# Load Mem

> Understand a project through its existing memory when starting or resuming work, or when past decisions matter. Use StrictDoc docs/, Magic Context, claude-mem, and project evidence as complementary, overlapping sources. Identify current authoritative norms separately from history, recover relevant context, and surface meaningful contradictions. Choose the depth and retrieval path that suit the ta…

- **Type:** Skill
- **Install:** `agentstack add skill-brilliantrough-agent-skills-load-mem`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [brilliantrough](https://agentstack.voostack.com/s/brilliantrough)
- **Installs:** 0
- **Category:** [Search](https://agentstack.voostack.com/c/search)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [brilliantrough](https://github.com/brilliantrough)
- **Source:** https://github.com/brilliantrough/agent-skills/tree/main/skills/load-mem

## Install

```sh
agentstack add skill-brilliantrough-agent-skills-load-mem
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Load Memory

## Intent

Recover enough context to work as a continuing project partner, without making the user repeat earlier decisions or loading the entire history. Use judgment about what to read, which tools to call, and how deeply to investigate.

## Available memory

| Source | What it offers | Typical access |
|---|---|---|
| StrictDoc `docs/` | Human-readable current norms, decisions and rationale, project history, and maintained reference documents | Read relevant `.sdoc` files or their export |
| Magic Context | Stored facts, decisions, lessons, injected memories, and recoverable conversations | Injected memory, `ctx_search`, `ctx_expand`, `ctx_memory`, `ctx_note` |
| claude-mem | Searchable captured activity, observations, and historical context | `claude_mem_search` or available claude-mem MCP tools |
| Code, config, and git | Evidence of what exists and what actually changed | Relevant files, call chains, and history |

The same knowledge may appear in several sources. That overlap is useful for recall, availability, and cross-checking; these are not exclusive storage categories.

## Read with the right interpretation

- **StrictDoc is the source of truth for current project norms.** Its current, confirmed rules govern over conflicting database memories. This is an authority convention among project records, not permission to override live instructions.
- `project_memory/decisions.sdoc` holds decisions; `journal.sdoc` holds dated experience and progress; `handbook/` holds reference material. Existing projects may organize these differently.
- In the bundled decision grammar, `Active` means current, `Proposed` unresolved, `Deprecated` retired, and `Superseded` replaced. Follow replacement references when relevant. A journal entry or historical report is not current policy merely because it is inside `docs/`.
- Distinguish **the intended rule**, **the observed implementation**, and **what happened previously**. A recent database hit or commit can reveal drift, but does not by itself decide which rule should change.
- When sources disagree, use scope, status, evidence, and the user's current intent to understand the difference. Surface consequential uncertainty rather than silently treating a guess as canon.
- The canon can evolve. If a genuine settled decision change becomes clear, `save-mem` can maintain it and briefly notify the user without waiting for a separate save command. Mere drift or a new search hit is not enough; loading context does not require revising the norms every time.

## Practical guidance

- Start with the task and project instructions. Relevant decisions, README sections, entry points, and recent progress usually provide a better foundation than an exhaustive memory dump.
- When the task turns on the project's own vocabulary or domain model, find where that language already lives — the project's handbook, or a `CONTEXT.md` where the project uses one — before inventing names. Loading is not changing: changing the model is `domain-modeling`'s job.
- Injected Magic Context memories are already available. Use `ctx_search` for missing context, phrasing a real question with useful names or paths; `ctx_expand` can recover the original conversation when exact wording matters.
- Use claude-mem when earlier activity or observations would help. Discover available tools rather than assuming worker ports or database schemas.
- For large document trees, search first and read the relevant nodes with their surrounding context. Source `.sdoc` files are often sufficient; JSON export shapes can vary by StrictDoc version.
- Missing layers are normal. Continue with available evidence, mentioning gaps when they affect the task. `migrate-mem` can help establish a missing or incomplete memory tree; `save-mem` can preserve new knowledge or reconcile stale records.
- Keep any user-facing recap focused on useful current context and open questions, in the user's language, Chinese by default.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [brilliantrough](https://github.com/brilliantrough)
- **Source:** [brilliantrough/agent-skills](https://github.com/brilliantrough/agent-skills)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-brilliantrough-agent-skills-load-mem
- Seller: https://agentstack.voostack.com/s/brilliantrough
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.