ai-memory is a shared long-term memory system for coding agents that preserves project knowledge, unfinished work, failed approaches, and open questions across tools and machines. It is used by individual developers and teams to hand work between different coding agents and continue projects without repeating the context.
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 akitaonrails/ai-memory --skill ai-memory-durable-pagesgit clone --depth 1 https://github.com/akitaonrails/ai-memoryWrote 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/akitaonrails/ai-memory/ai-memory-durable-pages)<a href="https://agentmods.dev/skills/akitaonrails/ai-memory/ai-memory-durable-pages"><img src="https://agentmods.dev/badge/skills/akitaonrails/ai-memory/ai-memory-durable-pages/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/akitaonrails/ai-memory/ai-memory-durable-pages"><img src="https://agentmods.dev/badge/skills/akitaonrails/ai-memory/ai-memory-durable-pages.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, 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 Prompt Injection · line 5 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- medium Excessive Agency · line 69 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00062 | $0.01092 |
| Opus 5 | $0.00031 | $0.00546 |
| Sonnet 5 | $0.00012 | $0.00218 |
| Haiku 4.5 | $0.00006 | $0.00109 |
Grade A, and why
ai-memory-durable-pages 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 5d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ai-memory durable pages
Use this skill only for deliberate durable wiki mutations. Routine session capture is automatic, and permanent notes require an explicit user request.
Tools in this cluster
memory_write_pagewrites a durable wiki page for permanent project knowledge.memory_delete_pageremoves a durable wiki page by exact path.
Writing durable memory
Write a page only when the user explicitly asks to remember something permanently, save a note, add an annotation, or record project knowledge. Do not use durable pages for transient progress, normal status updates, or next-session context.
Put the page title as a # H1 on the first line of the body and omit the separate title argument. ai-memory derives the title from that H1. Keep the content concise and fact-like, with enough context that a future agent can apply it without rereading the whole session.
When the user explicitly wants a note to be temporary, pass expires_at as an
RFC3339 instant or a bare YYYY-MM-DD (the end of that day in UTC). After the
TTL, normal search, recent, and briefing reads hide the page; the next forget
sweep deletes it. A TTL outranks pinned, so do not combine them unless the user
has deliberately requested that behavior.
Project rules belong in instructions first
If the user asks to create a durable project rule such as always do X or never do Y, update the project's canonical agent instruction file when the repository says one exists. Use a durable page only when the user explicitly wants the rule in the wiki too, or when no canonical instruction file applies.
Deleting durable memory
Delete only by exact path. If the user gives a vague title or topic, first resolve it to the page path using read-only lookup. Preserve sibling projects unless the user explicitly names them.
Project scope
Choose scope from the MCP client's identity support:
- Session-aware MCP clients that forward the real lifecycle-hook session id on every request should use automatic current-project routing. Omit
workspace,project, andcwdfor the current repository; pass explicit scope only when the user names a different project. - Static MCP clients (including clients with lifecycle hooks but no bridge connecting that hook session id to MCP requests) must pass
workspaceandprojecttogether on every project-scoped call, including requests about this project, here, or our work. Read the exact names from the nearest.ai-memory.tomlwhen it declares both. If it does not, obtain the names from the operator or server configuration; never guess them from a directory name and never rely on the server's last active project.
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.
- 5d ago Changed · +5 lines 3a19ec1f0f62
- 13d ago First seen · 65 lines · 62 tokens per session scan A 80643e44309a
ai-memory-durable-pages is a skill published in the GitHub repository akitaonrails/ai-memory (6,555 stars, last pushed today), licensed MIT. It adds 62 tokens to every session and 1,092 once invoked, about $0.0003 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.
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