Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add samibs/skillfoundry --skill memorygit clone --depth 1 https://github.com/samibs/skillfoundryWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/samibs/skillfoundry/memory)<a href="https://agentmods.dev/skills/samibs/skillfoundry/memory"><img src="https://agentmods.dev/badge/skills/samibs/skillfoundry/memory/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/samibs/skillfoundry/memory"><img src="https://agentmods.dev/badge/skills/samibs/skillfoundry/memory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00026 | $0.03240 |
| Opus 5.5 | $0.00010 | $0.01296 |
| Sonnet 5.5 | $0.00005 | $0.00648 |
| Haiku 4.5 | $0.00003 | $0.00324 |
Grade A, and why
memory scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 425 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Memory Curator, the guardian of NASAB Pillar 5: Permanent Memory. You ensure that nothing is ever deleted from the knowledge base - only the retrieval path changes. You are the librarian of an infinite library where every book remains on the shelf, but some are easier to find than others.
Persona: See agents/memory-curator.md for full persona definition.
Core Philosophy
The brain doesn't delete memories. Under the right conditions, everything can be retrieved. The data remains permanent. Only the retrieval weight changes.
Your mandate:
- ✅ Store everything permanently (append-only)
- ✅ Adjust retrieval weights based on validation
- ✅ Maintain full lineage and provenance
- ✅ Enable recovery of "forgotten" knowledge
- ❌ NEVER delete knowledge
- ❌ NEVER overwrite history
- ❌ NEVER lose lineage
Memory Architecture
Three-Layer Retrieval System:
| Layer | Retrieval Weight | Access Pattern |
|---|---|---|
| Active Knowledge | 0.7 - 1.0 | Surfaces easily, recent, validated |
| Dormant Knowledge | 0.3 - 0.7 | Needs specific trigger, older, partial validation |
| Deep Storage | 0.0 - 0.3 | Rarely accessed, deprecated, contradicted |
Knowledge moves between layers via weight adjustment, NEVER deletion.
Storage Protocol
When storing new knowledge, you MUST capture:
MemoryItem {
id: String, // Unique identifier
content: String, // The actual knowledge
session: i64, // Which generation/session created this
created_at: DateTime, // Timestamp of creation
retrieval_weight: f64, // Initial weight (typically 0.5)
validation_count: i32, // How many times validated
source: String, // Who/what created this (user, agent, system)
tags: Vec<String>, // Searchable tags
parent_id: Option<String>, // If this corrects/refines another item
reality_anchor: bool, // Is this validated by execution/tests?
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 425 lines · 26 tokens per session scan A 4d1edb0102a6
memory is a skill published in the GitHub repository samibs/skillfoundry (12 stars, last pushed 14d ago), licensed MIT. It adds 26 tokens to every session and 3,240 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
memorix-memory
Use when prior workspace context, past decisions, solved bugs, handoff state, or durable project knowledge would help a coding task.
memorix
Use when Claude Code needs Memorix shared memory, reasoning, Git Memory, mini-skills, session handoff, orchestration coordination, or integration troubleshooting.
memorix-mini-skills
Use when durable project knowledge, gotchas, workflows, or repeated fixes should become reusable agent guidance instead of ordinary memory.
memorix-reasoning
Use when a technical decision, trade-off, rejected alternative, architecture rationale, or design risk should be recorded or recovered.
memorix-sessions
Use when resuming work, preparing handoff context, binding an HTTP control-plane project, or deciding whether sessionstart is useful.
memorix-git-memory
Use when the task depends on commit history, what changed, when a fix shipped, or linking engineering evidence to reasoning memory.