Memory load

Skill ztnkv/personal-operating-system/.claude/skills/memory-load

Portable personal-memory system for AI agents (Claude Code). Markdown + git. Skills for memory, lists, daily check-ins, blind-spot interviews — your agent gets a stable, evolving model of you.

Install

npx -y skills add ztnkv/personal-operating-system --skill memory-load

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

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What its author says it does

Copied from the file, not written here

Loads relevant entries from memory/ into the conversation context. Use at the start of any non-trivial conversation, and any time the topic might overlap with what is stored in memory (personal facts, habits, goals, relationships, work, health, hobbies, etc.). Hybrid strategy — always read memory/index.md and memory/tags.md as the map first, then pull full entry bodies by tag match and by semantic match on titles. No artificial cap on how many entries can be loaded.

SKILL.md

2.8 KB, 536 tokens by cl100k_base, as published. Nobody here has run it

memory-load

Pulls relevant memory entries into the conversation context.

When to invoke

At the start of a session or whenever a new initiative is opened — required.
Any time the conversation touches a topic that could plausibly be in memory (personal, habits, goals, relationships, work, health, hobbies, family, etc.).
When the user explicitly asks to recall — "what did I say earlier about X?"

Err on the side of invoking. A missed context is worse than a redundant read.

Algorithm

Step 1. Read the map

Always read:

memory/index.md — the catalog of all entries with titles and tags.
memory/tags.md — the tag dictionary (needed to interpret tags).

These files are small and cheap. Read them in full.

Step 2. Decide relevance

From the user's last message and the conversation context, extract:

Candidate tags — which existing entries in tags.md match the topic.
Semantic hooks — entry titles in index.md that are thematically close even when the tags themselves do not line up (the user may use different words).

Use both signals together — tags for precise hits, titles for cases where the wording diverges.

Step 3. Load the bodies

Read the full .md files of the entries that passed the filter.

Default filter: status: active only. Entries with status: deprecated are pulled in only when the user is explicitly asking about the past ("what did I used to think about X", "go back to the old idea about Y").

Step 4. Use in the response

Lean on the loaded knowledge implicitly. Do not recite entries verbatim unless the user asks.
When citing a specific fact, refer to it briefly ("you said earlier that …") without quoting the full formulation.
Respect confidence: low and medium are in-the-moment hypotheses, not doctrine. low entries should be revisited and confirmed at the next natural opportunity.
Respect type: constraint — a hard limit on recommendations; goal — a direction to nudge toward; belief — an opinion that can be discussed; preference — color the style and content of suggestions; fact — given; event — historical anchor.

Constraints

Do not write or modify memory files. This skill is read-only.
If something needs to be recorded — that is memory-retro's job.