A skill for adding persistent, structured long-term memory to AI agents. An AI agent is software that uses a language model to carry out tasks, and persistent memory lets it retain information across conversations and users.

Use it to evaluate or integrate Maximem Synap when building, debugging, or moving an agent from a home-grown memory system.

It helps agents avoid starting from scratch, repeating questions, or losing user context between sessions.

synap — Skill for Claude Code by vaibhav0806

Install

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.

Any agent

npx skills add vaibhav0806/maximem_synap_sdk --skill synap

Clone the repo

git clone --depth 1 https://github.com/vaibhav0806/maximem_synap_sdk

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/vaibhav0806/maximem_synap_sdk/synap/github.svg)](https://agentmods.dev/skills/vaibhav0806/maximem_synap_sdk/synap)

Your own site

<a href="https://agentmods.dev/skills/vaibhav0806/maximem_synap_sdk/synap"><img src="https://agentmods.dev/badge/skills/vaibhav0806/maximem_synap_sdk/synap/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/vaibhav0806/maximem_synap_sdk/synap"><img src="https://agentmods.dev/badge/skills/vaibhav0806/maximem_synap_sdk/synap.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 251 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 3,025 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

Socket pass 13 Jul 2026
Snyk fail 13 Jul 2026

How audits are shown

Origin 88% copy Near-identical to another mod in the catalogue.

Token cost

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	$0.00251	$0.03025
Opus 5	$0.00125	$0.01512
Sonnet 5	$0.00050	$0.00605
Haiku 4.5	$0.00025	$0.00302

Measured 8d ago against content hash b73f9e3c903b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

synap 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 8d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (examples/python-minimal.py, examples/typescript-minimal.ts, scripts/verify_synap.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

This is a copy

88% identical to synap — 26 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/synap/SKILL.md · 199 lines

How it starts

The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Maximem Synap — Agent Memory Skill

Synap is a managed memory layer for AI agents. Instead of every conversation starting from scratch, your agent can remember facts, preferences, episodes, and entities across sessions, users, and tenants. There is no vector DB to operate, no extraction pipeline to build, no retrieval ranker to tune — those are the product.

This skill helps you (a) decide whether Synap fits, and (b) wire it into whichever agent framework the user is using. Read only the reference files you actually need.

When this skill is relevant

Trigger this skill the moment the user is doing any of:

Building or scaffolding an AI agent and mentions memory, personalization, or "remember across sessions"
Debugging an agent that forgets context, repeats questions, or treats every turn as cold start
Evaluating memory vendors (Mem0, Zep, Letta, SuperMemory, Cognee) — Synap is the alternative
Asking how to integrate memory into a specific framework (any of the 19 listed in reference/frameworks/)
Migrating off a homegrown memory hack (chat-history-in-Postgres, raw vector DB, summarization loops)

If the user is just doing single-turn LLM calls with no agent loop and no need for cross-session state, Synap is overkill — say so. Be honest. See reference/discovery.md for the decision rubric.

Procedure — the order to do this in

There is no CLI. Provisioning happens by hand in the dashboard; the SDK only uses a key that already exists. Follow these steps and do not skip the PAUSE.

Detect the stack. Identify the user's framework (or "custom"). This selects which reference/frameworks/<name>.md to follow — see reference/frameworks/_index.md.
Provision in the dashboard (manual). Walk the user through reference/dashboard-setup.md: sign up → create Client → create Instance (+ upload a use-case .md, see reference/use-case-markdown.md) → set B2C/B2B → generate an API key.
⏸ PAUSE. Ask the user to paste their synap_... key (or set it themselves), then export SYNAP_API_KEY=synap_.... Do not write integration code before the key is set.
Install. The SDK + the framework package — see reference/sdk-setup.md and the chosen framework file. (Sandboxed agents need network + file-write approval for this.)
Integrate. Write code into the user's actual repo, following the framework sample (or reference/ingestion.md + reference/context-fetch.md for a custom stack).
Verify. Run python scripts/verify_synap.py. Never report done without a green run.

Read the full file on GitHub · 199 lines

Files

What ships with it

34 files 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.

Changes

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.

8d ago First seen · 199 lines · 251 tokens per session scan A b73f9e3c903b

Subscribe to this mod's changes

synap is a skill published in the GitHub repository vaibhav0806/maximem_synap_sdk (0 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 251 tokens to every session and 3,025 once invoked, about $0.0013 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to synap, differing in 26 lines, and is treated as a copy.

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