Kubeshark Installer
kubeshark/kubeshark
Installs and configures Kubeshark on a Kubernetes cluster, choosing between the quick CLI path and a Helm install with custom values.
Periodic health sweep of the running system via the debug pipeline (cloud logs / k8s / daemon / DB slices).
Install Observability
$ npx skills add Prismer-AI/PrismerCloud --skill observability -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Prismer-AI/PrismerCloud observability --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Prismer-AI/PrismerCloud.git skills-src && mkdir -p .claude/skills && cp -r skills-src/sdk/apc/skills/observability .claude/skills/observability && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "observability" agent skill from https://github.com/Prismer-AI/PrismerCloud/tree/main/sdk/apc/skills/observability into .claude/skills/observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "observability", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Prismer-AI/PrismerCloud/tree/main/sdk/apc/skills/observabilityType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Prismer-AI/PrismerCloud --skill observability -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Prismer-AI/PrismerCloud observability --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Prismer-AI/PrismerCloud.git skills-src && mkdir -p .agents/skills && cp -r skills-src/sdk/apc/skills/observability .agents/skills/observability && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "observability" agent skill from https://github.com/Prismer-AI/PrismerCloud/tree/main/sdk/apc/skills/observability into .agents/skills/observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "observability", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Prismer-AI/PrismerCloud --skill observability -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Prismer-AI/PrismerCloud observability --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Prismer-AI/PrismerCloud.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/sdk/apc/skills/observability .cursor/skills/observability && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "observability" agent skill from https://github.com/Prismer-AI/PrismerCloud/tree/main/sdk/apc/skills/observability into .cursor/skills/observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "observability", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Prismer-AI/PrismerCloud.git --path sdk/apc/skills/observability--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Prismer-AI/PrismerCloud --skill observability -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Prismer-AI/PrismerCloud observability --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Prismer-AI/PrismerCloud.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/sdk/apc/skills/observability .gemini/skills/observability && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "observability" agent skill from https://github.com/Prismer-AI/PrismerCloud/tree/main/sdk/apc/skills/observability into .gemini/skills/observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "observability", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Prismer-AI/PrismerCloud observabilityInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Prismer-AI/PrismerCloud --skill observability -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Prismer-AI/PrismerCloud.git skills-src && mkdir -p .github/skills && cp -r skills-src/sdk/apc/skills/observability .github/skills/observability && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "observability" agent skill from https://github.com/Prismer-AI/PrismerCloud/tree/main/sdk/apc/skills/observability into .github/skills/observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "observability", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Prismer-AI/PrismerCloud --skill observability -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Prismer-AI/PrismerCloud observability --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Prismer-AI/PrismerCloud.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/sdk/apc/skills/observability .opencode/skills/observability && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "observability" agent skill from https://github.com/Prismer-AI/PrismerCloud/tree/main/sdk/apc/skills/observability into .opencode/skills/observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "observability", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
observability- GitHub stars
- 1.6k
- Token cost
- ~2.6k tokens
- SKILL.md length
- 714 words
- Files
- 2
- Skills in repo
- 88
- Repo updated
- First seen
- Licence
- MIT
At a glance
Periodic health sweep of the running system via the debug pipeline (cloud logs / k8s / daemon / DB slices).
- Works in 6 steps: 先落调用回执（见文末 ACK 块），再做 canonical discovery… → 拉全局索引，覆盖其余信号面 → 锁定可疑目标 → 下钻取副作用切片 → …
- Tasks that involve Observability
- SKILL.md covers 工具契约（签名以此为准，先核后用）, Workflow, 输出契约（机器判据按这个复验，别自由发挥格式） and 产出（副作用 oracle，报告里必须给）, plus 1 more section
- Calls npx and rg; needs PRISMER_API_KEY
What it does
Observability is an agent skill from Prismer-AI/PrismerCloud. Periodic health sweep of the running system via the debug pipeline (cloud logs / k8s / daemon / DB slices). On a real anomaly, open a bug task (--kind workitem) carrying the evidence refs so it re-enters the bugfix loop. A healthy sweep opens NO task — never fabricate a bug.
Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `skill.json`). Compatibility notes: ["claude-code","prismer-sdk"]
It sits in DevOps & Cloud, covering Observability and Container orchestration. It works with Kubernetes. The licence is MIT.
