API Clients + structured JSON results: app-level tokens for Synap/WSIT integration

- New api_clients + api_client_scopes tables; tokens scoped per-instance
- Admin UI tab at /admin for token create/rotate/revoke/delete with one-time reveal
- Dual-auth dependency (user session OR Bearer app token) on trigger + runs endpoints
- /api/instances/{id}/trigger pre-creates a run and returns run_id + cached last_result instantly
- New GET /api/runs/{id} for polling
- Generic trigger path for sub-agent instances (weather, calendar, etc.)
- runs.result column for structured JSON alongside markdown output
- agent_catalog.result_schema describes each agent's result shape
- Weather, daily-briefing, project-monitor retrofitted to emit structured results
- log_run: env INSTANCE_ID/RUN_ID only used when target matches, so nested sub-agents don't clobber parent runs
- Wiki docs: API Clients & Token Scoping + Calling Agents From Your Apps

agents/project_monitor.py

@@ -283,7 +283,8 @@ def run(config, user_id=None, instance_id=None):
     project_name = config.get("project_name", "Unknown Project")
 
     if not user_id:
-        return f"## {project_name}\n\n*No user context for LLM.*\n", "error: no user_id"
+        md = f"## {project_name}\n\n*No user context for LLM.*\n"
+        return {"markdown": md, "summary": "error: no user_id", "result": None}
 
     print(f"    Collecting data for {project_name}...")
 
@@ -313,16 +314,17 @@ def run(config, user_id=None, instance_id=None):
 
     print(f"    Calling LLM for analysis...")
     try:
-        result = llm_complete(user_id, prompt, system=SYSTEM_PROMPT, max_tokens=2000)
+        llm_result = llm_complete(user_id, prompt, system=SYSTEM_PROMPT, max_tokens=2000)
     except RuntimeError as e:
         err = str(e)
         log_run(AGENT_ID, "failed", err=err, instance_id=instance_id)
-        return f"## {project_name}\n\n*LLM error: {err}*\n", f"error: {err}"
+        md = f"## {project_name}\n\n*LLM error: {err}*\n"
+        return {"markdown": md, "summary": f"error: {err}", "result": None}
 
-    report_md = result["text"]
-    model = result["model"]
-    tokens_in = result["input_tokens"]
-    tokens_out = result["output_tokens"]
+    report_md = llm_result["text"]
+    model = llm_result["model"]
+    tokens_in = llm_result["input_tokens"]
+    tokens_out = llm_result["output_tokens"]
 
     print(f"    LLM: {model}, {tokens_in}+{tokens_out} tokens")
 
@@ -372,15 +374,31 @@ def run(config, user_id=None, instance_id=None):
     if links_md:
         section += f"\n{links_md}\n"
 
-    log_run(AGENT_ID, "success", output=f"{project_name}: {summary[:100]}", instance_id=instance_id, metadata={
-        "project": project_name,
-        "model": model,
-        "tokens_in": tokens_in,
-        "tokens_out": tokens_out,
+    structured = {
+        "project_name": project_name,
+        "app_url": app_url or None,
+        "wiki_collection_id": wiki_collection or None,
         "wiki_report_id": doc_id,
-    })
+        "gitea_repo": gitea_repo or None,
+        "summary": summary,
+        "report_markdown": report_md,
+        "model": model,
+        "tokens": {"input": tokens_in, "output": tokens_out},
+        "generated_at": datetime.now(MT).isoformat(),
+    }
 
-    return section, summary
+    log_run(AGENT_ID, "success", output=f"{project_name}: {summary[:100]}",
+            instance_id=instance_id,
+            result=structured,
+            metadata={
+                "project": project_name,
+                "model": model,
+                "tokens_in": tokens_in,
+                "tokens_out": tokens_out,
+                "wiki_report_id": doc_id,
+            })
+
+    return {"markdown": section, "summary": summary, "result": structured}
 
 
 if __name__ == "__main__":
@@ -398,6 +416,6 @@ if __name__ == "__main__":
         "wiki_collection_id": args.wiki_collection,
         "gitea_repo": args.gitea_repo,
     }
-    section, summary = run(config, user_id=args.user_id, instance_id=args.instance_id)
-    print(section)
-    print(f"\nSummary: {summary}")
+    out = run(config, user_id=args.user_id, instance_id=args.instance_id)
+    print(out["markdown"])
+    print(f"\nSummary: {out['summary']}")