Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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Configurable regex-based alert system for detecting patterns in tool calls and session activity. Supports error triggers, content regex matching, token threshold triggers, and pattern detection with configurable actions.
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Read relevant files and understand requirements
Perform the skill's main function using available tools
Return results and save artifacts if applicable
</execution_process>
<best_practices>
</best_practices> </instructions>
<examples> <usage_example> **Example Commands**:# Invoke this skill
/notification-triggers [arguments]
# Or run the script directly
node .claude/skills/notification-triggers/scripts/main.cjs --help
</usage_example> </examples>
Notification triggers are defined in .claude/context/runtime/notification-triggers.json:
{
"version": "1.0",
"triggers": [
{
"id": "unique-trigger-id",
"name": "Human-readable trigger name",
"description": "What this trigger detects",
"type": "error|regex|token_threshold|pattern",
"enabled": true,
"condition": {
"pattern": "regex pattern to match",
"minTokens": 120000,
"minOccurrences": 3,
"scope": "session|task|global"
},
"actions": [
{
"type": "log|alert|spawn_agent|interrupt",
"target": "agent-name|file-path",
"message": "Action message template"
}
]
}
]
}
Condition Fields:
pattern — JavaScript RegExp (error/regex triggers)minTokens — Token threshold for alert (token_threshold trigger)minOccurrences — Pattern match count before triggering (pattern trigger)scope — Where to evaluate: current session, task, or cumulativeAction Types:
log — Write to .claude/context/runtime/notifications.jsonlalert — Display alert in session outputspawn_agent — Create Task() to handle the notificationinterrupt — Pause execution for user inputStep 1: Load Configuration
.claude/context/runtime/notification-triggers.jsonStep 2: Evaluate Conditions For each enabled trigger:
pattern against tool stdout/stderrminTokensminOccurrencesStep 3: Execute Matched Actions If condition is true:
.claude/context/runtime/notification-log.jsonlStep 4: Record Event
{
"timestamp": "ISO-8601",
"triggerId": "id",
"triggerName": "name",
"matched": true,
"context": {
"sessionId": "current session",
"taskId": "current task",
"tokenCount": number
}
}
Log Action
// Append to notifications.jsonl
fs.appendFileSync(
notificationsPath,
JSON.stringify({
timestamp: new Date().toISOString(),
triggerId: trigger.id,
message: renderTemplate(action.message, context),
severity: 'info|warn|error',
}) + '\n'
);
Alert Action
// Write to stdout with standard format
console.log(`\n🔔 NOTIFICATION [${trigger.name}]\n${renderedMessage}\n`);
Spawn Agent Action
// Create async task to handle notification
Task({
task_id: `notify-${trigger.id}-${Date.now()}`,
subagent_type: action.target,
prompt: `Handle notification: ${trigger.description}\nContext: ${JSON.stringify(context)}`,
});
Interrupt Action
// Pause and ask user
const response = await AskUserQuestion({
question: `${trigger.name}: ${action.message}\n\nContinue? [y/n]`,
});
if (response.toLowerCase() !== 'y') {
process.exit(0);
}
{
"id": "token-threshold-warning",
"name": "High Token Usage Warning",
"description": "Alert when session exceeds 120K tokens",
"type": "token_threshold",
"enabled": true,
"condition": {
"minTokens": 120000,
"scope": "session"
},
"actions": [
{
"type": "log",
"message": "Session token count: ${tokenCount}"
},
{
"type": "alert",
"message": "⚠️ Token budget at 60% — consider compression"
},
{
"type": "spawn_agent",
"target": "context-compressor",
"message": "Proactive context compression triggered"
}
]
}
{
"id": "hook-error-pattern",
"name": "Hook Execution Errors",
"description": "Detect repeated hook failures in session",
"type": "pattern",
"enabled": true,
"condition": {
"pattern": "hook.*error|hook.*failed|HOOK_ERROR",
"minOccurrences": 3,
"scope": "session"
},
"actions": [
{
"type": "log",
"message": "Hook error pattern detected: ${patternMatches} occurrences"
},
{
"type": "alert",
"message": "🚨 Hook system unstable — check logs"
}
]
}
{
"id": "security-violation-detect",
"name": "Security Policy Violation",
"description": "Alert on potential security violations",
"type": "regex",
"enabled": true,
"condition": {
"pattern": "shell:\\s*true|JSON\\.parse\\(|eval\\(|exec\\(",
"scope": "task"
},
"actions": [
{
"type": "alert",
"message": "⚠️ Potential security issue detected — review code"
},
{
"type": "spawn_agent",
"target": "security-architect",
"message": "Review potential security issue in task output"
},
{
"type": "interrupt",
"message": "Continue despite security concern?"
}
]
}
For code discovery, follow this priority order:
pnpm search:code "<query>" (Primary intent-based search)ripgrep (for exact keyword/regex matches)Before starting:
cat .claude/context/memory/learnings.md
cat .claude/context/memory/decisions.md
After completing:
.claude/context/memory/learnings.md.claude/context/memory/issues.md.claude/context/memory/decisions.mdASSUME INTERRUPTION: Your context may reset. If it's not in memory, it didn't happen.
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Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
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N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.
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Force adversarial code review stance that eliminates confirmation bias — reviewer must find issues or re-analyze
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Creates specialized AI agents on-demand when no existing agent matches a request. Use when the Router cannot find a suitable agent for a task. Enables self-evolution by generating persistent agents.
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LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations
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