
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 Each fact carries id, category (relationship, milestone, status, preference), timestamp, source, active or superseded status, related entities, last_accessed, and access_count fields.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 Superseded facts link to replacement records via superseded_by for clean fact lineage.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)
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| Installs | 1.2k |
|---|---|
| repo stars | ★ 75.6k |
| Security audit | 3 / 3 scanners passed |
| Last updated | August 5, 2026 |
| Repository | paperclipai/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
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.mdPARA 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.mdfrom active facts. - Never delete facts. Supersede instead (
status: superseded, addsuperseded_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.mdor 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 similarityIndex 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.
Schemas and Memory Decay
Atomic Fact Schema (items.yaml)
- id: entity-001
fact: "The actual fact"
category: relationship | milestone | status | preference
timestamp: "YYYY-MM-DD"
source: "YYYY-MM-DD"
status: active # active | superseded
superseded_by: null # e.g. entity-002
related_entities:
- companies/acme
- people/jeff
last_accessed: "YYYY-MM-DD"
access_count: 0Memory Decay
Facts decay in retrieval priority over time so stale info does not crowd out recent context.
Access tracking: When a fact is used in conversation, bump access_count and set last_accessed to today. During heartbeat extraction, scan the session for referenced entity facts and update their access metadata.
Recency tiers (for summary.md rewriting):
- Hot (accessed in last 7 days) -- include prominently in summary.md.
- Warm (8-30 days ago) -- include at lower priority.
- Cold (30+ days or never accessed) -- omit from summary.md. Still in items.yaml, retrievable on demand.
- High
access_countresists decay -- frequently used facts stay warm longer.
Weekly synthesis: Sort by recency tier, then by access_count within tier. Cold facts drop out of the summary but remain in items.yaml. Accessing a cold fact reheats it.
No deletion. Decay only affects retrieval priority via summary.md curation. The full record always lives in items.yaml.
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.