Fix planning prompt preservation (#76)

* feat: allow disabling delegation tools

* fix planning prompt preservation

* refactor delegation tool gating into config

---------

Co-authored-by: Claude <claude@anthropic.com>

Author: Lixtt

CHANGELOG.md

@@ -459,6 +459,11 @@ fields, new `SessionStore` trait methods with default no-op impls).
   global `auto_parallel` kill switch. Setting `auto_parallel = false` disables
   automatic parallel child-agent fan-out while keeping manual `parallel_task`
   available.
+- Added `auto_delegation.allow_manual_delegation` and
+  `SessionOptions::with_manual_delegation_enabled(...)` so hosts can hide the
+  model-visible `task` / `parallel_task` tools per session while preserving the
+  child-agent registry for introspection and worker registration. This is an
+  operational cost/debug control, not a security sandbox.
 - Added `max_parallel_tasks` as the shared sibling fan-out limit for
   `parallel_task`, delegated plan waves, and safe parallel write batches.
 - Added a reusable ordered parallel executor so concurrent child results remain

README.md

@@ -1685,10 +1685,11 @@ skill_dirs = ["./skills"]
 mcp_servers = []
 
 auto_delegation {
-  enabled        = false
-  auto_parallel  = false
-  min_confidence = 0.72
-  max_tasks      = 4
+  enabled                  = false
+  auto_parallel            = false
+  allow_manual_delegation  = true
+  min_confidence           = 0.72
+  max_tasks                = 4
 }
 
 ahp = {
@@ -1707,6 +1708,11 @@ safe parallel write batches.
 `auto_delegation.enabled` controls Claude Code-style automatic subagent
 delegation. `auto_parallel = false` is a global kill switch for automatic
 parallel child-agent fan-out; manual `parallel_task` remains available.
+Set `allow_manual_delegation = false` to hide the model-visible `task` and
+`parallel_task` tools for cost control or debugging while preserving the child
+agent registry for introspection and host-managed worker registration. This is
+not a security sandbox: the parent agent may still use other registered tools,
+MCP servers, or skills.
 
 ---
 

core/prompts/analysis/pre_analysis_system.md

@@ -23,7 +23,7 @@ Schema:
     ],
     "required_tools": ["tool_name"]
   },
-  "optimized_input": "the same request with references resolved, in the user's language"
+  "optimized_input": "the full original request with references resolved, in the user's language"
 }
 
 Rules:
@@ -43,4 +43,7 @@ Rules:
   VeryComplex = release, migration, security-sensitive, or broad architecture work.
 - Prefer `program` for repeated structured repository analysis; prefer
   `task`/`parallel_task` for delegated agent work.
+- `optimized_input` must preserve every concrete constraint, path, name, branch,
+  environment variable, metric, and negative instruction from the original user
+  message. Do not replace the task with a short summary.
 - Respond with valid JSON only. No markdown fences, comments, or explanation.

core/src/agent/execution_mode.rs

@@ -14,6 +14,26 @@ struct ExecutionRoute {
 }
 
 impl AgentLoop {
+    pub(super) fn preserve_original_prompt_for_execution(
+        original_prompt: &str,
+        optimized_input: &str,
+    ) -> String {
+        let original = original_prompt.trim();
+        let optimized = optimized_input.trim();
+
+        if original.is_empty() {
+            return optimized.to_string();
+        }
+        if optimized.is_empty() || optimized == original {
+            return original.to_string();
+        }
+        if optimized.contains(original) {
+            return optimized.to_string();
+        }
+
+        format!("Original user request:\n{original}\n\nPlanner-optimized request:\n{optimized}")
+    }
+
     pub(super) fn should_run_pre_analysis(&self) -> bool {
         match self.config.planning_mode {
             PlanningMode::Disabled => false,
@@ -90,7 +110,9 @@ impl AgentLoop {
         let use_planning = self.resolve_planning_decision(style, pre_analysis.as_ref());
         let effective_prompt = pre_analysis
             .as_ref()
-            .map(|analysis| analysis.optimized_input.clone())
+            .map(|analysis| {
+                Self::preserve_original_prompt_for_execution(prompt, &analysis.optimized_input)
+            })
             .unwrap_or_else(|| prompt.to_string());
 
         ExecutionRoute {

core/src/agent/plan_execution.rs

@@ -109,15 +109,22 @@ impl AgentLoop {
         }
     }
 
-    pub(super) fn delegated_prompt_for_step(
+    pub(super) fn delegated_prompt_for_step_with_goal(
+        plan_goal: Option<&str>,
         step: &Task,
         step_number: usize,
         total_steps: usize,
     ) -> String {
-        let mut prompt = format!(
+        let mut prompt = String::new();
+        if let Some(goal) = plan_goal.map(str::trim).filter(|goal| !goal.is_empty()) {
+            prompt.push_str("Plan goal/context:\n");
+            prompt.push_str(goal);
+            prompt.push_str("\n\n");
+        }
+        prompt.push_str(&format!(
             "Execute plan step {}/{}.\n\nTask:\n{}\n",
             step_number, total_steps, step.content
-        );
+        ));
         if let Some(criteria) = step
             .success_criteria
             .as_deref()
@@ -131,25 +138,29 @@ impl AgentLoop {
         prompt
     }
 
