Sensor Health Reporting Skill

Prerequisites: Run /init-lc to load LimaCharlie guidelines into your CLAUDE.md.

This skill orchestrates parallel sensor health checks across multiple LimaCharlie organizations for fast, comprehensive fleet reporting.

When to Use

Use this skill when the user asks about:

• Connectivity Issues: "Show me sensors online but not sending data"
• Offline Sensors: "List sensors that haven't been online for 7 days"
• Data Availability: "Which sensors have no events in the last hour?"
• Fleet Health: "Find all offline sensors across my organizations"
• Cross-Org Reports: "Show me sensor health across all my orgs"

What This Skill Does

This skill orchestrates sensor health reporting by:

1. Getting the list of user's organizations
2. Spawning parallel lc-essentials:sensor-health-reporter agents (one per org)
3. Aggregating results from all agents
4. Presenting a unified report

Key Advantage: By running one agent per organization in parallel, this skill can check dozens of organizations simultaneously, dramatically reducing execution time.

How to Use

Step 1: Parse User Query

Identify the key parameters:

• Time window: Last hour, 7 days, 30 days, etc.
• Status filter: Online, offline, all sensors
• Data availability: Has events, no events, sparse events
• Scope: All orgs (default) or specific orgs

Step 2: Get Organizations

Use the LimaCharlie API to get the user's organizations:

Task(
  subagent_type="lc-essentials:limacharlie-api-executor",
  model="haiku",
  prompt="Execute LimaCharlie API call:
    - Function: list_user_orgs
    - Parameters: {}
    - Return: RAW"
)

Handle large results with the analyze script if needed.

Step 3: Spawn Parallel Agents

For each organization, spawn a lc-essentials:sensor-health-reporter agent in parallel:

Task(
  subagent_type="lc-essentials:sensor-health-reporter",
  model="haiku",
  prompt="Check sensors in organization '{org_name}' (OID: {oid}) that are online but have not sent telemetry in the last {timeframe}."
)

CRITICAL: Spawn ALL agents in a SINGLE message with multiple Task tool calls to run them in parallel:

<message with multiple Task blocks>
  Task 1: Check org 1
  Task 2: Check org 2
  Task 3: Check org 3
  ...
</message>

Do NOT spawn them sequentially - that defeats the purpose of parallelization.

Step 4: Aggregate Results

Once all agents return:

1. Parse each agent's findings
2. Count total problematic sensors across all orgs
3. Group by organization
4. Identify patterns or anomalies

Step 5: Generate Report

Present a unified report with:

• Executive Summary: Total sensors with issues across all orgs
• Per-Org Breakdown: Findings from each organization
• Context: What the findings mean
• Recommendations: Optional suggestions

Example Workflow

User Query: "Show me sensors online but not reporting events in the last hour"

Step 1: Get current timestamp and calculate 1 hour ago

current=$(date +%s)
one_hour_ago=$(date -d '1 hour ago' +%s)

Step 2: Get org list

Task(
  subagent_type="lc-essentials:limacharlie-api-executor",
  model="haiku",
  prompt="Execute LimaCharlie API call:
    - Function: list_user_orgs
    - Parameters: {}
    - Return: RAW"
)

Step 3: Spawn parallel agents (example with 3 orgs)

# Single message with 3 Task calls
Task(subagent="lc-essentials:sensor-health-reporter", prompt="Check org1...")
Task(subagent="lc-essentials:sensor-health-reporter", prompt="Check org2...")
Task(subagent="lc-essentials:sensor-health-reporter", prompt="Check org3...")

Step 4: Aggregate

Org1: 5 sensors with no data
Org2: 12 sensors with no data
Org3: 0 sensors with issues
Total: 17 sensors

Step 5: Present report

## Sensors Online But Without Events (Last Hour)

**Total: 17 sensors across 2 organizations**

### org1 (5 sensors)
- sensor-id-1
- sensor-id-2
...

### org2 (12 sensors)
- sensor-id-6
...

### Analysis
These sensors are connected but not generating events...

Handling Large Result Sets

When list_user_orgs returns a resource_link, use the analyze script from the plugin root. From this skill's base directory (shown at the top of the skill prompt), the script is at ../../scripts/analyze-lc-result.sh:

# Path: {skill_base_directory}/../../scripts/analyze-lc-result.sh
bash "{skill_base_directory}/../../scripts/analyze-lc-result.sh" "<resource_link>"
jq -r '.orgs[] | "\(.oid)|\(.name)"' /tmp/lc-result-*.json

Time Window Calculations

Use bash to calculate timestamps:

# Current time
date +%s

# X hours ago
date -d 'X hours ago' +%s

# X days ago
date -d 'X days ago' +%s

# X weeks ago
date -d 'X weeks ago' +%s

Performance Tips

1. Always spawn agents in parallel - Use a single message with multiple Task calls
2. Limit scope if needed - For quick checks, allow user to specify specific orgs
3. Use Haiku model - Sensor health checks are straightforward data gathering
4. Handle errors gracefully - If one org fails, continue with others
5. Cache org list - If doing multiple related queries, reuse the org list

Error Handling

If an agent fails:

• Log the error for that organization
• Continue processing other organizations
• Include error summary in final report
• Don't let one org failure block the entire report

Report Format Template

## {Query Title}

**Summary**: {Total count} sensors across {N} organizations

### {Org Name 1} ({count} sensors)
- {sensor-id-1}
- {sensor-id-2}
...

### {Org Name 2} ({count} sensors)
- {sensor-id-x}
...

### Organizations with No Issues
- {Org Name 3}
- {Org Name 4}

### Analysis
{Context about findings}

### Recommendations
{Optional suggestions}

Important Constraints

• Parallel Execution: ALWAYS spawn agents in parallel (single message, multiple Tasks)
• OID Format: Organization ID is a UUID, not the org name
• Time Limits: Data availability checks must be <30 days
• Model: Always use "haiku" for the sub-agents
• Error Tolerance: Continue with partial results if some orgs fail

Related Skills

• sensor-tasking - For sending commands to sensors (live response, data collection)
• sensor-coverage - For comprehensive asset inventory and coverage gap analysis

Related Functions

From limacharlie-call skill:

• list_user_orgs - Get organizations
• get_online_sensors - Get online sensor list (used by agent)
• get_time_when_sensor_has_data - Check data timeline (used by agent)
• list_sensors - Get all sensors (used by agent for offline checks)