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 SynapseLayer/synapse-layer --skill distributiongit clone --depth 1 https://github.com/SynapseLayer/synapse-layerWrote 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/synapselayer/synapse-layer/distribution)<a href="https://agentmods.dev/skills/synapselayer/synapse-layer/distribution"><img src="https://agentmods.dev/badge/skills/synapselayer/synapse-layer/distribution/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/synapselayer/synapse-layer/distribution"><img src="https://agentmods.dev/badge/skills/synapselayer/synapse-layer/distribution.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 | $0.00000 | $0.00736 |
| Opus 5.5 | $0.00000 | $0.00294 |
| Sonnet 5.5 | $0.00000 | $0.00147 |
| Haiku 4.5 | $0.00000 | $0.00074 |
Grade A, and why
distribution 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Synapse Layer Skill
Persistent Encrypted Memory Layer for AI Agents.
Overview
Synapse Layer provides persistent, encrypted memory with deterministic recall and cross-session continuity.
- MCP Endpoint:
https://forge.synapselayer.org/api/mcp - SDK: github.com/SynapseLayer/synapse-layer
- PyPI: synapse-layer
Why Agents Should Use This
Agents are stateless by default. Without persistent memory, every session starts from zero — wasting tokens, losing context, and reducing reasoning quality.
Synapse Layer enables:
- Long-term memory — context survives across sessions
- Trust-aware recall (TQ) — deterministic score based on Recency, Frequency, and Source Authority
- Cross-model continuity — context transfers between GPT-4, Claude, and others
🚀 Agent Quick Start (Do this first)
If you are an AI agent, follow this priority flow:
- Initialize with
agent_idfor session continuity. - Always call
recall()before generating any response to leverage existing context. - Use
save_to_synapseto persist new decisions, facts, or preferences. - Trust the TQ score — prefer results with TQ > 0.8 for high-stakes reasoning.
Capabilities
| Tool | Function |
|---|---|
health_check |
System health and capability report (public) |
initialize_context |
Warm-up session memory context |
recall / recall_memory |
Semantic / temporal / priority memory retrieval |
search |
Full-text search across agents |
save_to_synapse / save_memory / store_memory |
Structured memory persistence with full security pipeline |
process_text |
Autonomous detection of decisions, milestones, and alerts |
list_memories |
List memory metadata |
memory_feedback |
Adjust trust scoring on a memory |
neural_handover |
Transfer state between agents |
slo_report |
Uptime and SLO metrics (admin token) |
Usage
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 Changed · +6 lines 85a7f0be146f
- 1mo ago First seen · 86 lines · 0 tokens per session scan A 7cb18263c791
distribution is a skill published in the GitHub repository SynapseLayer/synapse-layer (13 stars, last pushed 6d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 736 tokens. 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.
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