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 tasksgit 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/tasks)<a href="https://agentmods.dev/skills/prismer-ai/prismercloud/tasks"><img src="https://agentmods.dev/badge/skills/prismer-ai/prismercloud/tasks/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/tasks"><img src="https://agentmods.dev/badge/skills/prismer-ai/prismercloud/tasks.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 Tool Misuse · line 384 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- medium Excessive Agency · line 251 Skill grants unrestricted tool access without appropriate constraints. An agent with unfettered tool access can perform arbitrary actions including file modification, network requests, and code execution.Fix: Restrict tool access to only the tools required for the skill's stated purpose. Use an explicit allowlist rather than granting blanket access.
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 | $0.00068 | $0.06200 |
| Opus 5.5 | $0.00027 | $0.02480 |
| Sonnet 5.5 | $0.00014 | $0.01240 |
| Haiku 4.5 | $0.00007 | $0.00620 |
Grade A, and why
tasks 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 24d 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 — 414 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tasks
Use this skill to drive the workspace Kanban end-to-end. Tasks are durable board items with owner, priority, schedule, and conversation linkage. Every operation goes through the cloud task CLI — never reply that a task was created/moved/completed unless the command actually returned a task ID and status.
⛔ Hard rules — delegation discipline
When the user asks you to assign / delegate / hand off work to ANOTHER agent (e.g. "create kanban tasks and assign to @research-agent", "give this to Bob"):
- Call
cloud task create --assignee-name <agent>(or--assignee-id). That is the ONLY legitimate delegation path. A delegation is a tracked board card that ALSO auto-dispatches: the card shows on the Kanban (留痕/可观测) and the cloud routes it to the target agent's daemon the moment the assignee is set — the target picks it up via its own dispatch loop, no manual "drag to Running" needed. (A--no-cardpure run exists for internal orchestrator sub-steps that should NOT surface a card.) - For a delegation-only request, stop after reporting the returned IDs / titles. If the user also requested orchestration, follow-through, or result collection, continue read-only status/result collection with bounded waits as described below. Never duplicate the assignee's work yourself.
- NEVER use a generic
Task/ subagent / fan-out / parallel-agent tool to silently do the work in-process. That bypasses the kanban board, the assignee never sees the card, the user's mental model ("an agent is working on this") is violated, and the delegation is fake. If you find yourself reaching for any tool whose name is "Task", "Subagent", "Worker", "Fanout", "ParallelAgents", or anything else that spawns an inline executor — stop and re-read this section. - The phrase "I've also started working on these" after a
cloud task createis a red flag that you violated rule 3. The correct phrase is "Tasks created and assigned. @research-agent will pick up the cards."
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.
- 24d ago Changed · +15 lines 444de268f0d4
- 1mo ago First seen · 399 lines · 68 tokens per session scan A d7a297f424d2
tasks is a skill published in the GitHub repository Prismer-AI/PrismerCloud (1,363 stars, last pushed yesterday), licensed MIT. It adds 68 tokens to every session and 6,200 once invoked, about $0.0003 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
req-create
Create structured requirement documents from user ideas. Use when capturing new features, tasks, or user stories.
repository-onboarding
Orient an agent without loading the entire repository.
grooming
Shape ambiguous work into an agreed, executable plan. Use when the user asks to groom, scope, decompose, or prepare work before implementation.
grooming-evidence
Ground work grooming in existing product evidence. Use while shaping tasks from code, documentation, tracker state, and user feedback.
planning-with-files
Organize complex work with file-based planning artifacts such as taskplan.md, findings.md, and progress.md. Use when the user needs a multi-step task, project, or research effort broken down and tracked across many tool calls.
V3 Swarm Coordination
15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.