memoryguard-local-ops

A procedure for installing, configuring, repairing, diagnosing, and governing the local agent-memguard Python package on Windows. It also covers its optional desktop console and the setup of Codex connections or hooks.

In plain words
What is it for?
Use it to install or upgrade agent-memguard, verify its package and interpreter, repair local setup, investigate control-home issues, and manage approved memory operations on Windows.
Why use it?
It reduces mistakes when checking the correct Python interpreter, installing the package, or troubleshooting configuration and memory-policy problems. It keeps diagnosis focused on read-only checks before changes.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/irisxc4/memoryguard/memoryguard-local-ops
Any agent
npx skills add irisxc4/memoryguard --skill memoryguard-local-ops
Clone the repo
git clone --depth 1 https://github.com/irisxc4/memoryguard

Made for: Claude Code, Codex.

Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,025 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00051 $0.02025
Opus 5 $0.00026 $0.01012
Sonnet 5 $0.00010 $0.00405
Haiku 4.5 $0.00005 $0.00202

Measured 2d ago against content hash 0f058465caa4, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

memoryguard-local-ops scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/memoryguard/skills/memoryguard-local-ops/SKILL.md · 226 lines

How it starts

The opening of the file, as written. The whole thing — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MemoryGuard local operations

Use this skill for the repository's agent-memguard package (the current checkout declares version 0.7.8). Scope is local Windows installation, configuration, repair, diagnostics, and governed memory operations.

This is a skills-only plugin. It does not bundle agent-memguard, add a remote MCP server, or silently edit a user's host configuration. Run commands only when the user asked for the corresponding operation; use read-only checks first when diagnosing.

Windows install

  1. Check the interpreter and package manager:

    py -3 --version
    py -3 -m pip --version
    py -3 -c "import sys; print(sys.executable)"
    

    agent-memguard requires Python 3.10 or newer. If the py launcher is not available, use python consistently and verify that it resolves to the interpreter that will run the MCP process.

  2. Install or upgrade the PyPI package:

    py -3 -m pip install --upgrade agent-memguard
    

    The optional desktop console is a separate extra:

    py -3 -m pip install --upgrade "agent-memguard[gui]"
    

    For a source checkout, use a non-editable install (py -3 -m pip install .). Do not point a live Codex MCP process at src or use pip install -e as its runtime. The provider installer can select or build a content-keyed, non-editable runtime snapshot when it detects a local/editable install.

  3. Verify the exact interpreter and package:

    memoryguard --version
    py -3 -c "import importlib.metadata as m; print(m.version('agent-memguard'))"
    py -3 -m memoryguard.mcp_server --help
    memoryguard doctor
    

    If memoryguard resolves to another Python installation, use that interpreter's console-script path or repair PATH; do not assume that a successful pip command configured Codex.

Codex configuration

Preferred provider path

If the MemoryGuard MCP tools are already available, call:

memoryguard_provider_install(provider="codex")

Read the full file on GitHub · 226 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 226 lines · 51 tokens per session scan A 0f058465caa4

Subscribe to this mod's changes

memoryguard-local-ops is a skill published in the GitHub repository irisxc4/memoryguard (2 stars, last pushed 2d ago), licensed MIT. It adds 51 tokens to every session and 2,025 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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