feat: /compress <focus> — guided compression with focus topic (#8017)

Adds an optional focus topic to /compress: `/compress database schema`
guides the summariser to preserve information related to the focus topic
(60-70% of summary budget) while compressing everything else more aggressively.
Inspired by Claude Code's /compact <focus>.

Changes:
- context_compressor.py: focus_topic parameter on _generate_summary() and
  compress(); appends FOCUS TOPIC guidance block to the LLM prompt
- run_agent.py: focus_topic parameter on _compress_context(), passed through
  to the compressor
- cli.py: _manual_compress() extracts focus topic from command string,
  preserves existing manual_compression_feedback integration (no regression)
- gateway/run.py: _handle_compress_command() extracts focus from event args
  and passes through — full gateway parity
- commands.py: args_hint="[focus topic]" on /compress CommandDef

Salvaged from PR #7459 (CLI /compress focus only — /context command deferred).
15 new tests across CLI, compressor, and gateway.

agent/context_compressor.py

@@ -306,13 +306,19 @@ class ContextCompressor(ContextEngine):
 
         return "\n\n".join(parts)
 
-    def _generate_summary(self, turns_to_summarize: List[Dict[str, Any]]) -> Optional[str]:
+    def _generate_summary(self, turns_to_summarize: List[Dict[str, Any]], focus_topic: str = None) -> Optional[str]:
         """Generate a structured summary of conversation turns.
 
         Uses a structured template (Goal, Progress, Decisions, Files, Next Steps)
         inspired by Pi-mono and OpenCode. When a previous summary exists,
         generates an iterative update instead of summarizing from scratch.
 
+        Args:
+            focus_topic: Optional focus string for guided compression.  When
+                provided, the summariser prioritises preserving information
+                related to this topic and is more aggressive about compressing
+                everything else.  Inspired by Claude Code's ``/compact``.
+
         Returns None if all attempts fail — the caller should drop
         the middle turns without a summary rather than inject a useless
         placeholder.
@@ -414,6 +420,14 @@ Target ~{summary_budget} tokens. Be specific — include file paths, command out
 
 Write only the summary body. Do not include any preamble or prefix."""
 
+        # Inject focus topic guidance when the user provides one via /compress <focus>.
+        # This goes at the end of the prompt so it takes precedence.
+        if focus_topic:
+            prompt += f"""
+
+FOCUS TOPIC: "{focus_topic}"
+The user has requested that this compaction PRIORITISE preserving all information related to the focus topic above. For content related to "{focus_topic}", include full detail — exact values, file paths, command outputs, error messages, and decisions. For content NOT related to the focus topic, summarise more aggressively (brief one-liners or omit if truly irrelevant). The focus topic sections should receive roughly 60-70% of the summary token budget."""
+
         try:
             call_kwargs = {
                 "task": "compression",
@@ -631,7 +645,7 @@ Write only the summary body. Do not include any preamble or prefix."""
     # Main compression entry point
     # ------------------------------------------------------------------
 
-    def compress(self, messages: List[Dict[str, Any]], current_tokens: int = None) -> List[Dict[str, Any]]:
+    def compress(self, messages: List[Dict[str, Any]], current_tokens: int = None, focus_topic: str = None) -> List[Dict[str, Any]]:
         """Compress conversation messages by summarizing middle turns.
 
         Algorithm:
@@ -643,6 +657,12 @@ Write only the summary body. Do not include any preamble or prefix."""
 
         After compression, orphaned tool_call / tool_result pairs are cleaned
         up so the API never receives mismatched IDs.
+
+        Args:
+            focus_topic: Optional focus string for guided compression.  When
+                provided, the summariser will prioritise preserving information
+                related to this topic and be more aggressive about compressing
+                everything else.  Inspired by Claude Code's ``/compact``.
         """
         n_messages = len(messages)
         # Only need head + 3 tail messages minimum (token budget decides the real tail size)
@@ -700,7 +720,7 @@ Write only the summary body. Do not include any preamble or prefix."""
             )
 
         # Phase 3: Generate structured summary
-        summary = self._generate_summary(turns_to_summarize)
+        summary = self._generate_summary(turns_to_summarize, focus_topic=focus_topic)
 
         # Phase 4: Assemble compressed message list
         compressed = []