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fix(tools): align Plan tool handler with schema definition (#23)
* fix(tools): align Plan tool handler with schema definition The Plan tool had a critical mismatch between its schema definition and handler implementation: - Schema expected: title, description, tasks, agent_analyses (required) - Handler processed: only 'todos' string parameter This caused function calls to fail when LLMs generated Plan tool calls based on the schema but the handler couldn't process the rich parameters. Changes: - Updated PlanHandler to properly parse all schema parameters - Added support for architecture, tech_stack, use_cases, risks, success_criteria, timeline, and estimated_changes fields - Convert tasks and agent_analyses to internal formats - Generate rich markdown output with all plan sections - Aligned app-server definitions to match engine schema This ensures consistent Plan tool behavior across the codebase. * fix(app-server): update planning.rs to handle Plan tool schema Address Greptile review feedback - the container mode Plan implementation in planning.rs was missing support for the new required field agent_analyses and other optional fields. Changes: - Added agent_analyses parameter handling (required) - Added optional fields: architecture, tech_stack, use_cases, risks, success_criteria, timeline - Build plan_data JSON with all fields for consistency * fix(batch): address unused variable clippy warnings
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3 files changed

Lines changed: 401 additions & 43 deletions

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‎src/cortex-app-server/src/tools/definitions.rs‎

Lines changed: 108 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -337,7 +337,7 @@ pub fn get_tool_definitions() -> Vec<ToolDefinition> {
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},
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ToolDefinition {
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name: "Plan".to_string(),
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description: "Present an implementation plan for user approval before coding. Use this to outline approach, list tasks, and get confirmation.".to_string(),
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description: "Present a comprehensive implementation plan with multi-agent expert analysis for user approval. Include security, architecture, performance, and other expert perspectives.".to_string(),
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parameters: json!({
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"type": "object",
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"properties": {
@@ -347,7 +347,16 @@ pub fn get_tool_definitions() -> Vec<ToolDefinition> {
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},
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"description": {
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"type": "string",
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"description": "Detailed description of what will be implemented and how"
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"description": "Detailed description of what will be implemented and the overall approach"
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},
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"architecture": {
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"type": "string",
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"description": "High-level architecture description"
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},
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"tech_stack": {
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"type": "array",
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"items": { "type": "string" },
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"description": "Technologies, frameworks, and tools to be used"
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},
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"tasks": {
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"type": "array",
@@ -357,21 +366,115 @@ pub fn get_tool_definitions() -> Vec<ToolDefinition> {
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"id": { "type": "string" },
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"title": { "type": "string" },
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"description": { "type": "string" },
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"subtasks": {
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"type": "array",
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"items": { "type": "string" }
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},
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"dependencies": {
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"type": "array",
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"items": { "type": "string" },
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"description": "IDs of tasks this depends on"
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},
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"complexity": {
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"type": "string",
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"enum": ["low", "medium", "high", "critical"]
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},
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"estimated_time": { "type": "string" },
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"status": {
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"type": "string",
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"enum": ["pending", "in_progress", "completed"]
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}
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},
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"required": ["id", "title"]
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},
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"description": "List of tasks to complete"
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"description": "List of tasks with subtasks and dependencies"
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},
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"use_cases": {
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"type": "array",
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"items": {
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"oneOf": [
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{ "type": "string" },
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{
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"type": "object",
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"properties": {
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"name": { "type": "string" },
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"description": { "type": "string" },
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"actors": { "type": "array", "items": { "type": "string" } },
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"flow": { "type": "array", "items": { "type": "string" } }
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}
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}
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]
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},
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"description": "User stories and use cases"
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},
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"agent_analyses": {
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"type": "array",
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"items": {
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"type": "object",
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"properties": {
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"agent": {
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"type": "string",
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"description": "Name of the expert agent (e.g., 'Security Analyst', 'Performance Engineer')"
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},
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"role": {
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"type": "string",
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"description": "Role description"
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},
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"findings": {
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"type": "array",
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"items": { "type": "string" },
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"description": "Key findings from analysis"
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},
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"recommendations": {
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"type": "array",
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"items": { "type": "string" },
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"description": "Recommendations and best practices"
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},
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"risk_level": {
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"type": "string",
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"enum": ["low", "medium", "high", "critical"]
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},
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"priority_items": {
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"type": "array",
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"items": { "type": "string" }
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}
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},
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"required": ["agent", "role", "findings", "recommendations"]
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},
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"description": "Expert analyses from different perspectives (security, performance, UX, etc.)"
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},
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"risks": {
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"type": "array",
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"items": {
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"oneOf": [
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{ "type": "string" },
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{
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"type": "object",
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"properties": {
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"risk": { "type": "string" },
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"level": { "type": "string", "enum": ["low", "medium", "high", "critical"] },
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"mitigation": { "type": "string" }
457+
}
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}
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]
460+
},
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"description": "Identified risks and mitigation strategies"
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},
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"success_criteria": {
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"type": "array",
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"items": { "type": "string" },
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"description": "Criteria to determine if implementation is successful"
467+
},
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"timeline": {
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"type": "string",
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"description": "Estimated timeline for completion"
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},
369472
"estimated_changes": {
370473
"type": "string",
371-
"description": "Brief estimate of scope (e.g., 'Small: ~50 lines', 'Medium: ~200 lines')"
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"description": "Brief estimate of scope (e.g., 'Small: ~50 lines', 'Large: ~1000 lines')"
372475
}
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},
374-
"required": ["title", "description", "tasks"]
477+
"required": ["title", "description", "tasks", "agent_analyses"]
375478
}),
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category: "workflow".to_string(),
377480
},

