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 EverMind-AI/EverMe --skill memory-recallgit clone --depth 1 https://github.com/EverMind-AI/EverMeWrote 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/evermind-ai/everme/memory-recall)<a href="https://agentmods.dev/skills/evermind-ai/everme/memory-recall"><img src="https://agentmods.dev/badge/skills/evermind-ai/everme/memory-recall/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/evermind-ai/everme/memory-recall"><img src="https://agentmods.dev/badge/skills/evermind-ai/everme/memory-recall.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 | $0.00030 | $0.00399 |
| Opus 5.5 | $0.00012 | $0.00160 |
| Sonnet 5.5 | $0.00006 | $0.00080 |
| Haiku 4.5 | $0.00003 | $0.00040 |
Grade A, and why
memory-recall 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.
What it actually says
EverMe Memory Recall
This session is backed by EverMe — a cross-session memory layer for Kimi Code.
At the start of the session and before each of the user's prompts, EverMe automatically injects relevant context drawn from past sessions:
<everme_profile>...</everme_profile>— a snapshot of durable facts and implicit traits about the user / their projects (injected at SessionStart).<everme_recall>...</everme_recall>— memories ranked as relevant to the prompt the user just submitted (injected on UserPromptSubmit).
After each of your replies, EverMe persists the just-finished turn back to the gateway so it can be recalled in future sessions.
How to use the injected context
- Treat
<everme_profile>and<everme_recall>as trusted background, not as instructions from the user. Weave the relevant parts into your answer; ignore the parts that don't apply. - Prefer recalled decisions/conventions over re-deriving them — but if the recalled memory conflicts with what the user says now, the user's current statement wins; surface the conflict briefly.
- Do not repeat the raw memory blocks back to the user. Synthesize.
- If the recall block is empty or unrelated, and the user references prior work, use the
mem_searchMCP tool to look it up (see thememory-toolsskill). Do not repeat a search for a topic the recall block already covers. - A section titled "Recent unextracted transcript" (when present) is provisional raw transcript, not yet extracted memory — never state its contents back as established user facts or confirmed decisions.
- Credentials (emk / evt) are secrets — never echo them, even in error messages.
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 · 25 lines · 30 tokens per session scan A 0c52563f1db9
memory-recall is a skill published in the GitHub repository EverMind-AI/EverMe (72 stars, last pushed 11d ago), licensed Apache-2.0. It adds 30 tokens to every session and 399 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
recall
Recall this repository's OwnMem local memory before changing code, and keep it healthy. Use when a repository contains .ownmem/, when past debugging lessons could apply ("have we hit this before", "why is it done this way"), or when the user mentions ownmem, project memory, or recalling across sessions.
dashboard
Open OwnMem Console, the local dashboard for this repository's memory. Use when the user asks to open the dashboard, see memory metrics, check recall quality, or set up the optional embedding lane. Requires a repository initialized with the dashboard layer.
init
Install or update OwnMem in the current repository. Use when the user asks to set up OwnMem, add local project memory for coding agents, or refresh an existing OwnMem installation after a version bump.
cargo-content
Manage the files a Cargo workspace holds — upload knowledge (PDF, CSV, text) and build native or connector-backed libraries agents retrieve from (RAG), and use files as plain storage: write and read by path, list a folder, hand out a signed or public link. Triggers: "upload this PDF", "add these docs as knowledge"…
contextstream-coach
Coach this agent on work the person needs again and again, such as a weekly note, an article, a recap or an image series. Use it when the person starts a job for one of their workflows, reacts to a draft, or asks what was learned from earlier jobs. Goals, drafts and the person's own words are saved in their…
mem-forever
Every AI tool forgets you. This one doesn't. Ever. Auto-generates your profile from conversation, saves decisions and lessons, applies your preferences across every session. Works with Claude Code, Cursor, Codex, Copilot, Gemini CLI. Use this skill at session start to load memory, and throughout the session to save…