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dalomeve

Memory Self-Heal

by Dalomeve · GitHub ↗ · v1.1.0
cross-platform ✓ Security Clean
679
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1
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6
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Install in OpenClaw
/install memory-self-heal
Description
General-purpose self-healing loop that learns from past failures, retries safely, and records reusable fixes.
Usage Guidance
This skill appears to do what it says, but it performs broad filesystem reads (memory/, tasks/, logs/, skills/*/SKILL.md) and appends entries to memory. Before enabling it: 1) Restrict scan roots to only the project-level memory/task directories you trust; avoid allowing it to read system-wide paths. 2) Ensure the agent enforces redaction rules (don’t include secrets/tokens in memory writebacks) and add explicit exclude patterns for known secret/config locations. 3) Limit the skill's write target (single memory file or dedicated folder) and review permissions so it cannot alter other skills or system files. 4) Test the skill in a sandboxed project to observe what it reads/writes. 5) If you need stronger guarantees, require user confirmation before any writeback or before scanning directories that might contain credentials. If you want a different assessment, provide the exact runtime root paths the agent will have access to and any platform-level sandboxing/config restrictions — that would raise confidence to high.
Capability Analysis
Type: OpenClaw Skill Name: memory-self-heal Version: 1.1.0 The skill bundle provides instructions for an AI agent to perform self-healing and diagnostic tasks. It instructs the agent to scan local directories like `memory/` and `tasks/` for error patterns using shell commands (`Get-ChildItem`/`rg` and `Select-String`). These operations are read-only and confined to expected diagnostic paths. Crucially, the `SKILL.md` includes explicit 'Safety Rules' instructing the agent to 'Never auto-run destructive operations without confirmation' and 'Never log secrets/tokens in memory files', which actively mitigate potential prompt injection risks and prevent malicious actions. There is no evidence of data exfiltration, malicious execution, persistence mechanisms, or obfuscation.
Capability Assessment
Purpose & Capability
Name/description match the instructions: scanning memory, tasks, logs and reusing prior fixes is expected for a self-heal skill. There are no unrelated env vars, binaries, or installs requested.
Instruction Scope
Instructions tell the agent to recursively scan project memory/, tasks/, runtime/channel logs, and skills/*/SKILL.md and to append entries to memory. This is coherent for the stated goal, but the scan is broad and will read many files (possibly containing tokens or secrets). The SKILL.md warns not to log secrets, but it does not prescribe redaction, least-privilege read scopes, or explicit exclusion patterns for sensitive paths.
Install Mechanism
Instruction-only skill with no install spec or code files — lowest-risk delivery mechanism. Nothing is downloaded or written by an installer.
Credentials
No environment variables, credentials, or config paths are requested. The skill does reference runtime logs and memory paths, which is appropriate for its purpose; it does not request unrelated secrets or cloud credentials.
Persistence & Privilege
The skill writes concise self-heal entries back into project memory (expected behavior). always:false and normal autonomous invocation are used. Because it reads and writes project memory and other skill docs, you should verify file permissions and that it cannot modify other skills' configurations.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install memory-self-heal
  3. After installation, invoke the skill by name or use /memory-self-heal
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.1.0
**General-purpose self-healing loop with improved resilience and evidence handling.** - Adds portable evidence scan order for improved flexibility (supports custom memory paths and multiple shells) - Expands failure classification to cover more error scenarios (syntax, auth, network, context, false done, etc.) - Refines 3-tier recovery policy: direct fix, safe fallback, and controlled escalation with user-minimal unblock input - Introduces strict safety and completion rules to ensure only validated recoveries are marked done - Enforces concise, structured memory logging for each self-heal cycle to aid future automation - Updates integration notes for wider compatibility and easier customization
v1.0.0
Initial release of memory-self-heal skill for autonomous issue recovery. - Automatically detects repeated friction patterns such as command errors, missing API keys, login walls, browser conflicts, and context exhaustion. - Searches memory for prior occurrences and applies documented fixes before escalating. - Structured retry and fallback policy escalates through up to three self-healing attempts, recording blockers and minimum unblock actions as needed. - Logs each recovery cycle and lesson learned to structured memory files for future improvement. - Integration with heartbeat enables automatic re-evaluation and retry of previously blocked tasks when conditions change. - Safety boundaries included to prevent unsafe retries and protect sensitive information.
Metadata
Slug memory-self-heal
Version 1.1.0
License
All-time Installs 6
Active Installs 6
Total Versions 2
Frequently Asked Questions

What is Memory Self-Heal?

General-purpose self-healing loop that learns from past failures, retries safely, and records reusable fixes. It is an AI Agent Skill for Claude Code / OpenClaw, with 679 downloads so far.

How do I install Memory Self-Heal?

Run "/install memory-self-heal" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Memory Self-Heal free?

Yes, Memory Self-Heal is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Memory Self-Heal support?

Memory Self-Heal is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Memory Self-Heal?

It is built and maintained by Dalomeve (@dalomeve); the current version is v1.1.0.

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