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Install in OpenClaw
/install memory-governor
Description
Memory governance kernel for AI agents that complements OpenClaw Dreaming with explicit correction staging, target-class routing, adapter boundaries, and saf...
Usage Guidance
This skill is internally consistent with its documentation: it provides rules, templates, and small helper scripts to check and bootstrap host-level memory adapter files. Before running anything, review the included scripts (bootstrap-generic-host.sh, check-memory-host.py, validate-memory-frontmatter.py, review-learning-candidates.py) so you understand what files they will read or create. The bootstrap script will create example files in a target directory (it documents that it won't overwrite existing files). Avoid copying secrets into the memory files it manages (references/exclusions.md explicitly forbids storing tokens/passwords). If you do not want the agent or scripts to access certain workspace files, run them in a controlled directory or inspect/limit file permissions. If you need stricter runtime guarantees, run the scripts manually rather than allowing autonomous agent invocation. Overall, the package appears to do what it claims; proceed if that governance model fits your host and you are comfortable with the scripts' filesystem access.
Capability Analysis
Type: OpenClaw Skill
Name: memory-governor
Version: 0.2.9
The 'memory-governor' bundle is a governance framework designed to help AI agents categorize and manage their memory layers (e.g., long-term, daily, and working buffers). The bundle contains Python validation scripts (check-memory-host.py, validate-memory-frontmatter.py) and a shell bootstrap script that operate strictly on local files to ensure workspace configuration matches the defined memory contract. Analysis of the SKILL.md and reference documentation shows no evidence of malicious prompt injection; rather, the instructions explicitly direct the agent to exclude secrets and sensitive data from memory. No network activity, data exfiltration, or unauthorized persistence mechanisms were detected.
Capability Assessment
Purpose & Capability
Name/description (a memory-governor governance kernel) align with the shipped files: policy docs, adapter/manifest guidance, fallback templates, and helper scripts for host checking, frontmatter validation, candidate review, and a lightweight bootstrap. There are no unrelated environment variables, binaries, or credentials requested.
Instruction Scope
SKILL.md and the references concentrate on classification, routing, promotion and exclusion rules. The included scripts read host manifests and structured memory files and the bootstrap script creates example files. This is coherent with the stated purpose, but note that running the scripts will read and (in the case of bootstrap) write files in a host directory — exactly as documented.
Install Mechanism
No install spec; the skill is instruction-only and ships helper scripts. No downloads, package managers, or external installers are referenced in the metadata. Risk from installation is low since nothing will be pulled from arbitrary URLs.
Credentials
The skill requires no environment variables, credentials, or config paths. The job it performs (governing memory artifacts) legitimately needs access to host files and manifests, which is consistent with the provided scripts and guidance.
Persistence & Privilege
Flags are default (always: false). The package does include a bootstrap script that can create host files when run, but installation metadata does not request permanent platform privileges or automatic modification of unrelated skills; the docs explicitly state integration should be explicit and not silent.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install memory-governor - After installation, invoke the skill by name or use
/memory-governor - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.2.9
- Added guidance for OpenClaw Dreaming integration to clarify boundaries and avoid duplicate promotion flows.
- Introduced explicit mention of correction staging, adapter separation, and hardening rules in the skill description.
- Expanded reference documentation, including a new dreaming-integration guide.
- Improved rule descriptions around target-class routing and memory promotion.
- Updated references and docs to refine installation, adapters, host profiles, and integration practices.
v0.2.8
- Introduced the learning_candidates target class as a staging layer for corrections and emerging lessons.
- Added references and documentation for candidate review and correction pipelines.
- Updated routing, promotion, and integration guides to reflect the candidate staging and review flow.
- Provided example assets and scripts for handling learning candidates in host environments.
- Expanded README and SKILL.md to clarify the candidate-to-rule process and new classification logic.
v0.2.7
**Changelog for memory-governor 0.2.7**
- Major cleanup: removed 57 files, including all dev, test, and historical release materials.
- Documentation now streamlined: SKILL.md and README.md are significantly simplified and clarified.
- English-only documentation: Chinese-language documentation and bilingual explanations have been removed from core docs.
- Reference section pointers remain, but "first read" flow and explanations are more concise.
- All development, evaluation, plan, and scenario files are now removed for a leaner public distribution.
v0.2.6-beta
Organizes the repository into runtime, dev, releases, and tests; adds maintainer-facing tests and clearer package boundaries.
v0.2.4-beta
Fixes Python 3.9/3.10 compatibility for packaged scripts via tomli fallback and documents the requirement explicitly.
v0.2.3-beta
Adds fallback-aware manifest validation, a migration guide, and clearer reusable_lessons adapter modes.
v0.2.2-beta
Adds bilingual public-facing README and SKILL intro for English and Chinese readers.
v0.2.1-beta
Adds an English public-facing summary, bilingual ClawHub metadata, and clearer readiness wording for external users.
v0.2.0-beta
First public beta of a memory governance core for AI agents. Adds target classes, adapters/fallbacks, host manifests, host checker, and generic/OpenClaw integration guidance.
Metadata
Frequently Asked Questions
What is Memory Governor?
Memory governance kernel for AI agents that complements OpenClaw Dreaming with explicit correction staging, target-class routing, adapter boundaries, and saf... It is an AI Agent Skill for Claude Code / OpenClaw, with 177 downloads so far.
How do I install Memory Governor?
Run "/install memory-governor" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Memory Governor free?
Yes, Memory Governor is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Memory Governor support?
Memory Governor is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Memory Governor?
It is built and maintained by SakenW (@sakenw); the current version is v0.2.9.
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