Hindsight

Hindsight Memory (Self-Hosted)

Persistent, structured memory via the official Hindsight CLI (v0.4.14). Store knowledge during tasks, recall context before starting new ones, reflect to synthesize patterns.

Bank Detection

Auto-detect bank from git repo name (worktree-safe — --git-common-dir makes every worktree of a repo resolve to ONE shared bank, not the worktree folder name):

BANK=$( { d=$(git rev-parse --git-common-dir 2>/dev/null) && basename "$(dirname "$(readlink -f "$d")")"; } || echo "general" )

Or use the helper: BANK=$(./scripts/hs-bank-id.sh)

CLI Config

• Binary: hindsight at ~/.local/bin/hindsight (official v0.4.14)
• Config: ~/.hindsight/config (TOML: api_url, api_key)
• Endpoint: https://api.hs.delo.sh (resolves to localhost via /etc/hosts)
• Reconfigure: hindsight configure --api-url <url> --api-key <key>

Core Operations

Retain (store knowledge)

hindsight memory retain $BANK "npm test requires --experimental-vm-modules" \
  --context "debugging"

Context categories: architecture, conventions, debugging, deployment, dependencies, preferences, session-summary, code-edit

With document tracking (same doc-id = upsert, replacing old facts):

hindsight memory retain $BANK "Project deadline extended to April 15" \
  --context "conventions" --doc-id "sprint-notes-2026-03"

Recall (retrieve context)

hindsight memory recall $BANK "What testing patterns does this project use?"

With options:

hindsight memory recall $BANK "How are auth and session management connected?" \
  --budget high --max-tokens 8192 --fact-type world,observation

Budget levels: low (fast, shallow), mid (balanced, default), high (deep graph traversal)

JSON output for programmatic use:

hindsight memory recall $BANK "query" -o json | jq '.results[].text'

Reflect (synthesize with agentic reasoning)

Reflect runs an agentic loop: autonomously searches memories, applies bank disposition, generates grounded response with citations.

hindsight memory reflect $BANK "What architectural decisions have shaped this project?"

With context and higher budget:

hindsight memory reflect $BANK "Should we migrate to event sourcing?" \
  --context "architecture review" --budget high

Response includes based_on.memories, based_on.mental_models, based_on.directives for citation traceability.

Mental Models (pre-computed reflect responses)

Mental models are curated summaries checked first during reflect. Faster, more consistent answers for recurring topics. Top of the retrieval hierarchy.

hindsight mental-model create $BANK \
  --name "Project Architecture" \
  --source-query "What is the overall system architecture?"

hindsight mental-model list $BANK
hindsight mental-model refresh $BANK <mental_model_id>
hindsight mental-model delete $BANK <mental_model_id>

Directives (hard rules for reflect)

Always-enforced rules during reflect. Unlike disposition (soft personality influence), directives are strict behavioral constraints.

hindsight directive create $BANK \
  --name "Code Style" \
  --content "Always recommend Python type hints and strict typing"

hindsight directive list $BANK
hindsight directive update $BANK <directive_id> --active false
hindsight directive delete $BANK <directive_id>

Documents (source tracking)

Documents track where memories came from. Re-retaining with the same doc-id replaces old facts (upsert). Deleting a document removes all its extracted memories.

hindsight document list $BANK
hindsight document get $BANK <document_id>
hindsight document delete $BANK <document_id>

Bank Management

hindsight bank list
hindsight bank stats $BANK
hindsight bank disposition $BANK
hindsight bank disposition $BANK --skepticism 4 --literalism 3 --empathy 2
hindsight bank mission $BANK "Extract technical facts, conventions, and decisions."

Disposition (Personality Traits)

Three traits (1-5 scale) that influence reflect behavior:

Retrieval Hierarchy (during reflect)

1. Mental Models - User-curated summaries (highest priority)
2. Observations - Consolidated knowledge (auto-generated from retained facts)
3. Raw Facts - Ground truth memories (world, experience, observation types)

Fact Types

• world - Objective facts ("Alice works at Google")
• experience - Conversational events ("User asked about deployment")
• observation - Consolidated patterns (auto-synthesized from multiple facts)

Multi-Bank Routing Architecture

For multi-agent or multi-project setups, use domain-first routing to prevent cross-project pollution and recall noise.

Strategy

• Primary bank = domain/product (source of truth). Example: wean, chorescore, 33god-core
• Secondary bank(s) = role/hierarchy overlay. Example: exec-office for leadership decisions
• Global fallback bank. Example: 33GOD for org-wide context

Avoid agent-only banks as canonical memory. They drift when agents switch projects.

