diff --git a/crates/edit_prediction_cli/src/anthropic_client.rs b/crates/edit_prediction_cli/src/anthropic_client.rs
index 9758419860146c87de667ffd6f71278504912962..941e82c9dbf39186cd4e061f81bcfe71b2ad5ee0 100644
--- a/crates/edit_prediction_cli/src/anthropic_client.rs
+++ b/crates/edit_prediction_cli/src/anthropic_client.rs
@@ -11,6 +11,7 @@ use reqwest_client::ReqwestClient;
 use sqlez::bindable::Bind;
 use sqlez::bindable::StaticColumnCount;
 use sqlez_macros::sql;
+use std::collections::HashSet;
 use std::hash::Hash;
 use std::hash::Hasher;
 use std::path::Path;
@@ -517,6 +518,7 @@ impl BatchingLlmClient {
 
         let mut current_batch_rows = Vec::new();
         let mut current_batch_size = 0usize;
+        let mut pending_hashes: HashSet<String> = HashSet::new();
         loop {
             let rows: Vec<(String, String)> = {
                 let connection = self.connection.lock().unwrap();
@@ -534,9 +536,15 @@ impl BatchingLlmClient {
 
             // Split rows into sub-batches based on size
             let mut batches_to_upload = Vec::new();
+            let mut new_rows_added = 0;
 
             for row in rows {
                 let (hash, request_str) = row;
+
+                // Skip rows already added to current_batch_rows but not yet uploaded
+                if pending_hashes.contains(&hash) {
+                    continue;
+                }
                 let serializable_request: SerializableRequest = serde_json::from_str(&request_str)?;
 
                 let messages: Vec<Message> = serializable_request
@@ -586,8 +594,16 @@ impl BatchingLlmClient {
                     current_batch_size = 0;
                 }
 
+                pending_hashes.insert(hash.clone());
                 current_batch_rows.push((hash, batch_request));
                 current_batch_size += estimated_size;
+                new_rows_added += 1;
+            }
+
+            // If no new rows were added this iteration, all pending requests are already
+            // in current_batch_rows, so we should break to avoid an infinite loop
+            if new_rows_added == 0 {
+                break;
             }
 
             // Only upload full batches, keep the partial batch for the next iteration
@@ -595,6 +611,11 @@ impl BatchingLlmClient {
             for (batch_rows, batch_size) in batches_to_upload {
                 let request_hashes: Vec<String> =
                     batch_rows.iter().map(|(hash, _)| hash.clone()).collect();
+
+                // Remove uploaded hashes from pending set
+                for hash in &request_hashes {
+                    pending_hashes.remove(hash);
+                }
                 let batch_requests: Vec<anthropic::batches::BatchRequest> =
                     batch_rows.into_iter().map(|(_, req)| req).collect();
 
diff --git a/crates/edit_prediction_cli/src/prompts/repair.md b/crates/edit_prediction_cli/src/prompts/repair.md
index 8ff3390af29cef83f4b23c141b6a772fb326cfc2..d3d77c03924344ec4d7d47c3e92e7b7cfda2084d 100644
--- a/crates/edit_prediction_cli/src/prompts/repair.md
+++ b/crates/edit_prediction_cli/src/prompts/repair.md
@@ -6,6 +6,8 @@ Your previous prediction has quality issues that need to be addressed. Please ge
 
 {quality_feedback}
 
+{token_change_info}
+
 ## Your Previous Prediction (word-diff format)
 
 `````
diff --git a/crates/edit_prediction_cli/src/repair.rs b/crates/edit_prediction_cli/src/repair.rs
index e1e588b0174ed9db5fdf52470cead38eea28019d..bf59604eb4b14d6860504151037fb09bffc37104 100644
--- a/crates/edit_prediction_cli/src/repair.rs
+++ b/crates/edit_prediction_cli/src/repair.rs
@@ -11,6 +11,7 @@ use crate::{
     anthropic_client::AnthropicClient,
     example::{ActualCursor, Example, ExamplePrediction},
     format_prompt::{TeacherPrompt, extract_last_codeblock},
+    metrics::count_patch_token_changes,
     openai_client::OpenAiClient,
     parse_output::run_parse_output,
     paths::LLM_CACHE_DB,
@@ -168,10 +169,26 @@ pub fn build_repair_message(example: &Example) -> Result<String> {
 
     let actual_patch_word_diff = unified_to_word_diff(actual_patch);
 
+    let token_counts = count_patch_token_changes(actual_patch);
+    let mut token_change_info = format!(
+        "\n## Token Change Statistics\n\n\
+         - **Deleted tokens**: {}\n\
+         - **Inserted tokens**: {}",
+        token_counts.deleted_tokens, token_counts.inserted_tokens,
+    );
+    if token_counts.deleted_tokens > 100 || token_counts.inserted_tokens > 100 {
+        token_change_info.push_str(
+            "\n\n> **Note:** The token change count is high. \
+             Consider producing a more scoped edit that targets only the lines \
+             that truly need to change, rather than rewriting large sections.",
+        );
+    }
+
     let prompt_template = crate::prompt_assets::get_prompt("repair.md");
     Ok(prompt_template
         .replace("{actual_patch_word_diff}", &actual_patch_word_diff)
-        .replace("{quality_feedback}", &quality_feedback))
+        .replace("{quality_feedback}", &quality_feedback)
+        .replace("{token_change_info}", &token_change_info))
 }
 
 /// Check if an example needs repair based on QA feedback or computed scores.