humanrail-escalation

name	humanrail-escalation
description	Human-in-the-loop escalation via HumanRail — route low-confidence agent decisions, pre-destructive operation approvals, and ambiguous incident tickets to real human engineers. Human answers are verified and returned as structured output. Workers are paid via Lightning Network. Use when the agent is uncertain, when a destructive change needs explicit human sign-off beyond a ServiceNow CR, or when an ambiguous ticket requires human triage before automated handling.
license	Apache-2.0
user-invokable	true
metadata	{"openclaw":{"requires":{"env":"[Truncated]"}}}

HumanRail Escalation

Safety — Non-Negotiable Rules

NEVER route tasks that expose internal tooling or infrastructure details to workers. HumanRail workers are external humans. Task descriptions must be neutral: describe the decision needed without referencing agent names, internal hostnames, file paths, or credentials. Frame the task as a domain question a knowledgeable engineer would answer — not as "an AI agent needs help."

NEVER use HumanRail as a substitute for ServiceNow Change Management. A HumanRail approval is an engineering judgment call, not a formal ITSM change record. Pre-destructive approvals via HumanRail are a second safety layer — the ServiceNow CR must still exist and be in Implement state before any config push.

NEVER expose PII, device credentials, or configuration secrets in task payloads. Sanitize payloads: use device roles ("core router") not hostnames, use interface descriptions not IP addresses where possible.

ALWAYS wait for verified status before acting. A task with status submitted has been answered by a worker but not yet verified. Only act on the output when status == "verified".

When to Use

Situation	Use HumanRail	Use ServiceNow CR	Use Slack Escalation
Agent confidence low — multiple valid interpretations	✓	—	—
Pre-destructive op beyond normal ITSM gating	✓	Required (both)	—
Ambiguous incident ticket needs triage	✓	—	Notify after
P1/P2 in-flight, need immediate human judgment	✓	—	✓ (both)
Standard config change with approved CR	—	✓	—
Routine maintenance window	—	✓	—
Auto-quarantine endpoint (ISE)	—	—	✓ (ise-incident-response)

MCP Server

Property	Value
Source	prime001/humanrail-mcp-server
Transport	Streamable HTTP (FastMCP, default port 8100)
Language	Python 3.10+
Tools	7 (create_task, get_task, wait_for_task, cancel_task, list_tasks, get_usage, health_check)
Auth	HUMANRAIL_API_KEY (Bearer token — ek_live_... or ek_test_...)
Public endpoint	https://humanrail.dev/mcp (no local install required)

How to Run (Local)

# Install dependencies
pip3 install "mcp[cli]>=1.0.0" httpx

# Start the MCP server (runs on http://127.0.0.1:8100/mcp)
HUMANRAIL_API_KEY=ek_live_your_key python3 $HUMANRAIL_MCP_SCRIPT

# Or use the public endpoint directly (no local install needed):
# Set HUMANRAIL_MCP_URL=https://humanrail.dev/mcp in ~/.openclaw/.env

Get your free API key at humanrail.dev.

Available Tools

Tool	Parameters	What It Does
create_task	task_type, payload, output_schema, risk_tier?, sla_seconds?, payout_currency?, payout_max_amount?, callback_url?, metadata?	Post a task to the human worker pool and return a task ID
get_task	task_id	Get current status and output of a task
wait_for_task	task_id, poll_interval_seconds?, timeout_seconds?	Block until task reaches terminal state (verified, failed, cancelled, expired)
cancel_task	task_id	Cancel a non-terminal task
list_tasks	status?, task_type?, limit?, created_after?, created_before?	List tasks with optional filters
get_usage	—	Org-level usage stats and billing summary
health_check	—	Verify the HumanRail API is reachable

---

Workflow 1: Low-Confidence Decision Escalation

When the agent reaches a decision point where two or more interpretations are equally valid and the wrong choice has significant consequences:

Phase 1: Assess Uncertainty

Identify what the agent cannot determine autonomously:

• Does the context admit multiple valid network design choices?
• Would an experienced engineer need site-specific knowledge the agent doesn't have?
• Is the downstream impact large enough that getting it wrong matters?