‎src/cortex-app-server/src/tools/planning.rs‎

Lines changed: 30 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -70,21 +70,50 @@ pub async fn plan(args: Value) -> ToolResult {
7070
.get("description")
7171
.and_then(|v| v.as_str())
7272
.unwrap_or("");
73+
let architecture = args.get("architecture").and_then(|v| v.as_str());
74+
let tech_stack = args.get("tech_stack").cloned();
7375
let tasks = args.get("tasks").cloned().unwrap_or(json!([]));
76+
let use_cases = args.get("use_cases").cloned();
77+
let agent_analyses = args.get("agent_analyses").cloned().unwrap_or(json!([]));
78+
let risks = args.get("risks").cloned();
79+
let success_criteria = args.get("success_criteria").cloned();
80+
let timeline = args.get("timeline").and_then(|v| v.as_str());
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let estimate = args
7582
.get("estimated_changes")
7683
.and_then(|v| v.as_str())
7784
.unwrap_or("");
7885

79-
let plan_data = json!({
86+
// Build the plan data with all fields
87+
let mut plan_data = json!({
8088
"type": "plan",
8189
"title": title,
8290
"description": description,
8391
"tasks": tasks,
92+
"agent_analyses": agent_analyses,
8493
"estimated_changes": estimate,
8594
"status": "pending_approval"
8695
});
8796

97+
// Add optional fields if present
98+
if let Some(arch) = architecture {
99+
plan_data["architecture"] = json!(arch);
100+
}
101+
if let Some(stack) = tech_stack {
102+
plan_data["tech_stack"] = stack;
103+
}
104+
if let Some(cases) = use_cases {
105+
plan_data["use_cases"] = cases;
106+
}
107+
if let Some(risk_list) = risks {
108+
plan_data["risks"] = risk_list;
109+
}
110+
if let Some(criteria) = success_criteria {
111+
plan_data["success_criteria"] = criteria;
112+
}
113+
if let Some(tl) = timeline {
114+
plan_data["timeline"] = json!(tl);
115+
}
116+
88117
ToolResult {
89118
success: true,
90119
output: serde_json::to_string_pretty(&plan_data).unwrap_or_default(),

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