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 skills add Prismer-AI/PrismerCloud --skill persona-generatorgit 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/persona-generator)<a href="https://agentmods.dev/skills/prismer-ai/prismercloud/persona-generator"><img src="https://agentmods.dev/badge/skills/prismer-ai/prismercloud/persona-generator/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/prismer-ai/prismercloud/persona-generator"><img src="https://agentmods.dev/badge/skills/prismer-ai/prismercloud/persona-generator.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00183 | $0.04085 |
| Opus 5.5 | $0.00073 | $0.01634 |
| Sonnet 5.5 | $0.00037 | $0.00817 |
| Haiku 4.5 | $0.00018 | $0.00409 |
Grade A, and why
persona-generator 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 22d 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 — 297 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persona Generator
Who speaks. Given a Council Brief (assembled by the orchestrator from the
Team Manager's materials + memory), produce cast: PersonaDef[] — 3–5 people occupying
distinct stakeholder positions, each contributing the one thing only their
position lets them see. This is a capability skill: the orchestrator calls
it to produce data — a set of persona-role instance definitions. Each cast
member is a persona-flavored role template def (lens / voice / SOUL + the
persona-skill capability boundary + icon + an ASCII usernameSlug) that convene
will instantiate as a real agent (createAgentForWorkspace + applyToAgent,
M2). It is not a virtual im_users mask — persona = role instance.
| Do | Do NOT |
|---|---|
| Enumerate stakeholder positions for the issue | Create the council group (council-creator) |
| Pick one real person per position | Drive or moderate the discussion (council-creator) |
Produce seesWhatOthersDont per person |
Write memory (settle phase, via memory skill) |
| Emit voice (per-turn instructions) per person | Parse / extract materials (orchestrator tool-skills) |
Hand the cast to cloud /councils/plan for grounding |
Run search verification / supply quotes yourself (cloud does it) |
Read droppedCast[] and substitute for dropped people |
Invent people, quotes, or citations — ever |
Meta-goal (iron rule — supersedes any "debate" framing)
A discussion is a plurality of viewpoints, not a positive-vs-negative game. Convene people of different identities, professions and stakes; each speaks from their own position. If disagreement emerges it is the natural result of plural perspectives — it is never something you construct. Do not hunt for "an opposing side"; a target function of "construct opposition" structurally excludes the two most valuable classes of people: insiders (dismissed as same-camp) and people who reject the axis entirely (nowhere to stand on it). The UI language is "讨论组" (discussion group), never "吵一架".
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.
- 22d ago First seen · 297 lines · 183 tokens per session scan A cf796fd0a7b0
persona-generator is a skill published in the GitHub repository Prismer-AI/PrismerCloud (1,384 stars, last pushed 6d ago), licensed MIT. It adds 183 tokens to every session and 4,085 once invoked, about $0.0007 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 2026-09-29.
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.
turbo-quant-memory
Install, configure, and operate the Turbo Quant Memory (tqmemory) MCP server. Use when setting up persistent agent memory in a workspace, registering the tqmemory MCP server in a client, or working with tqmemory tools (remembernote, semanticsearch, recentcontext, linkentities, secrets vault).
performing-container-image-hardening
This skill covers hardening container images by minimizing attack surface, removing unnecessary packages, implementing multi-stage builds, configuring non-root users, and applying CIS Docker Benchmark recommendations to produce secure production-ready images.
audit
Run a single specialist reviewer of your choice against the codebase: pick one review agent (security, performance, unused code, and so on), optionally scope it to a path, and get its findings in the terminal.