When your agent uses it
- Tasks that involve Observability
- Tasks that involve Container orchestration
Example prompts
- “/observability”
Requirements
- Node.js
- A credential in PRISMER_API_KEY
- Compatibility (from SKILL.md): ["claude-code","prismer-sdk"]
- Pre-approved tools (allowed-tools): Bash
Workflow steps
6 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit e5d9444. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
Bash
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
npxrg
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
PRISMER_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Compatibility
["claude-code","prismer-sdk"]
From compatibility in the SKILL.md frontmatter.
Context cost
Observability loads about 2.6k tokens when it runs. Until then it costs about 73 tokens; SKILL.md has 714 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
allowed-tools: Bash
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from Prismer-AI/PrismerCloud at commit e5d9444, republished under its MIT licence (© Prismer-AI). 714 words, ~2,649 tokens.
Download SKILL.mdSave it as
.claude/skills/observability/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- observability
- description
- Periodic health sweep of the running system via the debug pipeline (cloud logs / k8s / daemon / DB slices). On a real anomaly, open a bug task (--kind work_item) carrying the evidence refs so it re-enters the bugfix loop. A healthy sweep opens NO task — never fabricate a bug.
- allowed-tools
- Bash
- compatibility
- ["claude-code","prismer-sdk"]
- license
- MIT
- scope
- common
- metadata.category
- observability
observability
用 debug pipeline 巡检运行中的系统（cloud log / k8s / daemon / DB 切片），异常时开一个 bug task 把证据带回 bugfix 循环（apc/05 S10 · 生命周期矩阵行 11 监控→回流）。触发器 = product205 定时任务后端（已建，缺前端）挂周期巡检——本 skill 是那次巡检真正干的活，不悬空。
承重纪律：
- healthy 扫描不开 task。 没有异常就报"绿"并停手——绝不为了"有产出"造一个假 bug。一个无论系统健不健康都会建 task 的巡检 = 噪声制造机。
- 异常 → bug task 必须带证据 ref。 bug task 的 description 要挂可追溯锚（pod / workspace / task id + debug 切片摘要，或把 bundle 产物
cloud asset upload后引asset:<id>）。空口"系统好像有问题"不是 bug task。 - oracle 是真 task 行，不是聊天叙述。 "我建了 bug task" 不算数——
cloud task create返回的真 id + 回读的 task 行才算。
什么时候用：周期巡检（定时任务触发）或收到"系统是不是出问题了"时——先用 debug pipeline 取副作用切片核实，再决定是否回流。
工具契约（签名以此为准，先核后用）
| 命令 | 作用 | 输出/退出码 |
|---|---|---|
npx tsx scripts/debug/admin-observability.ts capabilities [--env=local|test|prod] | canonical Admin v1 discovery；读取 principal、capabilities、schema version 与 opaque contract digest | 0 成功；不兼容/无权限非零 |
npx tsx scripts/debug/admin-observability.ts logs --target-kind=service --target-id=prismer-cloud --purpose=<reason> [--since=15m] [--cursor=<opaque>] [--completeness=require-complete|allow-partial] | canonical POST /api/admin/v1/logs:query 只读快照；命令内部必须先 discovery；cursor 只能原样回传 | 默认 require-complete；置信边界完整 0，不满足 3，请求/合同错误 1，用法错误 2 |
cloud admin log-targets --kind <service|sandbox|daemon> --purpose <reason> [--workspace-id <id>] [--cursor <opaque>] | daemon-held credential 下发现 DB-resolved logical targets；不接受 namespace/selector | 0 完整成功；partial projection 2；请求失败 1 |
cloud admin logs --target-kind <kind> --target-id <id> --purpose <reason> [--attach-to-task [taskId]] | credentialless loopback 查询 service/sandbox/daemon；可经既有 daemon task-attach 把 JSON 证据绑定到 task | 0 完整成功；partial 2；失败 1；attach 要求 daemon dispatch + PRISMER_ARTIFACTS_DIR |
