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Para Memory Files

  • 1.2k installs
  • 75.6k repo stars
  • Updated August 5, 2026
  • paperclipai/paperclip

This is a copy of para-memory-files by getpaperclipai - installs and ranking accrue to the original listing.

PARA Memory Files is an agent skill that maintains long-term factual memory across extended conversations using atomic fact records, supersession chains, and access-based memory decay in items.yaml.

About

PARA Memory Files is a Paperclip skill from paperclipai/paperclip that structures agent long-term memory as atomic facts in items.yaml. Each fact carries id, category (relationship, milestone, status, preference), timestamp, source, active or superseded status, related entities, last_accessed, and access_count fields. Memory decay lowers retrieval priority for stale facts so older entries do not crowd recent context. When a fact is referenced in conversation, the skill bumps access_count and updates last_accessed during heartbeat extraction scans. Developers reach for PARA Memory Files when building agents that must remember entities, preferences, and milestones across weeks of sessions without bloating the context window. Superseded facts link to replacement records via superseded_by for clean fact lineage.

  • Implements Atomic Fact Schema with category, timestamp, source, status, related_entities and access metadata
  • Applies Memory Decay using Hot/Warm/Cold recency tiers based on last_accessed and access_count
  • Weekly synthesis that curates summary.md while preserving every fact in items.yaml
  • Access tracking automatically bumps access_count and updates last_accessed on use
  • No deletion policy — cold facts remain retrievable on demand

Para Memory Files by the numbers

  • 1,175 all-time installs (skills.sh)
  • +83 installs in the week ending Aug 5, 2026 (Skillselion tracking)
  • Security screen: LOW risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/paperclipai/paperclip --skill para-memory-files

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Listed on Skillselion
Installs1.2k
repo stars75.6k
Security audit3 / 3 scanners passed
Last updatedAugust 5, 2026
Repositorypaperclipai/paperclip

How do agents persist facts across long conversations?

Maintain long-term factual memory across extended agent conversations without losing important context over time.

Who is it for?

Agent developers implementing PARA-style persistent memory with supersession and decay instead of dumping full chat logs into context.

Skip if: Teams needing vector database semantic search only, with no structured YAML fact files or supersession lifecycle.

When should I use this skill?

The user asks to persist agent memory, define atomic fact schemas, or implement memory decay across multi-session conversations.

What you get

items.yaml atomic fact records with timestamps, supersession chains, access tracking, and decay-weighted retrieval priority.

  • items.yaml fact records
  • Supersession chains
  • Access-tracked memory index

Files

SKILL.mdMarkdownGitHub ↗

PARA Memory Files

Persistent, file-based memory organized by Tiago Forte's PARA method. Three layers: a knowledge graph, daily notes, and tacit knowledge. All paths are relative to $AGENT_HOME.

Three Memory Layers

Layer 1: Knowledge Graph ($AGENT_HOME/life/ -- PARA)

Entity-based storage. Each entity gets a folder with two tiers:

1. summary.md -- quick context, load first. 2. items.yaml -- atomic facts, load on demand.

$AGENT_HOME/life/
  projects/          # Active work with clear goals/deadlines
    <name>/
      summary.md
      items.yaml
  areas/             # Ongoing responsibilities, no end date
    people/<name>/
    companies/<name>/
  resources/         # Reference material, topics of interest
    <topic>/
  archives/          # Inactive items from the other three
  index.md

PARA rules:

  • Projects -- active work with a goal or deadline. Move to archives when complete.
  • Areas -- ongoing (people, companies, responsibilities). No end date.
  • Resources -- reference material, topics of interest.
  • Archives -- inactive items from any category.

Fact rules:

  • Save durable facts immediately to items.yaml.
  • Weekly: rewrite summary.md from active facts.
  • Never delete facts. Supersede instead (status: superseded, add superseded_by).
  • When an entity goes inactive, move its folder to $AGENT_HOME/life/archives/.

When to create an entity:

  • Mentioned 3+ times, OR
  • Direct relationship to the user (family, coworker, partner, client), OR
  • Significant project or company in the user's life.
  • Otherwise, note it in daily notes.

For the atomic fact YAML schema and memory decay rules, see references/schemas.md.

Layer 2: Daily Notes ($AGENT_HOME/memory/YYYY-MM-DD.md)

Raw timeline of events -- the "when" layer.

  • Write continuously during conversations.
  • Extract durable facts to Layer 1 during heartbeats.

Layer 3: Tacit Knowledge ($AGENT_HOME/MEMORY.md)

How the user operates -- patterns, preferences, lessons learned.

  • Not facts about the world; facts about the user.
  • Update whenever you learn new operating patterns.

Write It Down -- No Mental Notes

Memory does not survive session restarts. Files do.

  • Want to remember something -> WRITE IT TO A FILE.
  • "Remember this" -> update $AGENT_HOME/memory/YYYY-MM-DD.md or the relevant entity file.
  • Learn a lesson -> update AGENTS.md, TOOLS.md, or the relevant skill file.
  • Make a mistake -> document it so future-you does not repeat it.
  • On-disk text files are always better than holding it in temporary context.

Memory Recall -- Use qmd

Use qmd rather than grepping files:

qmd query "what happened at Christmas"   # Semantic search with reranking
qmd search "specific phrase"              # BM25 keyword search
qmd vsearch "conceptual question"         # Pure vector similarity

Index your personal folder: qmd index $AGENT_HOME

Vectors + BM25 + reranking finds things even when the wording differs.

Planning

Keep plans in timestamped files in plans/ at the project root (outside personal memory so other agents can access them). Use qmd to search plans. Plans go stale -- if a newer plan exists, do not confuse yourself with an older version. If you notice staleness, update the file to note what it is supersededBy.

Related skills

How it compares

Choose PARA Memory Files for structured YAML fact lifecycles; prefer vector memory skills when semantic similarity search is the primary retrieval model.

FAQ

What fields does PARA Memory Files store per fact?

PARA Memory Files uses an atomic fact schema in items.yaml with id, fact text, category (relationship, milestone, status, preference), timestamp, source, status (active or superseded), superseded_by, related_entities, last_accessed, and access_count.

How does PARA Memory Files prevent stale context?

PARA Memory Files applies memory decay so facts lose retrieval priority over time. Referenced facts bump access_count and last_accessed during heartbeat extraction, keeping recently used information ahead of stale entries.

Is Para Memory Files safe to install?

skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

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