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konstruct/.planning/phases/02-agent-features/02-04-SUMMARY.md
Adolfo Delorenzo d1bcdef0f5 docs(02-04): complete human escalation handoff plan
- Summary with decisions, metrics, and self-check
- STATE.md: advance progress to 78%, add decisions, record session
- ROADMAP.md: update phase 2 plan progress (3 of 5 complete)
- REQUIREMENTS.md: mark AGNT-05 complete
2026-03-23 14:55:22 -06:00

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---
phase: 02-agent-features
plan: 04
subsystem: orchestrator
tags: [escalation, handoff, slack-api, redis, celery, pydantic, postgres, alembic]
requires:
- phase: 02-01
provides: "get_recent_messages for transcript assembly; Redis short-term memory infrastructure"
provides:
- "Escalation rule evaluator: 'keyword AND count > N' condition parser + natural language phrase detection"
- "Conversation transcript packager: Slack mrkdwn format with 3000-char truncation"
- "Human DM delivery: Slack conversations.open + chat.postMessage via httpx"
- "Escalation status tracking in Redis: escalation_status_key sets 'escalated' flag"
- "Post-escalation assistant mode: end-user messages to escalated threads get auto-reply, skipping LLM"
- "Agent model fields: escalation_assignee (Slack user ID), natural_language_escalation (bool)"
- "Alembic migration 003: adds escalation_assignee and natural_language_escalation to agents table"
- "No-op audit logger stub for escalation events (replaced when Plan 02 audit module ships)"
affects:
- "02-02 (audit) — escalation events use no-op logger stub, ready for real AuditLogger swap"
- "tasks.py pipeline — escalation pre/post checks integrated around LLM call"
tech-stack:
added: []
patterns:
- "Condition parsing: 'keyword AND count_field > N' format, regex-based, no eval()"
- "TDD pattern: RED (failing tests committed) then GREEN (implementation committed)"
- "Escalation pre-check before LLM: Redis flag gates whether LLM is called at all"
- "No-op logger stub: allows feature to work before audit plan is implemented"
key-files:
created:
- packages/orchestrator/orchestrator/escalation/__init__.py
- packages/orchestrator/orchestrator/escalation/handler.py
- migrations/versions/003_escalation_fields.py
- tests/unit/test_escalation.py
- tests/integration/test_escalation.py
modified:
- packages/shared/shared/models/tenant.py
- packages/orchestrator/orchestrator/tasks.py
key-decisions:
- "Keyword-based conversation metadata detection (v1): billing keywords + attempt counter from sliding window — simple and sufficient for initial rules"
- "Natural language escalation condition uses literal string 'natural_language_escalation' in escalation_rules config — matches plan spec"
- "Bot token loaded unconditionally in _process_message (not gated on placeholder_ts) — escalation DM needs it regardless of Slack placeholder presence"
- "No-op audit logger stub in tasks.py: escalation works independently of Plan 02 audit module; swap is a one-line change"
- "Condition parser uses regex (not eval): safe, deterministic, no code injection risk"
patterns-established:
- "Escalation check is two-phase: pre-LLM (assistant mode gate) and post-LLM (rule trigger)"
- "assistant mode: escalated thread + end user sender → skip LLM entirely, return static reply"
- "Escalation DM format follows employee metaphor: '{agent.name} needs human assistance'"
requirements-completed:
- AGNT-05
duration: 5min
completed: 2026-03-23
---
# Phase 02 Plan 04: Human Escalation Handoff Summary
**Rule-based and natural-language escalation with Slack DM delivery, Redis assistant-mode gate, and full transcript packaging**
## Performance
- **Duration:** 5 min
- **Started:** 2026-03-23T21:08:30Z
- **Completed:** 2026-03-23T21:13:12Z
- **Tasks:** 2
- **Files modified:** 7
## Accomplishments
- Built complete escalation handler: condition evaluator, transcript builder, and Slack DM pipeline
- Wired escalation checks into the orchestrator message pipeline at both pre-LLM and post-LLM positions
- Added Agent model columns and Alembic migration for escalation configuration
- 28 tests passing (22 unit, 6 integration) covering all escalation behaviors
## Task Commits
1. **Task 1 (TDD RED): Failing tests for escalation handler** - `d489551` (test)
2. **Task 1 (TDD GREEN): Escalation handler implementation** - `4047b55` (feat)
3. **Task 2: Wire escalation into orchestrator pipeline** - `a025cad` (feat)
## Files Created/Modified
- `packages/orchestrator/orchestrator/escalation/__init__.py` - Package init for escalation module
- `packages/orchestrator/orchestrator/escalation/handler.py` - check_escalation_rules, build_transcript, escalate_to_human
- `packages/shared/shared/models/tenant.py` - Added escalation_assignee and natural_language_escalation to Agent model
- `migrations/versions/003_escalation_fields.py` - Alembic migration for new Agent columns
- `packages/orchestrator/orchestrator/tasks.py` - Escalation pre/post checks in _process_message
- `tests/unit/test_escalation.py` - 22 unit tests (rule matching, NL phrases, transcript formatting)
- `tests/integration/test_escalation.py` - 6 integration tests (Slack API mocking, Redis, audit)
## Decisions Made
- **Keyword-based metadata detection (v1):** Rather than LLM-structured output, detect billing keywords and count user turns as a proxy for attempts. Simple, zero-latency, sufficient for v1 escalation rules.
- **Bot token loaded unconditionally:** Changed from conditional load (only when placeholder_ts set) to always load from channel_connections. Escalation DM delivery requires it regardless.
- **No-op audit logger stub:** tasks.py includes a minimal no-op AuditLogger stub so escalation works before Plan 02 (audit) ships. Swap is one import change.
- **Condition parser uses regex, not eval:** Prevents code injection. Supports "X AND Y op Z" format with standard comparison operators.
## Deviations from Plan
None - plan executed exactly as written. The no-op audit logger is specified in the plan's "CRITICAL constraints" section.
## Issues Encountered
None.
## Next Phase Readiness
- Escalation handler ready; can be tested end-to-end with a real Slack bot token in escalation_assignee
- When Plan 02 (audit) ships, replace `_get_no_op_audit_logger()` in tasks.py with the real AuditLogger import
- Conversation metadata detection is v1 keyword-based; can be upgraded to LLM-structured output in a future plan
---
*Phase: 02-agent-features*
*Completed: 2026-03-23*
## Self-Check: PASSED
- All 7 files created/modified: FOUND
- All 3 task commits (d489551, 4047b55, a025cad): FOUND
- All 28 tests passing