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 code-reviewgit 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/code-review)<a href="https://agentmods.dev/skills/prismer-ai/prismercloud/code-review"><img src="https://agentmods.dev/badge/skills/prismer-ai/prismercloud/code-review/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/code-review"><img src="https://agentmods.dev/badge/skills/prismer-ai/prismercloud/code-review.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 | $0.00072 | $0.04143 |
| Opus 5.5 | $0.00029 | $0.01657 |
| Sonnet 5.5 | $0.00014 | $0.00829 |
| Haiku 4.5 | $0.00007 | $0.00414 |
Grade A, and why
code-review 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 17d 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 — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
code-review
对一个 diff + 验收标准做四段评审，产出按严重度排序的 findings（每条带 file:line + 失败场景），把 /review 的纪律移植到任意 coding agent（apc/05 §2 S5 · apc/12 code-review 行）。
什么时候用：一个 coding task 改完、进 review 门时，需要由非实施者独立审这份 diff。
评审独立性（第一铁律，P2-17）
评审必须由非实施 agent 执行——实施者不自评自的 diff，与 no-self-approval 同精神（apc/05 §2 评审独立性）。服务端也有牙：code-review 工件若 reviewerId === task.assigneeId 直接 403（task-review-artifact.service.ts:126 forbidden_implementer_self_review）。
开审第一步先自证独立：
git log --format='%an <%ae> %H' <base>..<head> # 被审提交的作者
# 断言：作者 ∉ {你自己}。若你就是作者 → 停手，报告"不能自评"，让另一个 agent 审。
四段评审（缺一段不算完）
移植自 /review 的分段纪律——每段独立扫一个维度，产出 findings 再合并按严重度排序：
| 段 | 扫什么 | 怎么做 | 典型 finding |
|---|---|---|---|
| 1. 规约符合 | diff 是否违反 CLAUDE.md / 既有约定 | 读根 + 相关目录的 CLAUDE.md，逐条对 diff | 用了被禁的 pattern、破坏 layer rules |
| 2. bug 浅扫 | 只看 diff 本身的明显 bug | 读 git diff，聚焦大 bug（空/边界/错误分支/资源泄漏/并发），不纠 lint/类型/格式（CI 会管） |
off-by-one、未处理的 null、错误吞异常 |
| 3. 历史上下文 | 结合被改代码的历史看回归 | git blame / git log -p 被改的行，看这段代码为何这么写、这次改会不会破坏原意图 |
改动撤销了一个之前修 bug 的提交、重新引入已知回归 |
| 4. 测试覆盖缺口 | 改动引入的行为有没有测试护 | rg 找对应测试文件、看新增/改动路径是否被断言 |
新分支零测试、负控缺失、断言放松 |
只标真问题，不纠鸡毛（/review 纪律）：预存 bug、非本次改动行、CI 会抓的（lint/类型/格式/import）、senior 不会提的吹毛求疵——都不进 findings。这是避免虚报的纪律，直接对应负控"干净 diff 不虚报"。
Procedure
1. 独立性自证（见上）— 不过则停手
2. 取 diff + 验收标准
git diff <base>..<head> > /tmp/review.diff # 或对 working tree: git diff
cloud task acceptance "$PRISMER_TASK_ID" # 读该 task 的验收标准（可选，若挂 task）
3. 四段逐段扫，每段产 findings
每条 finding 的形状（缺一项不算数）：
{ severity: blocker|major|minor,
segment: convention|bug|history|coverage,
file: "src/foo.ts", line: 42,
finding: "<一句话说清是什么问题>",
failureScenario: "<在什么输入/时序下它会真的坏，可复现的因果>" }
failureScenario 是承重字段：说不清"怎么坏"的 = 还没验证的猜测，降级成 openQuestion，不当 finding 报。
4. 合并 + 按严重度排序
blocker → major → minor。产出：
findings[]（排序后）changeSummary（这份 diff 干了什么，一段话）openQuestions[]（拿不准的，不是 finding）residualTestGaps[]（第 4 段发现的、本次不补但要记的覆盖缺口）
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 17d ago First seen · 199 lines · 72 tokens per session scan A 2aa80ff0788a
code-review is a skill published in the GitHub repository Prismer-AI/PrismerCloud (1,386 stars, last pushed 2d ago), licensed MIT. It adds 72 tokens to every session and 4,143 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 2026-09-29.
Other skills, from other repositories
gentle-ai-bench
Trigger: bench, journey, journeys, driven mode, gentle-ai-bench, journey corpus, j-numbers, bench axis. Author and verify gentle-ai bench journeys; go test ./bench never proves driven execution.
go-testing
Trigger: Go tests, go test coverage, Bubbletea teatest, golden files. Apply focused Go testing patterns.
remove-ai-slops
Removes AI-generated code smells from branch changes or an explicit file list behind regression tests. Use when the user asks to clean up, deslop, or remove AI-slop patterns from recent changes.
pre-pr
Prepare a Honcho change for a pull request to plastic-labs/honcho. Invoke before opening a PR, when drafting a PR body, when asked if a branch is PR-ready, or when filling the pull request template. Checks the linked issue, required tests and docs, then writes Description / Proofs / Fixes.
eval-leakage-audit
Audits whether a verification (eval/metric/experiment/holdout) actually secures independent external ground truth, or whether the designer, the model, and the scorer are just confirming each other in a circle — via a 28-pattern taxonomy. Read-only. Use before trusting any 'how we'll know it worked' — A/B tests…
review
Review Playwright tests for quality. Use when user says "review tests", "check test quality", "audit tests", "improve tests", "test code review", or "playwright best practices check".