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 agentmods add skills/plmbr/nui/remembernpx skills add plmbr/nui --skill remembergit clone --depth 1 https://github.com/plmbr/nuiWhat 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 | $0.00020 | $0.00503 |
| Opus 5 | $0.00010 | $0.00251 |
| Sonnet 5 | $0.00004 | $0.00101 |
| Haiku 4.5 | $0.00002 | $0.00050 |
Grade A, and why
remember 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 2d 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Remember
Use this skill when the user invokes /remember or explicitly asks you to remember something (e.g. "remember this", "save to memory").
Do not save to memory proactively in manual mode — wait for an explicit user request.
Memory locations
- User memory (
~/.nui/memory/user.md) — preferences and facts that apply across all agents (timezone, coding style, default branch, communication preferences). - Agent memory (
~/.nui/memory/agents/<agent-id>.md) — facts specific to this agent's role (review checklist, project conventions, choices made in this workflow).
Scope rules
Default to agent scope. When the user asks to remember something — including a choice, decision, or preference for the current task — save to agent memory unless they clearly mean all agents.
Use user scope only when the user explicitly asks for cross-agent or personal memory, e.g.:
- "always", "for all agents", "everywhere"
- "remember this about me" / personal preference that should follow them across agents
Do not move agent-specific choices into user memory just because they sound like a preference.
Saving memory
API harness (nui-agent MCP)
Call update_memory on the nui-agent MCP server:
scope:"user"or"agent"content: concise markdown (bullet points or short paragraphs)mode:"append"to add to existing memory,"replace"to overwrite the whole file
CLI harness (Write/Edit tools)
Write directly to the canonical path:
- User:
~/.nui/memory/user.md - Agent:
~/.nui/memory/agents/<agent-id>.md
When appending, read the existing file first and preserve prior content.
Quality bar
- Store durable facts, not transient task state or conversation summaries.
- Keep entries concise; prefer bullets over long prose.
- Do not store secrets, API keys, or credentials.
- If memory would exceed roughly 8KB, consolidate or prune older low-value entries before appending.
- When unsure, default to agent scope; ask only if it is genuinely ambiguous whether the fact applies to all agents.
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.
- 2d ago First seen · 53 lines · 20 tokens per session scan A 375c68bbe4af
remember is a skill published in the GitHub repository plmbr/nui (5 stars, last pushed 5d ago), licensed MIT. It adds 20 tokens to every session and 503 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 2026-08-31.
Other skills, from other repositories
doubt-driven-review
In-flight adversarial check on a non-trivial decision BEFORE it stands — distinct from post-hoc review of a finished diff. Use on "stress-test this decision", "are we sure about this", "verify before commit", "poke holes in this", when working in unfamiliar code, or before an irreversible step (migration, prod deploy…
release-cut
Cut a new pi-agent-dashboard release: promote ## [Unreleased] in CHANGELOG.md, bump every workspace package.json per SemVer, commit, tag v , and push — triggering the Release workflow that publishes every non-private workspace, builds the Electron artifacts, and creates a GitHub Release. Use on "cut a release"…
ship-it
Worktree-side implementation orchestrator for an OpenSpec change. Idempotent: gates automated scenarios on filesystem reality, owns the red-test fix loop, runs the docker harness with always-teardown, then drives ship-change inline. Escape hatch writes SHIPITBLOCKED.md. Runnable headless. Triggers: "ship it", "build…
faq-mine
Mine docs/faq.md from README.md, docs/.md, and the pi-hermes memory stores. Dispatches @fast subagents per source, dedupes against the existing FAQ, and merges entries in caveman style. Use when asked to "build / regenerate / extend the FAQ", "mine docs into FAQ", "mine hermes memory into FAQ", "surface runtime…
session-to-guideline
Turn a pi session into a Markdown "how-we-did-it" collaboration guideline: reads the session's JSONL transcript and synthesizes a reusable playbook of which prompts worked, what had to be steered, and how to reproduce the result faster. Use when: "document this session", "write up how we did X with the AI", "make a…
scenario-design
Draft real-life test SCENARIOS (not smoke tests) from a change/feature spec. Derives edge-case, performance, frontend-quirk and error-handling scenarios with ISTQB techniques, routes each to a test level, and writes test-plan.md, emitting clarification questions on a spec gap. Use on "design test scenarios", "what…