npx tsx scripts/debug/inventory.ts [--env=local|test|prod] [--json] | 全局索引：running pods / recent workspaces / recent tasks / recent errors | 人读 5 段 或 --json |
npx tsx scripts/debug/bundle.ts <workspace|task|pod> <id> [--sections=db,system,k8s,daemon] [--stdout] [--since=ISO] | 复合切片（DB+system-log+k8s+daemon） | 默认写 ./debug-bundle-*.json，--stdout 打屏 |
npx tsx scripts/debug/snapshot.ts <workspace|task|conversation|container> <id> [--json|--brief] | DB 切片（task 终态行/runs/logs/approvals/assets） | 默认 compact，--json raw |
npx tsx scripts/debug/logs.ts [--contains=text] [--since=ISO|10m|1h] [--level=...] [--json] | cloud 进程 pino ring buffer | 每行一条 或 --json |
cloud task create --title <t> --description <d> --kind work_item [--priority high] [--json] | 开 bug task（--kind work_item 是 board 投影） | 打印 ID: <taskId>（--json 出整行） |
cloud task list [--json] | 回读 task 行确认落库 | 0 成功 |
--kind合法值恰好两个：work_item（默认，bug/工作项）/goal。bug 巡检一律work_item。- 鉴权：debug pipeline 走 admin RBAC（
--env=localdev 短路免鉴权；--env=test|prod需PRISMER_API_KEY_TEST/PRISMER_API_KEY）。coding agent 的 workdir env 不注入高危凭据——test/prod 巡检由平台方持凭发起，不在 agent 的 bash 里裸读（apc/05§3 凭据可见性边界）。 - 凭据边界：canonical 命令没有
--api-key参数，也不把 credential 写入 stdout、stderr 或产物；禁止env、printenv、shell tracing（set -x）和把 Authorization header 拼进命令行。平台执行器在模型不可见边界注入 credential。 - 合同边界：只调用
/api/admin/v1/capabilities与/api/admin/v1/logs:query，不猜 403、不回退 legacy route、不猜 digest 算法。若平台固定了本次发布 digest，可由执行器注入PRISMER_ADMIN_CONTRACT_DIGEST做 exact match。
Workflow
1. 先落调用回执（见文末 ACK 块），再做 canonical discovery + Cloud 日志快照
APC 自动巡检默认要求完整结果。先调用 capabilities，再由同一命令进程完成 logs query：
mkdir -p .e2e-tmp/apc/observability
npx tsx scripts/debug/admin-observability.ts capabilities \
> .e2e-tmp/apc/observability/admin-capabilities.json
npx tsx scripts/debug/admin-observability.ts logs \
--target-kind=service --target-id=prismer-cloud --since=15m \
--purpose="periodic APC observability sweep" \
--completeness=require-complete \
> .e2e-tmp/apc/observability/admin-service-logs.json
admin_logs_exit=$?admin_logs_exit=3 表示所需置信边界不完整，不得宣布 healthy；读取 JSON 中的
requestId、sources[]、partial、attemptedSourceTiers、availableSourceTiers、
confidenceBoundary.productionRetainedRequirement、contractDigest、evidenceHash 后报告受限结论。
attemptedSourceTiers 只说明服务端尝试过某 tier；只有 availableSourceTiers 才代表可用证据，
retained source 为 unavailable 或 error 时严禁把它写成 retained evidence。
只有 human 明确做探索性查询时才可传 allow-partial，且逐 source outcome 仍必须保留。1/2 是请求或
用法失败，同样不能当作“没有 error”。canonical 输出可作为 task-bound evidence，但先确认其中不含凭据；
不要长期保存为 loose file。
生产环境的 require-complete 还有强 gate：必须同时看到
availableSourceTiers 包含 retained、
confidenceBoundary.productionRetainedRequirement.satisfied=true、稳定 ordering/continuity、
完整 coverage、truncated=false、mayDuplicate=false。任一不满足均按退出码 3 处理。
分页时只可把响应 nextCursor 原样作为下一次 --cursor=<opaque>；不得解析、修改或自行生成 cursor。
SLS 当前只提供 offset continuation，服务端会明确标记 continuity=best-effort、mayDuplicate=true 和
partial=true；即使 provider query 返回 Complete 也不得升级成完整证据。Sandbox/Daemon 查询前先用
cloud admin log-targets 发现 logical id，禁止把 Pod、namespace 或 label selector 当 target id 猜测。
2. 拉全局索引，覆盖其余信号面
mkdir -p .e2e-tmp/apc/observability
npx tsx scripts/debug/inventory.ts | tee .e2e-tmp/apc/observability/inventory.md; echo "inventory exit=$?"
