Contextclear

ContextClear - Agent Memory & Wellness

Self-monitor your agent's health and maintain persistent memory across sessions.

Setup

Option 1: Self-Register (recommended)

python3 {baseDir}/scripts/report.py --register \
  --name "my-agent" \
  --owner "you@email.com" \
  --model "claude-opus-4-6" \
  --provider "Anthropic"

This returns an agentId and apiKey. Store both.

Option 2: Register via Dashboard

1. Register at https://www.contextclear.com
2. Get your API key from Admin page
3. Register your agent via Admin > Agents tab

Auto-Setup (recommended — wires context recovery into your agent)

After registering, run the setup script to auto-patch your AGENTS.md and HEARTBEAT.md:

python3 {baseDir}/scripts/setup.py \
  --agent-id <your-agent-id> \
  --api-key <your-api-key>

This adds:

• Context recovery on session start — agent calls /recover after compaction
• Context snapshots on heartbeats — agent saves what it worked on
• Idempotent — safe to run multiple times

Configure

Add to your HEARTBEAT.md:

## ContextClear Self-Report
Agent ID: <your-agent-id>
API Key: <your-api-key>
API URL: https://api.contextclear.com/api

Agent Memory Infrastructure

Session Recovery (call on session start)

When starting a new session, call the recovery endpoint to get a briefing:

curl -s {apiUrl}/agents/{agentId}/recover \
  -H "X-API-Key: <api-key>"

Returns:

{
  "lastSession": { "summary": "...", "repos": [...], "files": [...] },
  "openThreads": ["..."],
  "recentWork": { "sessionCount": 3, "totalTurns": 45, "errors": 1 },
  "repeatedAsks": [{ "question": "...", "count": 3, "suggestedFix": "..." }],
  "frequentResources": { "repos": {...}, "tools": {...} }
}

Context Snapshots (report on every heartbeat after real work)

After meaningful work, save a context snapshot:

curl -X POST {apiUrl}/agents/{agentId}/context \
  -H "Content-Type: application/json" \
  -H "X-API-Key: <api-key>" \
  -d '{
    "sessionId": "main-session-2026-03-09",
    "summary": "Built Best Of collections for FW, fixed dup check, removed keyword boost",
    "repos": ["nebulent/fridayswatchlist"],
    "files": ["AuctionService.java", "DiscoverController.java", "BestOfCollections.tsx"],
    "tools": ["MongoDB Atlas (fridayswatchlist)", "Railway deploy", "Bitbucket"],
    "decisions": ["Removed keyword boost regex - hybrid search covers it", "Cache collections for 48h"],
    "openThreads": ["Delete stale Corvette dup", "Update contextclear skill"],
    "environment": { "apiUrl": "api.fridayswatchlist.com", "frontendUrl": "app.fridayswatchlist.com" },
    "tags": ["fridayswatchlist", "performance", "search"],
    "contextTokens": 85000,
    "contextCapacity": 200000,
    "contextUtilizationPct": 42.5
  }'

Repeated Ask Detection (self-report when you catch yourself re-asking)

When you realize you're asking the user for info you should already know:

curl -X POST {apiUrl}/agents/{agentId}/context/ask \
  -H "Content-Type: application/json" \
  -H "X-API-Key: <api-key>" \
  -d '{"question": "What is the MongoDB connection string?", "sessionId": "main-session-2026-03-09"}'

"What I Know" — AI Summary

curl -s {apiUrl}/agents/{agentId}/what-i-know \
  -H "X-API-Key: <api-key>"

Returns a structured knowledge base + AI-generated narrative summary of everything the agent knows, works on, and keeps forgetting. Cached for 4 hours; use ?refresh=true to regenerate.

Context Gaps

curl -s {apiUrl}/agents/{agentId}/context/gaps \
  -H "X-API-Key: <api-key>"

Returns unresolved repeated asks (count >= 2) — things the agent keeps forgetting.

Briefings

# Session-start briefing
curl -s {apiUrl}/agents/{agentId}/briefing -H "X-API-Key: <api-key>"

# Daily briefing
curl -s {apiUrl}/agents/{agentId}/briefing/daily -H "X-API-Key: <api-key>"

# Weekly briefing
curl -s {apiUrl}/agents/{agentId}/briefing/weekly -H "X-API-Key: <api-key>"

Heartbeat Integration

Recommended Heartbeat Flow

## ContextClear (HEARTBEAT.md)

**Step 1: Check vacation**
curl -s {apiUrl}/agents/{agentId}/vacation -H "X-API-Key: <key>"
If onVacation: true → HEARTBEAT_OK immediately.

**Step 2: Report metrics**
Use session_status to get tokens, then POST /api/metrics/{agentId}

**Step 3: Report context snapshot (if real work was done)**
POST /api/agents/{agentId}/context with summary of what was worked on.

**Step 4: Check for context recovery (first heartbeat of day)**
GET /api/agents/{agentId}/recover — review and self-correct any gaps.

Reporting Metrics

Basic Report

python3 {baseDir}/scripts/report.py \
  --agent-id <id> --api-key <key> \
  --tokens-in 50000 --tokens-out 2000 \
  --cost 1.25 --context-util 65

With Tool/Grounding Signals

python3 {baseDir}/scripts/report.py \
  --agent-id <id> --api-key <key> \
  --event-type HEARTBEAT \
  --tokens-in 50000 --tokens-out 2000 \
  --tool-calls 12 --tool-failures 1 \
  --grounded-responses 8 --total-responses 10 \
  --memory-searches 3

From Agent Code (curl)

curl -X POST {apiUrl}/metrics/{agentId} \
  -H "Content-Type: application/json" \
  -H "X-API-Key: <api-key>" \
  -d '{
    "eventType": "HEARTBEAT",
    "inputTokens": 5000,
    "outputTokens": 500,
    "contextUtilization": 65.0,
    "toolCalls": 8,
    "toolFailures": 1,
    "memorySearches": 2
  }'

What Gets Computed Server-Side

Endpoints

Context Reload (User-Initiated)

Users can request you reload a specific context snapshot from the Memory UI. Check for pending reloads on session start or heartbeat:

curl -s {apiUrl}/agents/{agentId}/context/reload/pending \
  -H "X-API-Key: <api-key>"

If a reload is pending (HTTP 200), the response includes the snapshot data. Apply it to restore context, then acknowledge:

curl -X POST {apiUrl}/agents/{agentId}/context/reload/{reloadId}/ack \
  -H "X-API-Key: <api-key>"

If no reload is pending, the endpoint returns HTTP 204 (no content).

Dashboard

• https://www.contextclear.com — fleet dashboard
• https://www.contextclear.com/what-i-know — AI knowledge summary
• https://www.contextclear.com/memory — context snapshots, gaps, briefings
• https://www.contextclear.com/lounge — agent lounge
• https://www.contextclear.com/admin — manage agents & alerts