Routing Pattern

For each agent/session:

1. Resolve writeBank (where new memories are retained)
2. Resolve recallBanks[] (ordered primary -> secondary -> fallback)
3. On prompt build, recall from each bank and merge results
4. On run end/reset/tool-error, retain high-signal facts into writeBank

Capture Policy (high signal only)

Retain automatically for:

• Explicit memory intent ("remember", "don't forget", preferences)
• Post-run user facts/decisions
• High-level architectural patterns
• Pre-reset session summaries
• Non-standard system paths/configs
• Tool errors (debugging context)

Do NOT retain:

• Cron/noise/system spam
• Tiny one-word messages
• Slash commands

Failure Modes

When to Retain

• Discovered a bug fix or workaround
• Found a project convention or pattern
• Learned a user preference
• Completed a significant task (summarize what was done)
• Found something that didn't work (negative knowledge is valuable)

When to Recall

• Before starting any non-trivial task
• When working in an unfamiliar area of the codebase
• When making architectural or tooling decisions
• When the user asks about past work or patterns

Best Practices

1. Be specific: "npm test requires --experimental-vm-modules" not "tests need a flag"
2. Include outcomes: Store what worked AND what didn't
3. Use context categories: Tag with the right context for better retrieval
4. Recall first: Check for relevant context before starting work
5. Don't duplicate: Check if knowledge already exists before retaining
6. Use document_id: Group related session facts so they compound, not duplicate
7. Create mental models: For topics you reflect on repeatedly
8. Use directives: For hard rules that must always be enforced during reflect

OpenClaw Plugin Integration

The local OpenClaw plugin (workspace/.openclaw/extensions/hindsight-memory/) automates capture and recall so agents don't need to manually call hindsight. Config lives in openclaw.json under plugins.entries.hindsight-memory.

What the plugin automates

Routing resolution order

The plugin resolves writeBank and recallBanks per-request through layered routing:

1. Start with defaultBank + globalRecallBanks
2. Apply agentRoutes[agentId] override
3. Apply sessionPrefixRoutes (longest-prefix match on session key)
4. Apply workspaceRoutes (substring match on workspace dir)
5. Apply channelRoutes (exact match on channel ID)
6. Dedupe and cap at maxRecallBanks (default: 4)

Noise filtering

The plugin skips: messages < 24 chars, slash commands, system messages, heartbeat pings, cron hooks, and upstream errors. The MEMORY_INTENT_RE pattern triggers immediate capture for explicit memory phrases.

Key config knobs

Claude Code Hook Integration

The Claude Code analog of the OpenClaw plugin. Three hooks under ~/.claude/hooks/ auto-recall on every user prompt, auto-retain on every file edit, and emit a per-session journal at ~/.claude/.hindsight-journal/YYYY-mm-dd-h-m-s.md that explains in plain English what was searched, what bank was resolved, how effective the recall was, and what was retained (with LLM-synthesized rationale for the subjective parts).

The Stop hook must detach the journal writer with setsid nohup … </dev/null >/dev/null 2>&1 & — Claude Code reaps the hook's process group on return, killing any plain & background that's still waiting on the 30-second hindsight memory reflect call.

Full reference (event schema, env knobs, manual ops, failure modes): references/claude-code-journal.md.

Deterministic Governance (Single-Skill Canonical)

This hindsight skill is the single canonical memory package. Keep governance here (do not split into a second memory-governance skill).

Required invariants

• hindsight-memory plugin enabled
• autoRecall=true
• autoCapture=true
• captureDirectIntent=true
• captureToolErrors=true
• Explicit defaultBank and agentRoutes

Deterministic audit

Run:

python3 /home/delorenj/.agents/skills/hindsight/scripts/audit_hindsight_memory.py

Expect PASS. Non-zero exit means policy drift.

Governance Principles

Clock independence

Three independent clocks operate in the OpenClaw runtime. They must not be conflated:

• Heartbeat (agent runtime): Owns triage/dispatch loops and proactive checks
• Cron (scheduler): Owns exact-time reminders and isolated scheduled tasks
• Hindsight (memory backend): Owns memory extraction, indexing, and consolidation independently

If cron jobs duplicate heartbeat behavior, remove the cron jobs. If heartbeat tries to manage memory refresh timing, stop it.

Automated curation replaces manual promotion

The old pattern of writing daily logs to memory/YYYY-MM-DD.md and manually promoting to MEMORY.md is replaced by Hindsight's hierarchy:

The plugin's before_compaction and session_end hooks ensure context survives session boundaries without manual intervention.