Debugging Signals Pipeline Skill for Claude

Debugging the signals pipeline

Pipeline flow

emit_signals_from_fixture
  → signal-emitter (Temporal workflow)
    → buffer-signals (batches signals, 5s flush timer)
      → safety_filter_activity
      → flush_signals_to_s3_activity
      → signal_with_start_grouping_v2_activity
        → team-signal-grouping-v2 (30s batch collect window)
          → read_signals_from_s3_activity
          → get_embedding_activity + generate_search_queries_activity
          → run_signal_semantic_search_activity
          → match_signal_to_report_activity
          → assign_and_emit_signal_activity
          → wait_for_signal_in_clickhouse_activity
          → (if new report) signal-report-summary
            → fetch_signals_for_report_activity
            → report_safety_judge_activity
            → select_repository_activity (spawns Docker sandbox)

Emitting test signals

# Emit a single signal from the Zendesk fixture at offset 26
DEBUG=1 python manage.py emit_signals_from_fixture --type zendesk --team-id 1 --offset 26 --limit 1

# Clean up all signal data before re-emitting (avoids stale matches)
DEBUG=1 python manage.py cleanup_signals --team-id 1 --yes

# Check pipeline status
python manage.py signal_pipeline_status --team-id 1 --wait --expected-signals 1 --poll-interval 10

Always clean up before re-emitting to avoid stale embeddings causing phantom report matches.

Monitoring Temporal workflows

The Temporal UI runs at http://localhost:8081. The REST API is useful for scripted inspection.

List recent workflows

curl -s 'http://localhost:8081/api/v1/namespaces/default/workflows?query=ORDER+BY+StartTime+DESC&maximumPageSize=15' \
  | python3 -c "
import sys, json
for wf in json.load(sys.stdin).get('executions', []):
    info = wf['execution']
    status = wf['status'].replace('WORKFLOW_EXECUTION_STATUS_', '')
    print(f'{wf[\"startTime\"][:19]}  {status:20s} {wf[\"type\"][\"name\"]:35s} {info[\"workflowId\"][:90]}')
"

Inspect workflow history

WF_ID="buffer-signals-1"  # or team-signal-grouping-v2-1, signals-report:1:<uuid>
curl -s "http://localhost:8081/api/v1/namespaces/default/workflows/$WF_ID/history?maximumPageSize=200" \
  | python3 -c "
import sys, json
for event in json.load(sys.stdin).get('history', {}).get('events', []):
    etype = event['eventType'].replace('EVENT_TYPE_', '')
    etime = event['eventTime'][:19]
    details = ''
    for key, attrs in event.items():
        if key.endswith('Attributes') and isinstance(attrs, dict):
            if 'activityType' in attrs: details = attrs['activityType'].get('name', '')
            elif 'signalName' in attrs: details = f'signal: {attrs[\"signalName\"]}'
            elif 'startToFireTimeout' in attrs: details = f'timer: {attrs[\"startToFireTimeout\"]}'
            elif 'failure' in attrs: details = f'FAILED: {attrs[\"failure\"].get(\"message\", \"\")[:200]}'
    if details: print(f'  {etime}  {etype:50s} {details}')
"

Inspect a previous run (continued-as-new)

When a workflow has continued-as-new, use the execution.runId query param:

curl -s "http://localhost:8081/api/v1/namespaces/default/workflows/$WF_ID/history?execution.runId=<run-id>&maximumPageSize=200"

Reading sandbox agent logs

Agent logs are stored in object storage (MinIO locally) as JSONL files.

The log URL is on the TaskRun model.

# In Django shell (python manage.py shell)
from products.tasks.backend.models import TaskRun
from posthog.storage import object_storage

# Find the most recent task run
run = TaskRun.objects.order_by("-created_at").first()
print(f"status: {run.status}, error: {run.error_message}")
print(f"log_url: {run.log_url}")

# Read the log
content = object_storage.read(run.log_url, missing_ok=True)

# Print last 3000 chars (most useful — shows what happened before failure)
print(content[-3000:])

The log is JSONL with entries like:

{
  "type": "notification",
  "timestamp": "...",
  "notification": { "jsonrpc": "2.0", "method": "_posthog/console", "params": { "level": "debug", "message": "..." } }
}

Key things to look for in the log tail:

• agentsh network events — DENY entries show blocked network calls
• _posthog/progress events — show which setup step the sandbox reached
• _posthog/console debug messages — show sandbox provisioning, cloning, agent startup

Inspecting Docker sandbox containers

# List running sandbox containers
docker ps --filter "name=task-sandbox" --format "table {{.Names}}\t{{.Status}}\t{{.Image}}"

# See processes inside a running sandbox
docker exec <container-name> ps aux

# Read the agent-server log inside the container (while it's still running)
docker exec <container-name> cat /tmp/agent-server.log

The container is named task-sandbox-<task-id>-<random> and uses the posthog-sandbox-base image.

