feat: preserve read_file context across pruning with file-read summary injection

agents/ollama.ts

@@ -150,6 +150,11 @@ async function runOllamaLoop(ctx: AgentRunContext): Promise<AgentResult> {
   let addedContinueNudge = false;
   let reportProgressCount = 0;
   let selectedModeName = "";
+  // Accumulates content previews from read_file calls so that when tool
+  // messages are pruned under context pressure, the model retains a compact
+  // summary of what it already read. User messages survive pruning.
+  const readFileLog = new Map<string, string>(); // path → content excerpt
+  let injectedFileReadSummary = false;
 
   while (iterations < MAX_ITERATIONS) {
     iterations++;
@@ -205,6 +210,22 @@ async function runOllamaLoop(ctx: AgentRunContext): Promise<AgentResult> {
       );
       if (promptTokens > numCtx * 0.77) {
         messages = pruneToolMessages(messages);
+        // Inject a compact summary of all files read so far as a user message
+        // so the model retains the context even after tool messages are pruned.
+        // Only inject once — subsequent prune events leave this message intact.
+        if (readFileLog.size > 0 && !injectedFileReadSummary) {
+          injectedFileReadSummary = true;
+          const entries = [...readFileLog.entries()]
+            .map(([p, c]) => `### ${p}\n${c}`)
+            .join("\n\n");
+          messages.push({
+            role: "user",
+            content:
+              `The following files were read earlier but their content was pruned from context. ` +
+              `Use these excerpts as your understanding of each file when writing the review:\n\n${entries}`,
+          });
+          log.info(`» injected file-read summary: ${readFileLog.size} file(s)`);
+        }
       }
     }
 
@@ -285,6 +306,39 @@ async function runOllamaLoop(ctx: AgentRunContext): Promise<AgentResult> {
         content: result,
       });
 
+      // Track read_file calls so we can reconstruct context after pruning.
+      if (toolName === "read_file") {
+        const path = (toolArgs as Record<string, unknown>)?.path;
+        if (typeof path === "string" && !readFileLog.has(path)) {
+          readFileLog.set(path, result.slice(0, 500));
+        }
+      }
+
+      // After checkout_pr returns, extract and pin the diffPath as a user
+      // message. Only tool messages are pruned — user messages survive context
+      // pressure — so the model retains the exact diff file path and knows how
+      // to call read_file with offset/limit to read diff ranges.
+      if (toolName === "checkout_pr") {
+        try {
+          const parsed = JSON.parse(result) as Record<string, unknown>;
+          if (typeof parsed?.diffPath === "string") {
+            const dp = parsed.diffPath;
+            messages.push({
+              role: "user",
+              content:
+                `The diff file is at: ${dp}\n\n` +
+                `Read each file's diff by calling read_file on this path with the line range from the TOC.\n` +
+                `Example — for "device.ts (163 lines, 1146-1308)": read_file(path="${dp}", offset=1146, limit=163)\n` +
+                `IMPORTANT: Do NOT call read_file on source files (apps/..., packages/...). ` +
+                `Use read_file on the diff file path above with the TOC ranges.`,
+            });
+            log.info(`» pinned diffPath to context: ${dp}`);
+          }
+        } catch {
+          // best-effort: if checkout_pr result isn't JSON, skip
+        }
+      }
+
       // report_progress called more than once means the model is looping —
       // it has no signal to stop since the tool always returns success.
       if (toolName === "report_progress") {