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/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/verygoodplugins/mcp-automem/automem"><img src="https://agentmods.dev/badge/skills/verygoodplugins/mcp-automem/automem.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00340 |
| Opus 5.5 | $0.00007 | $0.00136 |
| Sonnet 5.5 | $0.00004 | $0.00068 |
| Haiku 4.5 | $0.00002 | $0.00034 |
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 4d 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.
- 4d ago Changed 923eeec6d5bf
- 5d ago Changed 6e915aa06cf8
- 1mo ago First seen · 34 lines · 18 tokens per session scan A 1316ebe6d34a
automem is a skill published in the GitHub repository verygoodplugins/mcp-automem (66 stars, last pushed 2d ago), licensed MIT. It adds 18 tokens to every session and 340 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
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…
ensemble-sessionlog
Save a structured session transcript to SessionLogs with key decisions, commands, and resolutions (Codex skill for /ensemble:sessionlog).
context-review
Phase 8.5 grep checks C1-C3. Runs the three mechanical grep checks of the context review in a single invocation - C1 credential patterns, C2 unresolved placeholders, C3 field name staleness. Returns pass/fail per check with matched lines. The orchestrator handles C4-C12 (judgment-required checks) in the main session…
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.
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.