Prismer Cloud is an infrastructure layer for AI agents that provides shared learning, compressed context, persistent memory, collaboration, messaging, tasks, identity, and workspaces. It is for agents and the people building or using long-running agent systems that need information and outcomes to persist across sessions. The catalogue entries provide skills, hooks, agents, instructions, and a plugin for using Prismer Cloud.
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/prismer-ai/prismercloud/teamnpx skills add Prismer-AI/PrismerCloud --skill teamgit clone --depth 1 https://github.com/Prismer-AI/PrismerCloudWrote 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/prismer-ai/prismercloud/team)<a href="https://agentmods.dev/skills/prismer-ai/prismercloud/team"><img src="https://agentmods.dev/badge/skills/prismer-ai/prismercloud/team.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00071 | $0.01365 |
| Opus 5 | $0.00036 | $0.00682 |
| Sonnet 5 | $0.00014 | $0.00273 |
| Haiku 4.5 | $0.00007 | $0.00136 |
Grade A, and why
team 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 6d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Team
Use this skill when work needs another human in the loop. The workspace + project surfaces collectively decide who can see and act on tasks, conversations, and assets in a workspace; this skill is how the agent exposes those surfaces to the user.
⛔ Hard rules — human-in-loop
- Never auto-send an invite. Agents may propose who should be invited and explain why, but the final action (
POST /api/im/workspaces/:id/invites) must originate from a human click in workspace settings or from an explicit user instruction like "send the invite". If you ever find yourself about to call invite-create without that explicit go-ahead, stop and surface the proposal as text instead. - Never expose member emails. The
/api/im/workspaces/:id/membersresponse carries imUserIds, not addresses. If the user asks "what's Bob's email", say you can see Bob's username + display name but not their email. - Distinguish workspace member from project member. Workspace member = ACL boundary across the whole workspace (chat, tasks, assets). Project member = a sub-scope inside that workspace with its own role enum (owner/contributor/observer). Adding someone to a project requires them to be a workspace member first — surface that constraint when proposing.
- Never silently re-add a removed member. If a user was removed from the workspace, their project memberships were cascade-deleted on purpose (release201/16 §3.2.3). Treat re-adding as a new collaboration event that needs explicit user consent, not a "fix it" automation.
When to use
- The user names someone who isn't already on the workspace: "Have Maya look at this", "Loop Bob in on Q2 launch".
- The user asks who's on the team or what the roster looks like: "who has access to this workspace", "who's working on Q2 launch".
- The user asks to remove someone, change someone's role, or move someone between projects.
- An agent (e.g. CEO role) is reasoning about staffing in onboarding and needs to propose additions without taking action.
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.
- 6d ago First seen · 77 lines · 71 tokens per session scan A d4167bb386c5
team is a skill published in the GitHub repository Prismer-AI/PrismerCloud (1,410 stars, last pushed 1mo ago), licensed MIT. It adds 71 tokens to every session and 1,365 once invoked, about $0.0004 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
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.
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.
docmancer
Work from the same local memory as every other coding agent on this machine. Recall prior decisions, preferences, instructions, and project conventions that Claude Code, Codex, Cursor, and other agents wrote here, with cited sources, fully local. Also searches a separate local technical-documentation index.
agent-prompts-warmup
Audit and sync agent instruction files across all coding agent formats. FRE (first-run) checks scaffolding completeness; ongoing use keeps files in sync after edits.
memex-sync
Sync Zettelkasten cards across devices via git.
setup-bot
Diagnose and fix Telegram bot connection issues -- verify config, test send, resolve common errors.