If confidence is high enough to proceed, do so — don't over-escalate. HumanRail has an SLA cost.

Phase 2: Frame the Decision Neutrally

Write the task payload without referencing agent internals. The worker is an engineer; give them the facts they need.

task_type: "technical_decision"
payload:
  title:       "BGP policy clarification needed"
  description: |
    A network change is in progress on a dual-homed edge router.
    The router has two upstream transit providers. Policy options:
      A) Prefer Provider-A for all prefixes (lower latency, higher cost)
      B) Prefer Provider-B for all prefixes (higher latency, lower cost)
      C) Split: prefer Provider-A for /24s and shorter, Provider-B for longer prefixes
    Current traffic: ~8 Gbps mixed. No documented preference in the change ticket.
    What is the recommended policy and why?
  context:     "Standard dual-homed BGP edge, no MPLS, IXP peering not in scope."
output_schema:
  type: object
  required: [recommendation, rationale]
  properties:
    recommendation: {type: string, enum: [A, B, C]}
    rationale:      {type: string, minLength: 20}
risk_tier:     "medium"
sla_seconds:   900
payout_currency: "USD"
payout_max_amount: 1.00

Phase 3: Create and Wait

task = create_task(...)
result = wait_for_task(task_id=task["id"], timeout_seconds=900)

Phase 4: Act on Verified Output

Only proceed when result["status"] == "verified". The result["output"] field contains the worker's structured response matching your output_schema.

---

*** HUMAN DECISION IN FLIGHT ***

While wait_for_task polls, do not proceed with the ambiguous action. Post a Slack status update:

"⏳ Waiting for human engineer input on [topic]. Task ID: [id]. ETA: [sla_seconds]s."

If the task expires or fails, fall back to the conservative option and create a ServiceNow incident for manual follow-up.

---

Workflow 2: Pre-Destructive Operation Approval

For operations the agent is authorized to perform but that are irreversible or high-blast-radius — beyond the standard ServiceNow CR gate:

Examples: device reload, write erase, BGP peer teardown affecting production traffic, ISE policy purge.

Phase 1: Baseline and Summarize

Before asking for approval, gather the current state so the human reviewer has complete context.

# Capture pre-change state first
python3 $MCP_CALL "${PYATS_PYTHON:-python3} -u $PYATS_MCP_SCRIPT" get_interface_brief '{"device":"core-rtr-01"}'
python3 $MCP_CALL "${PYATS_PYTHON:-python3} -u $PYATS_MCP_SCRIPT" get_bgp_summary '{"device":"core-rtr-01"}'

Phase 2: Build Approval Request

task_type: "change_approval"
payload:
  title:       "Production reload approval — core edge router"
  description: |
    A device reload is requested to apply a software upgrade from IOS-XE 17.9 to 17.12.
    Pre-change state:
      - BGP peers: 4 active (2 transit, 2 iBGP) — all ESTABLISHED
      - Active sessions: 847 flows
      - Estimated downtime: 3-5 minutes
      - Rollback: IOS-XE 17.9 image retained in flash
    ServiceNow CR: [CR number] — in Implement state.
    Should this reload proceed NOW or be deferred to the next maintenance window?
  urgency:     "high"
output_schema:
  type: object
  required: [decision, notes]
  properties:
    decision: {type: string, enum: [proceed, defer]}
    notes:    {type: string}
risk_tier:     "high"
sla_seconds:   300
payout_currency: "USD"
payout_max_amount: 2.00

Phase 3: Gate on Response

result = wait_for_task(task_id=task["id"], timeout_seconds=300)
if result["output"]["decision"] == "proceed":
    # Execute the destructive operation
else:
    # Defer — log in GAIT, update ServiceNow CR

---

*** HUMAN APPROVAL GATE ***

STOP. The destructive operation MUST NOT execute until result["status"] == "verified" AND result["output"]["decision"] == "proceed".

If wait_for_task times out: default to DEFER. Update the ServiceNow CR with status "awaiting human authorization" and notify the Slack incident channel.

