Skills memory-management

📦

memory-management

Name: memory-management
Author: aaron-he-zhu

v19.0.0 Content revision r2 Safe ⚙️ External commands📁 Filesystem access🌐 Network access

Organize Project Memory Safely

Project context becomes difficult to find when notes are scattered or stale. This skill organizes authorized working memory while preserving registry ownership and privacy boundaries.

Supports: Claude Codex Code(CC)

🥉 78 Bronze

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request

Review the Skillstore skill "memory-management" from https://skillstore.io/skills/aaron-he-zhu-memory-management.md and its manifest at https://skillstore.io/api/skills/aaron-he-zhu-memory-management/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/aaron-he-zhu-memory-management.md Signed manifest GET /api/skills/aaron-he-zhu-memory-management/manifest Signed lockfile GET /api/skills/aaron-he-zhu-memory-management/lockfile

Test it

Using "memory-management". Review project memory for stale context.

Expected outcome:

HOT: 4 active priorities with source pointers.
WARM: 2 notes are older than 90 days and need review.
No writes made.

Using "memory-management". Prepare a consolidation plan for duplicate notes.

Expected outcome:

Two non-canonical notes cover the same observation window.
Keep the newer note as primary and retain the older note with a supersession reference.
Registry-owned facts remain unchanged.

Security Audit

Safe

v9 • 7/27/2026 Open versioned report

Three documented local Python commands are confirmed as external-command actions for initialization, consent lookup, and artifact validation. The remaining 34 detections are false positives from Markdown formatting, fixed documentation links, metadata URLs, and a redirected git error stream. No prompt injection, data exfiltration intent, or malicious behavior was found in the reviewed content.

Files scanned

537

Lines analyzed

Review items

False positives ignored

Capability review items (3)

These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.

Medium

SKILL.md:68

Ruby/shell backtick execution

2. Read [`runtime-invocation.md`](../../references/runtime-invocation.md), resolve `AARON_SKILLS_ROO

The installation instructions execute git and a local Python registry script. Although intended for local initialization, execution changes local registry directories and requires user authorization and script integrity verification.

Medium

SKILL.md:74-75

Ruby/shell backtick execution

1. Check live consent with `python3 "$AARON_SKILLS_ROOT/scripts/registry-events.py" is-suppressed <a

The query procedure executes a local Python registry script using an aggregate identifier. It is an external command with privacy-sensitive lookup behavior, even though the procedure limits it to consent checks.

Medium

SKILL.md:108

Ruby/shell backtick execution

Auditor outputs are written only after explicit authorization and must pass `python3 "$AARON_SKILLS_

The audit procedure executes a local validation script on an artifact path. This is a genuine external-command action and relies on the referenced script and runtime-root preflight.

Risk Factors

Audited by: claude View Audit History →

Share & cite this report

Share the versioned assessment report, neutral badge, embed card, and citations. Skillstore reports evidence without deciding whether this Skill is safe.

Open versioned report

Copy report link

https://skillstore.io/skills/aaron-he-zhu-memory-management/audits/9?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Markdown badge

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Academic citations (APA · BibTeX · CFF)

APA citation

aaron-he-zhu. (2026). memory-management security audit report (audit version 9) [Author version 19.0.0]. Skillstore. https://skillstore.io/skills/aaron-he-zhu-memory-management/audits/9

BibTeX citation

@techreport{aaron-he-zhu-aaron-he-zhu-memory-management-2026,
  author = {aaron-he-zhu},
  title = {memory-management security audit report (audit version 9)},
  institution = {Skillstore},
  year = {2026},
  number = {9},
  url = {https://skillstore.io/skills/aaron-he-zhu-memory-management/audits/9},
  note = {Author version 19.0.0}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "memory-management security audit report (audit version 9)"
version: "19.0.0"
type: report
authors:
  - name: "aaron-he-zhu"
date-released: "2026-07-27"
url: "https://skillstore.io/skills/aaron-he-zhu-memory-management/audits/9"
identifiers:
  - type: other
    value: "skillstore:aaron-he-zhu-memory-management:audit:9"
    description: "Skillstore immutable audit report identifier"

Compare variants

2 installable variants

Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.

Why this variant is first

Stronger evidence confidence

Author / source Skillstore Score Evidence Confidence Skillstore usage Updated

DojoCodingLabs Recommended

dojocodinglabs-memory-management

Skillstore Score 78

Evidence Confidence High

Skillstore usage 13

Updated

2026-09-09

aaron-he-zhu Current

aaron-he-zhu-memory-management

Skillstore Score 78

Evidence Confidence Medium

Skillstore usage 9

Updated

2026-09-09

Skillstore Score

Why this score Evidence Confidence: Medium

Architecture

100

Maintainability

Content

Community

Spec Compliance

What You Can Build

Start a new project memory space

Initialize private memory templates and define the first priorities without storing sensitive production data.

Prepare a cross-session handoff

Refresh a compact checkpoint with pending work, source offsets, and the next approved action.

Review an erasure request

Plan a scoped privacy purge, identify affected working notes, and report limitations before any authorized deletion.

Try These Prompts

Initialize memory

Initialize private project memory from the templates. Show the proposed paths and ask for approval before writing.

Review current context

Review our HOT and WARM memory. List current priorities, stale notes, and the source record for each conclusion.

Consolidate duplicates

Find duplicate non-canonical notes for this campaign. Propose a consolidation plan that preserves conflicts and source references.

Plan a privacy purge

Create a dry-run plan to erase the pseudonymous subject ID Subject-A1B2 from authorized working memory. Show scope and request confirmation before changes.

Best Practices

Ask for explicit approval before the first persistent write.
Store source references and observation dates with every durable note.
Treat HOT memory as an index and verify important facts in live registry records.