Fix output order and add Reddit error handling

- SKILL.md: Move "What I learned" BEFORE "Research Complete" stats
- Add error tracking to Report schema (reddit_error, x_error fields)
- Wrap OpenAI API calls in try/catch with clear error messages
- Show explicit error or "no results" messages in compact output
- Fix false positive error detection for null error fields

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

SKILL.md

@@ -108,20 +108,15 @@ Read the research output and become an **expert**. Identify:
 
 ## THEN: Show Summary + Invite Vision
 
-Display in this EXACT order (so stats are visible at bottom of terminal):
+**CRITICAL ORDER**: Display sections in this EXACT sequence (insights FIRST, stats LAST):
 
 ```
-**Key patterns discovered:**
+---
-1. [Pattern 1] - [one-line insight]
+What I learned:
-2. [Pattern 2] - [one-line insight]
-3. [Pattern 3] - [one-line insight]
-4. [Pattern 4] - [one-line insight]
-5. [Pattern 5] - [one-line insight]
 
-I'm now an expert in {TOPIC}.
+[2-4 sentences synthesizing the key insight from your research. What's the secret? What pattern emerged? What do experts do differently? Write this as a mini-expert briefing, not a list.]
 
 ---
-
 📊 Research Complete
 
 Analyzed {total_sources} sources from the last 30 days
@@ -129,6 +124,7 @@ Analyzed {total_sources} sources from the last 30 days
 ├─ X: {n} posts │ {sum} likes │ {sum} reposts
 └─ Top voices: r/{sub1}, r/{sub2}, @{handle1}, @{handle2}
 
+---
 Share your vision for what you want to create and I'll write a thoughtful prompt you can copy-paste directly into {TARGET_TOOL}.
 ```
 

scripts/last30days.py

@@ -29,6 +29,7 @@ from lib import (
     dates,
     dedupe,
     env,
+    http,
     models,
     normalize,
     openai_reddit,
@@ -62,25 +63,38 @@ def run_research(
     """Run the research pipeline.
 
     Returns:
-        Tuple of (reddit_items, x_items, raw_openai, raw_xai, raw_reddit_enriched)
+        Tuple of (reddit_items, x_items, raw_openai, raw_xai, raw_reddit_enriched, reddit_error, x_error)
     """
     reddit_items = []
     x_items = []
     raw_openai = None
     raw_xai = None
     raw_reddit_enriched = []
+    reddit_error = None
+    x_error = None
 
     # Reddit search via OpenAI
     if sources in ("both", "reddit"):
         if mock:
             raw_openai = load_fixture("openai_sample.json")
         else:
+            try:
                 raw_openai = openai_reddit.search_reddit(
                     config["OPENAI_API_KEY"],
                     selected_models["openai"],
                     topic,
                     depth=depth,
                 )
+            except http.HTTPError as e:
+                print(f"[REDDIT ERROR] OpenAI API request failed: {e}", flush=True)
+                if e.body:
+                    print(f"[REDDIT ERROR] Response body: {e.body[:500]}", flush=True)
+                raw_openai = {"error": str(e)}
+                reddit_error = f"API error: {e}"
+            except Exception as e:
+                print(f"[REDDIT ERROR] Unexpected error: {type(e).__name__}: {e}", flush=True)
+                raw_openai = {"error": str(e)}
+                reddit_error = f"{type(e).__name__}: {e}"
 
         # Parse response
         reddit_items = openai_reddit.parse_reddit_response(raw_openai)
@@ -112,7 +126,7 @@ def run_research(
         # Parse response
         x_items = xai_x.parse_x_response(raw_xai)
 
-    return reddit_items, x_items, raw_openai, raw_xai, raw_reddit_enriched
+    return reddit_items, x_items, raw_openai, raw_xai, raw_reddit_enriched, reddit_error, x_error
 
 
 def main():
@@ -227,7 +241,7 @@ def main():
         mode = "x-only"
 
     # Run research
-    reddit_items, x_items, raw_openai, raw_xai, raw_reddit_enriched = run_research(
+    reddit_items, x_items, raw_openai, raw_xai, raw_reddit_enriched, reddit_error, x_error = run_research(
         args.topic,
         sources,
         config,
@@ -265,6 +279,8 @@ def main():
     )
     report.reddit = deduped_reddit
     report.x = deduped_x
+    report.reddit_error = reddit_error
+    report.x_error = x_error
 
     # Generate context snippet
     report.context_snippet_md = render.render_context_snippet(report)

scripts/lib/openai_reddit.py

@@ -101,6 +101,13 @@ def parse_reddit_response(response: Dict[str, Any]) -> List[Dict[str, Any]]:
     """
     items = []
 
+    # Check for API errors first
+    if "error" in response and response["error"]:
+        error = response["error"]
+        err_msg = error.get("message", str(error)) if isinstance(error, dict) else str(error)
+        print(f"[REDDIT ERROR] OpenAI API error: {err_msg}", flush=True)
+        return items
+
     # Try to find the output text
     output_text = ""
     if "output" in response:
@@ -131,6 +138,7 @@ def parse_reddit_response(response: Dict[str, Any]) -> List[Dict[str, Any]]:
                 break
 
     if not output_text:
+        print(f"[REDDIT WARNING] No output text found in OpenAI response. Keys present: {list(response.keys())}", flush=True)
         return items
 
     # Extract JSON from the response

scripts/lib/render.py

@@ -46,7 +46,17 @@ def render_compact(report: schema.Report, limit: int = 15) -> str:
         lines.append("")
 
     # Reddit items
-    if report.reddit:
+    if report.reddit_error:
+        lines.append("### Reddit Threads")
+        lines.append("")
+        lines.append(f"**ERROR:** {report.reddit_error}")
+        lines.append("")
+    elif report.mode in ("both", "reddit-only") and not report.reddit:
+        lines.append("### Reddit Threads")
+        lines.append("")
+        lines.append("*No relevant Reddit threads found for this topic.*")
+        lines.append("")
+    elif report.reddit:
         lines.append("### Reddit Threads")
         lines.append("")
         for item in report.reddit[:limit]:
@@ -78,7 +88,17 @@ def render_compact(report: schema.Report, limit: int = 15) -> str:
             lines.append("")
 
     # X items
-    if report.x:
+    if report.x_error:
+        lines.append("### X Posts")
+        lines.append("")
+        lines.append(f"**ERROR:** {report.x_error}")
+        lines.append("")
+    elif report.mode in ("both", "x-only") and not report.x:
+        lines.append("### X Posts")
+        lines.append("")
+        lines.append("*No relevant X posts found for this topic.*")
+        lines.append("")
+    elif report.x:
         lines.append("### X Posts")
         lines.append("")
         for item in report.x[:limit]:

scripts/lib/schema.py

@@ -153,9 +153,12 @@ class Report:
     best_practices: List[str] = field(default_factory=list)
     prompt_pack: List[str] = field(default_factory=list)
     context_snippet_md: str = ""
+    # Status tracking
+    reddit_error: Optional[str] = None
+    x_error: Optional[str] = None
 
     def to_dict(self) -> Dict[str, Any]:
-        return {
+        d = {
             'topic': self.topic,
             'range': {
                 'from': self.range_from,
@@ -171,6 +174,11 @@ class Report:
             'prompt_pack': self.prompt_pack,
             'context_snippet_md': self.context_snippet_md,
         }
+        if self.reddit_error:
+            d['reddit_error'] = self.reddit_error
+        if self.x_error:
+            d['x_error'] = self.x_error
+        return d
 
 
 def create_report(