---

Workflow 3: Ambiguous Incident Ticket Triage

When an inbound ServiceNow incident has insufficient information to determine severity, affected CIs, or the correct response team:

Phase 1: Extract What's Known

Pull the raw incident from ServiceNow and identify the gaps:

• Missing: affected device? Affected service? Symptom details?
• Conflicting: multiple possible root causes with different response paths?
• Stale: ticket opened hours ago with no updates — still valid?

Phase 2: Route to Human Triage

task_type: "incident_triage"
payload:
  title:       "Triage: ambiguous network incident ticket"
  description: |
    An incident ticket has insufficient detail for automated handling.
    Ticket summary: [short_description from ServiceNow]
    Known facts:
      - Reported by: [caller_id role/team, no PII]
      - Opened: [timestamp]
      - Impact field: [value]
      - Description: [full description, sanitized]
    Missing or conflicting:
      - [list gaps]
    Please determine: severity (P1/P2/P3/P4), affected CI(s) if identifiable,
    and recommended response team (NOC/NetEng/Security/Application).
output_schema:
  type: object
  required: [severity, team, notes]
  properties:
    severity: {type: string, enum: [P1, P2, P3, P4]}
    team:     {type: string, enum: [NOC, NetEng, Security, Application, Unknown]}
    notes:    {type: string, minLength: 10}
risk_tier:     "medium"
sla_seconds:   600
payout_currency: "USD"
payout_max_amount: 0.50

Phase 3: Apply Triage Output

Use the verified output to:

1. Update the ServiceNow incident severity and assignment group
2. Post a Slack alert at the appropriate level (#netclaw-alerts for P1/P2)
3. Trigger the relevant response workflow

---

Escalation Summary Report Template

Use this when closing a HumanRail-escalated session:

HUMANRAIL ESCALATION SUMMARY
==============================
Task ID:       [task_id]
Task Type:     [task_type]
Opened:        [ISO 8601 timestamp]
Resolved:      [ISO 8601 timestamp]
Worker SLA:    [sla_seconds]s / actual: [elapsed]s

Question Summary:
  [One-paragraph neutral description of what was asked]

Human Decision:
  [Paste result["output"] here]

Action Taken:
  [What the agent did based on the decision]

Outcome:
  [ ] Operation completed successfully
  [ ] Operation deferred — scheduled for [date/window]
  [ ] Escalated to [team] — ServiceNow [INC/CHG number]

---

Checklist

Use before closing any HumanRail-escalated action:

• Task created with neutral, non-internal-leaking payload
• status == "verified" confirmed before acting (not just "submitted")
• Human decision applied exactly — no agent interpretation of ambiguous output
• Slack status posted during wait period
• ServiceNow CR updated with escalation record (if change-related)
• GAIT audit trail records the task ID, human decision, and action taken
• If task expired/failed: conservative fallback applied and INC created

---

Integration with Other Skills

Skill	Integration
servicenow-change-workflow	HumanRail approval is a second-layer gate — ServiceNow CR must still be in Implement state; HumanRail output is added as a work note
ise-incident-response	Use HumanRail for low-confidence risk assessments before the *** HUMAN DECISION POINT *** gate when the on-call engineer is not immediately available
slack-incident-workflow	Post a Slack update when a HumanRail task is created; post result when resolved
gait-session-tracking	Always record HumanRail task IDs, decisions, and resulting actions in the GAIT audit trail
pyats-config-mgmt	Use pre-destructive approval workflow before executing high-risk config pushes

---

Environment Variables

Variable	Required	Example	Description
HUMANRAIL_API_KEY	Yes	ek_live_abc123...	API key from humanrail.dev
HUMANRAIL_MCP_URL	Yes	http://127.0.0.1:8100/mcp	MCP endpoint (local server or https://humanrail.dev/mcp)
HUMANRAIL_MCP_SCRIPT	No	/path/to/server.py	Path to local server.py (set by install.sh; not needed if using public endpoint)
HUMANRAIL_BASE_URL	No	https://api.humanrail.dev/v1	REST API base URL (default: https://api.humanrail.dev/v1)