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 verygoodplugins/mcp-automem --skill automemgit clone --depth 1 https://github.com/verygoodplugins/mcp-automemWrote 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/verygoodplugins/mcp-automem/automem)<a href="https://agentmods.dev/skills/verygoodplugins/mcp-automem/automem"><img src="https://agentmods.dev/badge/skills/verygoodplugins/mcp-automem/automem.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 19 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
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 | $0.00018 | $0.00333 |
| Opus 5 | $0.00009 | $0.00167 |
| Sonnet 5 | $0.00004 | $0.00067 |
| Haiku 4.5 | $0.00002 | $0.00033 |
Grade A, and why
automem 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.
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.
What it actually says
AutoMem
Use the native AutoMem tools exposed by the AutoMem plugin.
Natural language mappings
remember ...orstore this-> callautomem_store_memorywhat do you know about ...orrecall ...-> callautomem_recall_memoryupdate memory ...-> callautomem_update_memorydelete memory ...-> recall first when needed, then callautomem_delete_memorylink these memories ...-> callautomem_associate_memoriesis memory healthy?-> callautomem_check_health
Slash command behavior
Treat /automem remember ..., /automem recall ..., /automem update ..., and /automem delete ... as direct requests to use the matching AutoMem tool flow above.
Rules
- Recall first for prior decisions, preferences, ongoing projects, and debugging history.
- Store durable outcomes: decisions, bug fixes, patterns, preferences, and important context.
- Keep content compact:
Brief title. Context and details. Impact/outcome. - If deletion is ambiguous, recall candidates first and ask for confirmation with ids before deleting.
- Use
memory-corealongside AutoMem when file-backed workspace memory is helpful. It complements AutoMem; it is not a replacement.
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 · 34 lines · 18 tokens per session scan A 1316ebe6d34a
automem is a skill published in the GitHub repository verygoodplugins/mcp-automem (64 stars, last pushed 4d ago), licensed MIT. It adds 18 tokens to every session and 333 once invoked, about $0.0001 per session on Opus 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
omnigraph
Operate OmniGraph graphs and deployments. Use for .pg schemas, .gq queries, OmniGraph CLI commands, file:///s3:///az:// graph URIs, cluster.yaml, operator config, bearer-authenticated servers, graph-backed knowledge or memory, Blob values, embeddings, branches, commits, and change feeds. Apply especially before schema…
codebase-memory
Use the codebase knowledge graph for structural code queries. Triggers on: explore the codebase, understand the architecture, what functions exist, show me the structure, who calls this function, what does X call, trace the call chain, find callers of, show dependencies, impact analysis, dead code, unused functions…
context-recovery
Recovers project handoff context from local Codex, Claude Code, Gemini, CodeBuddy, and codexmate-derived sessions. Use when the user asks what happened in prior project/PR/branch/file/error work, needs a handoff brief, wants old decisions or validations recovered, or asks to summarize cross-session project activity…
refactor-memory
Use when about to refactor or refine Claude Code auto memory, the MEMORY.md index and its topic files, to delete stale or derivable memories, fix inconsistencies, promote standing decisions to CLAUDE.md or rules, and regroup the index. Not for CLAUDE.md or rules files themselves.
Wikimate Query
A read-only search and question-answering workflow for a personal Wikimate knowledge base, made from an Obsidian note vault and a Notion index. It checks that note files really exist before using them as evidence.
Wikimate Summarize
A note-summarizing workflow for Wikimate, a personal note system. It creates a one-line summary or, when needed, a separate atomic note containing the main idea.