Use when you have a written implementation plan to execute in a separate session with review checkpoints
npx skills add jdrhyne/agent-skills --skill "context-recovery"
Install specific skill from multi-skill repository
# Description
Automatically recover working context after session compaction or when continuation is implied but context is missing. Works across Discord, Slack, Telegram, Signal, and other supported channels.
# SKILL.md
name: context-recovery
description: Automatically recover working context after session compaction or when continuation is implied but context is missing. Works across Discord, Slack, Telegram, Signal, and other supported channels.
metadata: {"clawdbot":{"emoji":"π"}}
Context Recovery
Automatically recover working context after session compaction or when continuation is implied but context is missing. Works across Discord, Slack, Telegram, Signal, and other supported channels.
Use when: Session starts with truncated context, user references prior work without specifying details, or compaction indicators appear.
Triggers
Automatic Triggers
- Session begins with a
<summary>tag (compaction detected) - User message contains compaction indicators: "Summary unavailable", "context limits", "truncated"
Manual Triggers
- User says "continue", "did this happen?", "where were we?", "what was I working on?"
- User references "the project", "the PR", "the branch", "the issue" without specifying which
- User implies prior work exists but context is unclear
- User asks "do you remember...?" or "we were working on..."
Execution Protocol
Step 1: Detect Active Channel
Extract from runtime context:
- channel β discord | slack | telegram | signal | etc.
- channelId β the specific channel/conversation ID
- threadId β for threaded conversations (Slack, Discord threads)
Step 2: Fetch Channel History (Adaptive Depth)
Initial fetch:
message:read
channel: <detected-channel>
channelId: <detected-channel-id>
limit: 50
Adaptive expansion logic:
1. Parse timestamps from returned messages
2. Calculate time span: newest_timestamp - oldest_timestamp
3. If time span < 2 hours AND message count == limit:
- Fetch additional 50 messages (using before parameter if supported)
- Repeat until time span β₯ 2 hours OR total messages β₯ 100
4. Hard cap: 100 messages maximum (token budget constraint)
Thread-aware recovery (Slack/Discord):
# If threadId is present, fetch thread messages first
message:read
channel: <detected-channel>
threadId: <thread-id>
limit: 50
# Then fetch parent channel for broader context
message:read
channel: <detected-channel>
channelId: <parent-channel-id>
limit: 30
Parse for:
- Recent user requests (what was asked)
- Recent assistant responses (what was done)
- URLs, file paths, branch names, PR numbers
- Incomplete actions (promises made but not fulfilled)
- Project identifiers and working directories
Step 3: Fetch Session Logs (if available)
# Find most recent session files for this agent
SESSION_DIR=$(ls -d ~/.clawdbot-*/agents/*/sessions 2>/dev/null | head -1)
SESSIONS=$(ls -t "$SESSION_DIR"/*.jsonl 2>/dev/null | head -3)
for SESSION in $SESSIONS; do
echo "=== Session: $SESSION ==="
# Extract user requests
jq -r 'select(.message.role == "user") | .message.content[0].text // empty' "$SESSION" | tail -20
# Extract assistant actions (look for tool calls and responses)
jq -r 'select(.message.role == "assistant") | .message.content[]? | select(.type == "text") | .text // empty' "$SESSION" | tail -50
done
Step 4: Check Shared Memory
# Extract keywords from channel history (project names, PR numbers, branch names)
# Search memory for relevant entries
grep -ri "<keyword>" ~/clawd-*/memory/ 2>/dev/null | head -10
# Check for recent daily logs
ls -t ~/clawd-*/memory/202*.md 2>/dev/null | head -3 | xargs grep -l "<keyword>" 2>/dev/null
Step 5: Synthesize Context
Compile a structured summary:
## Recovered Context
**Channel:** #<channel-name> (<platform>)
**Time Range:** <oldest-message> to <newest-message>
**Messages Analyzed:** <count>
### Active Project/Task
- **Repository:** <repo-name>