-    pub(super) fn delegated_task_args(
+    pub(super) fn delegated_task_args_with_goal(
+        plan_goal: Option<&str>,
         step: &Task,
         step_number: usize,
         total_steps: usize,
     ) -> Value {
         json!({
             "agent": Self::delegated_agent_for_step(step),
             "description": step.content,
-            "prompt": Self::delegated_prompt_for_step(step, step_number, total_steps),
+            "prompt": Self::delegated_prompt_for_step_with_goal(plan_goal, step, step_number, total_steps),
         })
     }
 
-    pub(super) fn parallel_delegated_task_args(
+    pub(super) fn parallel_delegated_task_args_with_goal(
+        plan_goal: Option<&str>,
         steps: &[(Task, usize)],
         total_steps: usize,
     ) -> Value {
         let tasks = steps
             .iter()
-            .map(|(step, step_number)| Self::delegated_task_args(step, *step_number, total_steps))
+            .map(|(step, step_number)| {
+                Self::delegated_task_args_with_goal(plan_goal, step, *step_number, total_steps)
+            })
             .collect::<Vec<_>>();
         json!({ "tasks": tasks })
     }
@@ -275,9 +286,14 @@ impl AgentLoop {
                         _ => "task",
                     };
                     let args = if tool_name == "parallel_task" {
-                        json!({ "tasks": [Self::delegated_task_args(&step, step_number, total_steps)] })
+                        json!({ "tasks": [Self::delegated_task_args_with_goal(Some(&plan.goal), &step, step_number, total_steps)] })
                     } else {
-                        Self::delegated_task_args(&step, step_number, total_steps)
+                        Self::delegated_task_args_with_goal(
+                            Some(&plan.goal),
+                            &step,
+                            step_number,
+                            total_steps,
+                        )
                     };
                     let (output, _exit_code, is_error, _metadata) = self
                         .execute_delegated_plan_tool(tool_name, &args, session_id, &event_tx)
@@ -429,7 +445,11 @@ impl AgentLoop {
                     .iter()
                     .all(|(step, _)| Self::should_delegate_plan_step(step))
                 {
-                    let args = Self::parallel_delegated_task_args(&ready_steps, total_steps);
+                    let args = Self::parallel_delegated_task_args_with_goal(
+                        Some(&plan.goal),
+                        &ready_steps,
+                        total_steps,
+                    );
                     let (output, _exit_code, is_error, metadata) = self
                         .execute_delegated_plan_tool("parallel_task", &args, session_id, &event_tx)
                         .await;

core/src/agent/planning_runtime.rs

@@ -5,6 +5,23 @@ use anyhow::Result;
 use tokio::sync::mpsc;
 
 impl AgentLoop {
+    pub(super) fn preserve_plan_goal_context(
+        mut plan: ExecutionPlan,
+        execution_prompt: &str,
+    ) -> ExecutionPlan {
+        let context = execution_prompt.trim();
+        let goal = plan.goal.trim();
+
+        if context.is_empty() || goal == context || goal.contains(context) {
+            return plan;
+        }
+
+        plan.goal = format!(
+            "Original user request and planning context:\n{context}\n\nPlanner goal:\n{goal}"
+        );
+        plan
+    }
+
     pub(super) async fn emit_task_updated(
         &self,
         event_tx: &Option<mpsc::Sender<AgentEvent>>,
@@ -60,7 +77,10 @@ impl AgentLoop {
 
         // Use pre-analysis result if available (goal + plan already computed in one LLM call).
         let (goal, plan) = if let Some(analysis) = pre_analysis {
-            (Some(analysis.goal.clone()), analysis.execution_plan.clone())
+            (
+                Some(analysis.goal.clone()),
+                Self::preserve_plan_goal_context(analysis.execution_plan.clone(), prompt),
+            )
         } else {
             // Fall back: extract goal and create plan via separate LLM calls.
             let g = if self.config.goal_tracking {

core/src/agent/tests.rs

@@ -62,7 +62,7 @@ fn test_delegated_task_args_include_prompt_contract() {
     let task = Task::new("s1", "验证 program 工具")
         .with_tool("task")
         .with_success_criteria("All integration checks pass.");
-    let args = AgentLoop::delegated_task_args(&task, 2, 5);
+    let args = AgentLoop::delegated_task_args_with_goal(None, &task, 2, 5);
 
     assert_eq!(args["agent"], "verification");
     assert_eq!(args["description"], "验证 program 工具");
@@ -81,14 +81,63 @@ fn test_parallel_delegated_task_args_preserve_order() {
         (Task::new("s1", "Find docs").with_tool("task"), 1),
         (Task::new("s2", "Run tests").with_tool("task"), 2),
     ];
-    let args = AgentLoop::parallel_delegated_task_args(&steps, 2);
+    let args = AgentLoop::parallel_delegated_task_args_with_goal(None, &steps, 2);
     let tasks = args["tasks"].as_array().unwrap();
 
     assert_eq!(tasks.len(), 2);
     assert_eq!(tasks[0]["agent"], "explore");
     assert_eq!(tasks[1]["agent"], "verification");
 }
 
