Memory Boost

v1.0.0

Persistent task memory and keep-alive loop for OpenClaw agents. Every task gets durable notes. Arm the loop for long tasks, disarm when done. No external dep...

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byTerry Hundley@techieter

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for techieter/agent-memory-boost.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Memory Boost" (techieter/agent-memory-boost) from ClawHub.
Skill page: https://clawhub.ai/techieter/agent-memory-boost
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install agent-memory-boost

ClawHub CLI

Package manager switcher

npx clawhub@latest install agent-memory-boost
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Purpose & Capability
The name/description (persistent task notes + keep‑alive loop) matches the files and SKILL.md behavior. There are no unrelated required env vars or external services. The included prompts and templates are all about managing ~/.openclaw/memory/ and task notes, which is coherent with the stated purpose.
Instruction Scope
SKILL.md and the prompt files repeatedly restrict runtime scope to ~/.openclaw/memory/ and describe specific read/write rules (create RESUME/CHECKLIST/DOCS, update heartbeats, write WATCHDOG.md, etc.). There are no instructions in those files to access network endpoints, other system paths, or unrelated credentials. The installer modifies OpenClaw cron configuration (expected for a keep‑alive feature).
Install Mechanism
There is no remote download; install.sh copies files into ~/.openclaw and then registers 5 scheduled jobs. If the OpenClaw CLI is absent, the script directly edits ~/.openclaw/cron/jobs.json via an embedded Python snippet. Directly editing jobs.json (enabled=true) is more intrusive than using a vetted API/CLI and is worth manual review prior to running the installer.
Credentials
The skill requests no environment variables, no external credentials, and no config paths beyond the OpenClaw home directory. That is proportionate for a purely local task‑memory/monitoring skill.
Persistence & Privilege
The installer creates five recurring jobs that are enabled by default and attributed to the skill. Those jobs give the skill recurring autonomous execution within OpenClaw (normal for scheduled jobs) — review and control these entries (or leave them disabled) if you want to limit autonomous behavior.
Assessment
This package appears to do what it claims: create/maintain task notes under ~/.openclaw/memory/ and add scheduled jobs that run watchdog/validator/replayer/escalator/smoke‑test logic. Before installing: 1) Inspect the prompt files (prompts/*.md) to confirm you’re comfortable with the automated behaviors and the strict 'only touch ~/.openclaw/memory/' scope they declare. 2) Prefer installing when the openclaw CLI is present so jobs are added via the CLI; if not, the installer will directly modify ~/.openclaw/cron/jobs.json — review the produced jobs.json before enabling. 3) After install, verify the five cron jobs and consider disabling them until you’ve tested the smoke test. 4) Keep a backup of ~/.openclaw/ before running the installer and note the uninstall steps in INSTALL.md. If you want additional assurance, run the installer in a controlled environment (or with a disposable OpenClaw home) and inspect the resulting jobs.json and memory folder contents.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

OSmacOS · Linux
latestvk971gc2e42jfmg5yj7qeggeyss84482n
100downloads
0stars
1versions
Updated 3w ago
v1.0.0
MIT-0
macOS, Linux

Memory Boost

Two things in one skill:

  1. Task Memory — every task automatically gets persistent notes so work survives restarts
  2. Keep-Alive Loop — arm it for long tasks, disarm when done

No external dependencies. Everything lives inside ~/.openclaw/memory/.

Task Memory

When you receive any task, automatically create a task folder:

~/.openclaw/memory/tasks/<task-name>/
  RESUME.md      — status, heartbeat, next action, key files, restart note
  CHECKLIST.md   — step-by-step progress
  DOCS.md        — goal, decisions, gotchas, notes for next session

RESUME.md must contain:

  • Task name and one-line description
  • Current status (active / stalled / complete)
  • Last heartbeat (date and time, updated whenever you touch the task)
  • Next action (one concrete step)
  • Key files (relevant paths)
  • Restart note (what a fresh session needs to pick this up)

CHECKLIST.md must contain:

  • Numbered or checkbox steps
  • Current status of each step
  • A final verification step

DOCS.md must contain:

  • Goal
  • Important decisions and why
  • File paths that matter
  • Gotchas and failure modes
  • Notes for the next session

Update rules:

  • Create notes before starting a multi-step task.
  • Update RESUME.md before and after major milestones.
  • Mark checklist items complete as soon as they are done.
  • Add discoveries and gotchas to DOCS.md immediately.
  • Always update the heartbeat when touching an active task.
  • A heartbeat older than 24 hours or a missing next action means the task is stale.

Storage path:

Task notes live in ~/.openclaw/memory/tasks/. The canonical template is at {baseDir}/templates/TEMPLATE.md.

Keep-Alive Loop

For long-running tasks, the keep-alive loop prevents silent failures.

Controls

  • /loop-start — arms the loop. Monitoring jobs begin running.
  • /loop-stop — disarms the loop. Jobs no-op. No wasted tokens.

The loop state lives in ~/.openclaw/memory/LOOP-STATE.md.

Monitoring layers

When armed, three jobs watch your agent's work:

LayerJob nameScheduleWhat it does
Watchdogboost-watchdog*/15 * * * *Detects stalls, writes WATCHDOG.md
Replayerboost-replayer*/30 * * * *Takes one concrete step on a stalled task
Escalatorboost-escalator0 * * * *Forces fresh-session handoff on repeated stalls

Integrity layers

These run always, regardless of loop state:

LayerJob nameScheduleWhat it does
Validatorboost-validator5 * * * *Repairs missing notes, refreshes task index
Smoke testboost-smoke-test0 */6 * * *Verifies the skill itself is healthy

Watchdog rules:

  • Write WATCHDOG.md only when you can prove a stall. Do not manufacture problems.
  • Include: folder path, blocker, why-stalled tag, one next action.
  • Why-stalled tags: blocked-on-external, ambiguous-next-step, repeated-promise, missing-context

Replayer rules:

  • Take only one mechanical step per pass. No speculative fixes.
  • If the step is ambiguous, update WATCHDOG.md with a clearer next action and stop.

Escalator rules:

  • Escalate only after the same stall repeats or a replayer pass fails to advance.
  • Add an ESCALATE section to WATCHDOG.md with what was tried and the strongest next action.

Validator rules:

  • Inspect task folders for missing RESUME.md, CHECKLIST.md, or DOCS.md.
  • Backfill missing notes from the canonical template at {baseDir}/templates/TEMPLATE.md. Do not invent formats.
  • Refresh the task index so it lists all tasks with status and next action.
  • Treat a task as stale if heartbeat > 24h or next action is missing.

Smoke test checks:

  • Core files exist (TEMPLATE.md, TASK-INDEX.md, LOOP-STATE.md)
  • All 5 scheduled jobs exist and are enabled
  • At least one active task has a heartbeat and next action
  • Loop state is valid (armed or disarmed)

File layout

~/.openclaw/memory/
  TEMPLATE.md          # canonical template for new task folders
  TASK-INDEX.md        # quick-scan index of all tasks
  LOOP-STATE.md        # armed/disarmed state marker
  tasks/
    <task-name>/
      RESUME.md
      CHECKLIST.md
      DOCS.md
      WATCHDOG.md      # created by watchdog when stall detected

When to use

  • Task memory: Always. Every task should get notes automatically.
  • Keep-alive loop: For long tasks. /loop-start before the task, /loop-stop when done.
  • Quick tasks: Just let the task memory handle it. No need to arm the loop.

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