Containers are ephemeral — they're removed after the task run completes, so inspect while running.

Common failures

SignalReport matching query does not exist

The assign_and_emit_signal_activity tried to assign a signal to a report that doesn't exist.

Usually caused by stale embeddings in ClickHouse after a cleanup_signals that failed to delete them.

Root cause: CLICKHOUSE_DATABASE not set in .env. The cleanup command uses sync_execute

which connects to the CLICKHOUSE_DATABASE (defaults to default), but the embedding tables

live in the posthog database.

Fix: Add CLICKHOUSE_DATABASE=posthog to .env and restart workers.

Manual cleanup of stale embeddings:

curl -s 'http://localhost:8123/' --data-binary \
  "ALTER TABLE posthog.sharded_posthog_document_embeddings_text_embedding_3_small_1536 DELETE WHERE product = 'signals' AND team_id = 1 SETTINGS mutations_sync = 1"

Verify embeddings are clean:

curl -s 'http://localhost:8123/' --data-binary \
  "SELECT count() FROM posthog.sharded_posthog_document_embeddings_text_embedding_3_small_1536 WHERE team_id = 1 AND product = 'signals'"

Run timed out due to inactivity on select_repository_activity

The sandbox Claude agent went idle for longer than TASKS_INACTIVITY_TIMEOUT_SECONDS. When unset

this falls back to a 2 hour timeout — set TASKS_INACTIVITY_TIMEOUT_SECONDS=30 locally to force fast failures.

Diagnosing: Read the agent log from object storage (see above). Check the tail for:

• agentsh network denials — DENY host.docker.internal means the MCP server URL is blocked

by the sandbox network policy. The SIGNALS_REPO_DISCOVERY environment's domain allowlist

doesn't include host.docker.internal.

• No log content at all — sandbox failed to start, check Docker container logs.
• Claude API errors — check if ANTHROPIC_API_KEY is valid.

buffer-signals sits idle, never receives signals

The signal-emitter completed but buffer-signals never got the submit_signal.

This happens when the emitter sent the signal to a previous buffer run that then continued-as-new,

and the new run started fresh without the pending signal. Re-emit the signal.

ClickHouse embedding tables "not found" during cleanup

The tables exist in the posthog database but sync_execute queries the default database.

# Verify tables exist
curl -s 'http://localhost:8123/' --data-binary "SHOW TABLES FROM posthog LIKE '%embed%'"

# Check current CLICKHOUSE_DATABASE setting
grep CLICKHOUSE_DATABASE .env

Useful management commands

| Command | Purpose |

| -------------------------------------------------- | ---------------------------------------------- |

| emit_signals_from_fixture | Emit test signals from JSON fixtures |

| DEBUG=1 cleanup_signals --team-id N --yes | Delete all signal data and terminate workflows |

| signal_pipeline_status --team-id N --wait | Wait for pipeline to finish processing |

| list_signal_reports --team-id N --signals --json | Inspect grouping results |

| ingest_signals_json <file> --team-id N | Ingest pre-processed signals from JSON |

| ingest_report_json <file> --team-id N | Seed a pre-researched report (skip sandbox) |

Key file locations

• Pipeline workflow definitions: products/signals/backend/temporal/
• Buffer workflow: products/signals/backend/temporal/buffer.py
• Grouping workflow: products/signals/backend/temporal/grouping_v2.py
• Report summary workflow: products/signals/backend/temporal/summary.py
• Docker sandbox implementation: products/tasks/backend/services/docker_sandbox.py
• Sandbox Dockerfiles: products/tasks/backend/sandbox/images/
• Agent log polling: products/tasks/backend/services/custom_prompt_internals.py
• Cleanup command: products/signals/backend/management/commands/cleanup_signals.py
• Management command docs: products/signals/backend/management/CLAUDE.md