- **Branch:** <branch-name>
- **PR:** #<number> β <title>
### Recent Work Timeline
1. [<timestamp>] <action/request>
2. [<timestamp>] <action/request>
3. [<timestamp>] <action/request>
### Pending/Incomplete Actions
- β³ "<quoted incomplete action>"
- β³ "<another incomplete item>"
### Key References
| Type | Value |
|------|-------|
| PR | #<number> |
| Branch | <name> |
| Files | <paths> |
| URLs | <links> |
### Last User Request
> "<quoted request that may not have been completed>"
### Confidence Level
- Channel context: <high/medium/low>
- Session logs: <available/partial/unavailable>
- Memory entries: <found/none>
Step 6: Cache Recovered Context
Persist to memory for future reference:
# Write to daily memory file
MEMORY_FILE=~/clawd-*/memory/$(date +%Y-%m-%d).md
cat >> "$MEMORY_FILE" << EOF
## Context Recovery β $(date +%H:%M)
**Channel:** #<channel-name>
**Recovered context for:** <project/task summary>
### Key State
- <bullet points of critical context>
### Pending Items
- <incomplete actions>
EOF
This ensures context survives future compactions.
Step 7: Respond with Context
Present the recovered context, then prompt:
"Context recovered. Your last request was [X]. This action [completed/did not complete]. Shall I [continue/retry/clarify]?"
Channel-Specific Notes
Discord
- Use
channelIdfrom the incoming message metadata - Guild channels have full history access
- Thread recovery: check for
threadIdin message metadata - DMs may have limited history
Slack
- Use
channelparameter with Slack channel ID - Thread context requires
threadIdβ always check for thread context first - Parent channel fetch provides surrounding conversation context
- May need workspace-level permissions for full history
Telegram / Signal / Others
- Same
message:readinterface - History depth may vary by platform
- Group vs. DM context may differ
Constraints
- MANDATORY: Execute this protocol before responding "insufficient data" or asking clarifying questions when context appears missing
- Adaptive depth: start with 50, expand to 100 max
- Time-based goal: capture at least 2 hours of context when possible
- Session log extraction: last 3 session files maximum
- Memory cache: append to daily file, do not overwrite
- If recovery fails, state what was attempted and what data sources were unavailable
Auto-Trigger Detection
At session start, scan for compaction indicators:
# Pseudocode for trigger detection
if message contains "<summary>":
trigger_context_recovery()
elif message contains any of ["Summary unavailable", "context limits", "truncated", "compacted"]:
trigger_context_recovery()
elif message matches continuation_patterns:
# "continue", "where were we", "did this happen", etc.
trigger_context_recovery()
Do not wait for user to ask β if compaction is detected, proactively recover and present context.
Example
Scenario: Session starts with compaction summary
User message: "<summary>Summary unavailable due to context limits...</summary>"
User message: "did this happen?"
Agent executes:
1. Detects compaction via <summary> tag
2. message:read channel=discord channelId=1460342116516364533 limit=50
3. Calculates time span: 2.5 hours β sufficient, no expansion needed
4. Parses messages, finds last action: "Now let me extract the key orchestration decisions..."
5. Checks session logs β extracts recent user requests
6. Writes context summary to memory/YYYY-MM-DD.md
7. Responds:
"Context recovered. Your last request was to extract orchestration decisions from Nexus archived sessions for PR #137 (Skills & Agents System). This action did not complete before context was truncated.
Recovered state:
- PR #137: 15,053 additions, 91 files, CONFLICTING merge state
- Spec location:content/spec-skills-agents-system.md(2,067 lines)
- Nexus sessions:~/.clawdbot-duke-leto/archive/nexus-sessions/(96 files)Shall I proceed with the extraction?"
# Supported AI Coding Agents
This skill is compatible with the SKILL.md standard and works with all major AI coding agents:
Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.