":"[<objective>|clear|edit <objective>|pause|resume]"}}]}}}
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{"jsonrpc":"2.0","id":2,"result":{"sessionId":"{{sessionId}}","configOptions":[{"id":"model","name":"Model","description":"Sets this session's provider and model.","category":"model","type":"select","currentValue":"[\"deepseek\",\"deepseek-v4-flash\"]","options":[{"value":"[\"deepseek\",\"deepseek-v4-flash\"]","name":"deepseek-v4-flash"},{"value":"[\"deepseek\",\"deepseek-v4-pro\"]","name":"deepseek-v4-pro"}]},{"id":"permission","name":"Permissions","description":"The session permission preset: each choice bundles a sandbox mode and an approval policy.","category":"mode","type":"select","currentValue":"danger-full-access","options":[{"value":"workspace-write","name":"workspace-write","description":"Write inside the workspace and permitted temporary directories; wider retries require approval."},{"value":"danger-full-access","name":"danger-full-access","description":"Full file access without approval prompts."}]}]}}
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{"jsonrpc":"2.0","method":"session/update","params":{"sessionId":"{{sessionId}}","update":{"sessionUpdate":"agent_thought_chunk","content":{"type":"text","text":"The"}}}}
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{"jsonrpc":"2.0","method":"session/update","params":{"sessionId":"{{sessionId}}","update":{"sessionUpdate":"agent_thought_chunk","content":{"type":"text","text":" user"}}}}
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@@ -15,6 +15,8 @@ Check the [exit code: N] marker on every bash result; investigate failures befor
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Track every background task id you start. You are notified in-session when a task finishes — do not busy-poll or sleep on one; keep working on independent steps and do not duplicate a running task's work. Before giving a final answer, collect every still-relevant task with task_output (set wait: true only when you are genuinely blocked on it), and task_kill tasks that stopped mattering.
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Use goal tools for one long-running completion objective in the current session. create_goal may infer goal intent from a direct human request in any language; do not create a goal for routine single-turn work. Call get_goal before update_goal and copy its exact goal_id and revision. After session resume or fork, an active goal is disarmed: when a human asks to continue or resume in any wording or language, use update_goal action resume to rearm it. Mark complete only when the objective is actually achieved. Mark blocked only after the same blocking condition persists for at least 3 consecutive goal rounds; difficulty, uncertainty, or useful remaining work is not blocked.
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Approval prompts are disabled in this session: actions that require approval are rejected automatically — do not request sandbox escalation (do not set `sandbox_permissions`).
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<!-- dsh-user-approval-policy:never -->
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@@ -45,6 +45,26 @@
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]
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}
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},
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{
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"name": "create_goal",
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"description": "Create one persisted same-session completion goal when the current direct human request is a long-running objective that should continue across autonomous goal rounds. You may infer that intent without requiring the user to say \"create a goal\". Do not use this for trivial single-turn work. Execution rejects non-human and subagent authority.",
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"parameters": {
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"type": "object",
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"properties": {
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"objective": {
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"type": "string",
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"description": "The concrete completion objective inferred from the direct human request."
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},
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"max_goal_rounds": {
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"type": "number",
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"description": "Optional positive safe-integer cap; omission uses the goal-domain deployment default."
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}
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},
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"required": [
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"objective"
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]
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}
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},
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{
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"name": "edit",
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"description": "Edit an existing UTF-8 text file by replacing literal text.",
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@@ -75,6 +95,14 @@
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]
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}
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},
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{
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"name": "get_goal",
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"description": "Read the current same-session goal, including its exact id/revision, durable phase, admitted round count, cap, and live process-local activation. Call this before updating a goal.",
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"parameters": {
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"type": "object",
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"properties": {}
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}
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},
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{
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"name": "read",
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"description": "Read a UTF-8 text file and return line-numbered content.",
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@@ -255,6 +283,47 @@
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]
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}
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},
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{
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"name": "update_goal",
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"description": "Update the exact current goal revision. edit, pause, and resume require a direct top-level human turn. complete and blocked additionally accept the exact admitted goal round. blocked is rejected before the configured minimum round count; the model remains responsible for judging that the same condition persisted across those rounds.",
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"parameters": {
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"type": "object",
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"properties": {
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"goal_id": {
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"type": "string",
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"description": "Exact id returned by get_goal."
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},
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"revision": {
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"type": "number",
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"description": "Exact positive revision returned by get_goal."
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},
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"action": {
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"type": "string",
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"description": "edit | pause | resume | complete | blocked",
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"enum": [
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"edit",
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"pause",
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"resume",
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"complete",
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"blocked"
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]
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},
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"objective": {
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"type": "string",
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"description": "Replacement objective; valid only with action edit."
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},
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"max_goal_rounds": {
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"type": "number",
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"description": "Replacement cap; valid only with action edit."
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}
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},
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"required": [
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"goal_id",
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"revision",
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"action"
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]
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}
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},
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{
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"name": "workflow",
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"description": "Run a JavaScript workflow script that orchestrates subagents at scale. Use this for work that fans out across many independent pieces — an audit over many files, a migration, multi-angle research, adversarial verification of findings — where you write the orchestration as a script instead of delegating turn by turn.\n\nThe workflow's identity rides the `meta` parameter as JSON: required `name` (short kebab-case) and `description` strings, optional `whenToUse` string and `phases` array (`{title, detail?, provider?, model?}`). The `script` parameter is the plain JavaScript body ONLY (NOT TypeScript, and NO `export const meta` statement — meta is a parameter, not code), running with top-level await; end with `return <value>` — the value must be JSON-serializable and is this tool's result.\n\nScript-body hooks:\n- `agent(prompt, opts?): Promise<any>` — run one subagent to completion. Without `opts.schema` it resolves to the child's final text; with `opts.schema` (an object-rooted JSON Schema using ONLY type/properties/required/additionalProperties/items/enum/const — no oneOf/pattern/format/numeric bounds) it resolves to the validated object. Resolves `null` when the child fails (filter with `.filter(Boolean)`). Other opts: `label` (display), `phase` (progress group), and independent `provider`/`model` LLM target overrides (either may be provided alone). Anything else (`effort`/`isolation`/`agentType`) is rejected loudly.\n- `pipeline(items, ...stages): Promise<any[]>` — run each item through the stages independently with NO barrier between stages (prefer this for multi-stage work). Each stage receives `(prev, item, index)`. An ordinary stage throw drops that ITEM to `null` and skips its remaining stages.\n- `parallel(thunks): Promise<any[]>` — run zero-argument functions concurrently and await ALL of them (a barrier; use only when a stage genuinely needs every prior result together). A throwing thunk resolves to `null`.\n- `phase(title)` — start a progress phase; `log(message)` — narrate progress; `args` — the tool call's `args` input, verbatim.\n\nMisused hooks (bad arguments, unknown options, unsupported schemas, tripped caps) throw errors that ALWAYS kill the script — they never dissolve into a per-item `null`.\n\nConstraints: concurrency and total-agent caps apply; no filesystem, network, timers, or Node.js APIs are provided — the agents do the work, the script only coordinates them. The run executes in the foreground: this call returns when the whole script finishes.",
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