+#[test]
+fn test_preserve_original_prompt_for_planning_execution() {
+    let original =
+        "Fix planning mode. Preserve /tmp/task.txt and do not drop negative instructions.";
+    let optimized = "Fix planning mode.";
+
+    let preserved = AgentLoop::preserve_original_prompt_for_execution(original, optimized);
+
+    assert!(preserved.contains("Original user request"));
+    assert!(preserved.contains("/tmp/task.txt"));
+    assert!(preserved.contains("do not drop negative instructions"));
+    assert!(preserved.contains("Planner-optimized request"));
+    assert!(preserved.contains(optimized));
+}
+
+#[test]
+fn test_preserve_plan_goal_context_keeps_original_request_visible() {
+    use crate::planning::{Complexity, ExecutionPlan};
+
+    let plan = ExecutionPlan::new("Fix planning mode".to_string(), Complexity::Medium);
+    let execution_prompt =
+        "Original user request:\nFix planning mode for /workspace/app; do not change API.";
+
+    let preserved = AgentLoop::preserve_plan_goal_context(plan, execution_prompt);
+
+    assert!(preserved.goal.contains("/workspace/app"));
+    assert!(preserved.goal.contains("do not change API"));
+    assert!(preserved.goal.contains("Planner goal"));
+}
+
+#[test]
+fn test_delegated_plan_step_prompt_includes_plan_goal_context() {
+    use crate::planning::Task;
+
+    let task = Task::new("s1", "Implement the first step").with_tool("task");
+    let args = AgentLoop::delegated_task_args_with_goal(
+        Some("Original request: update /workspace/app and keep API stable."),
+        &task,
+        1,
+        1,
+    );
+    let prompt = args["prompt"].as_str().unwrap();
+
+    assert!(prompt.contains("Plan goal/context"));
+    assert!(prompt.contains("/workspace/app"));
+    assert!(prompt.contains("keep API stable"));
+    assert!(prompt.contains("Implement the first step"));
+}
+
 #[test]
 fn test_memory_items_become_context_result() {
     let item = a3s_memory::MemoryItem::new("Use focused regression tests for context changes.")

core/src/agent_api.rs

@@ -272,6 +272,12 @@ pub struct SessionOptions {
     pub max_parallel_tasks: Option<usize>,
     /// Per-session automatic subagent delegation override.
     pub auto_delegation: Option<crate::config::AutoDelegationConfig>,
+    /// Per-session switch for model-visible manual child-agent tools.
+    ///
+    /// This overlays the effective automatic delegation config instead of
+    /// replacing it, so callers can hide `task` / `parallel_task` while
+    /// preserving other delegation settings.
+    pub manual_delegation_enabled: Option<bool>,
     /// Per-session kill switch for automatic parallel child-agent fan-out.
     ///
     /// This overlays the effective automatic delegation config instead of

core/src/agent_api/capabilities.rs

@@ -163,6 +163,7 @@ fn register_task_capability(
     use crate::tools::register_task_with_mcp;
 
     let registry = AgentRegistry::new();
+    let auto_delegation = super::session_config::resolve_auto_delegation_config(code_config, opts);
     let built_in_agent_dirs = built_in_agent_dirs(workspace);
     for dir in code_config
         .agent_dirs
@@ -178,6 +179,12 @@ fn register_task_capability(
         registry.register_worker(worker.clone());
     }
 
+    if !auto_delegation.allow_manual_delegation {
+        // Keep the registry populated for introspection and host-managed worker
+        // registration even when the model-visible delegation tools are hidden.
+        return Arc::new(registry);
+    }
+
     let parent_context = ChildRunContext {
         security_provider: opts.security_provider.clone(),
         hook_engine: None,

core/src/agent_api/session_builder.rs

@@ -15,7 +15,9 @@ use std::sync::{Arc, RwLock};
 use super::capabilities::{
     build_session_capabilities, register_skill_capability, SessionCapabilityInput,
 };
-use super::session_config::{resolve_session_memory, resolve_session_store};
+use super::session_config::{
+    resolve_auto_delegation_config, resolve_session_memory, resolve_session_store,
+};
 use super::session_runtime::{build_session_runtime, SessionRuntimeInput};
 
 pub(super) fn prepare_session_options(agent: &Agent, opts: SessionOptions) -> SessionOptions {
@@ -135,13 +137,7 @@ pub(super) fn build_agent_session(
     let init_warning = resolved_memory.init_warning;
 
     let base = agent.config.clone();
-    let mut auto_delegation = opts
-        .auto_delegation
-        .clone()
-        .unwrap_or_else(|| base.auto_delegation.clone());
-    if let Some(auto_parallel) = opts.auto_parallel_delegation {
-        auto_delegation.auto_parallel = auto_parallel;
-    }
+    let auto_delegation = resolve_auto_delegation_config(&agent.code_config, opts);
     let config = AgentConfig {
         prompt_slots,
         tools: tool_defs,