npx tsx scripts/debug/inventory.ts --json > .e2e-tmp/apc/observability/inventory.json # 机器形（可选）产物落 repo-relative 的 .e2e-tmp/apc/observability/（已在 .gitignore），不要落 /tmp——判据要读回你引用的那一行，/tmp 从仓库根不可解析、跑完即毁的证据等于没有证据（同 test204「证据销毁反 pattern」）。报告前不许删这批产物。
读 5 段：pods（有没有 pending/crash）· workspaces · recent tasks（有没有卡在 pending/running 超时）· recent errors（error/warn 级别）。先索引再下钻——不要一上来 logs.ts --since=30m | grep（那是 v0 习惯）。
Show full SKILL.md (277 more words)Show less
3. 锁定可疑目标 → 下钻取副作用切片
对索引里冒出的可疑目标（报错的 pod / 卡死的 task / 异常 workspace）一次拿全套：
# 已知某 task/workspace/pod 可疑 → 复合切片
npx tsx scripts/debug/bundle.ts task <taskId> --sections=db,system,k8s,daemon --stdout > .e2e-tmp/apc/observability/bundle.json
# 或单钻 DB
npx tsx scripts/debug/snapshot.ts task <taskId> --json > .e2e-tmp/apc/observability/snapshot.json
# 关键字检索 cloud log
npx tsx scripts/debug/logs.ts --contains=<taskId> --since=1h > .e2e-tmp/apc/observability/logs.md4. 判异常（副作用为准，不猜）
| 观察到的副作用 | 判定 |
|---|---|
recent errors 有 level:error（非预期的一次性 warn）· pod crash/pending 超时 · task 卡 running 超 reaper 阈值无心跳 · daemon /healthz 不应答 | 异常 → 第 4 步开 bug task |
| 全绿：无 error 级、pods running、tasks 正常流转、daemon 健康 | healthy → 报绿，不开 task，停手 |
单条 flaky/预期内 warn（如 [K8sSandbox] pod-status: read failed 这类已知噪声） | 非异常——记一句备注，不开 task（造假 bug 比漏报危害大） |
canonical query 的服务端 partial=false 不等于生产证据 gate 已满足，更不等于“事实必然完整”；
confidenceBoundary.partial=true、truncated=true 或生产 retained gate 不满足时，结论置信边界必须显式
收窄，自动巡检不得据此判 healthy。
拿不准是不是真异常 → 单钻确认（
snapshot/logs），证据不足不开 task。开一个假 bug 会污染 bugfix 循环。
5. 异常 → 开 bug task（带证据回流 1b）
cloud task create \
--title "[observability] <一句话症状: pod X crash / task Y stuck>" \
--description "Anomaly from periodic sweep.
Target: <pod|task|workspace>:<id>
Evidence: <recent-errors 摘要 / bundle 关键段 / asset:<id>>
Repro: npx tsx scripts/debug/bundle.ts <entity> <id> --stdout" \
--kind work_item --priority high --json抓返回的 id（--json 里 data.id，或人读 ID: 行）——这条真 task 行是本 skill 的产出 oracle。可选：cloud asset upload .e2e-tmp/apc/observability/bundle.json 拿 asset:<id> 挂进 description 作持久证据。
6. 回读确认落库
cloud task list --json | grep <newTaskId> # 或 cloud task get <id>确认 bug task 真行存在、kind=work_item、带证据。
输出契约（机器判据按这个复验，别自由发挥格式）
旧判据是「正文里出现过 pod/task/error 加个数字」的关键词匹配——一篇没跑过任何命令的报告照样满分，而且只扫了 pods 就宣布全绿也照绿（其余四面静默跳过，判据看不出来）。现在五个信号面各占一行、由 dimension-coverage 逐面复核：某一面没写这行 = 判红，正文里出现那个词不算数。
每行的答案二选一：① 指向你这轮真落盘的巡检产物里的那一行（repo-relative path:line，判据把该行读回磁盘，文件不存在 / 行号越界 / 空行 → 判红）；② 显式 N/A — <理由 ≥20 非空白字符>（这一面本轮确实扫不到，比如没有 daemon 可达）。
- SIGNAL-pods: .e2e-tmp/apc/observability/inventory.md:12
- SIGNAL-workspaces: .e2e-tmp/apc/observability/inventory.md:21
- SIGNAL-tasks: .e2e-tmp/apc/observability/inventory.md:34
- SIGNAL-errors: .e2e-tmp/apc/observability/inventory.md:47
- SIGNAL-daemon: N/A — 本轮 --env=local 无在跑的 sandbox pod，daemon /healthz 无可探测目标行号照抄 cat -n / rg -n 你自己那份产物的真实输出，不许凭印象写。引用必须 repo-root-relative（/tmp/... 与绝对路径一律判红——这也是上面要求产物落 .e2e-tmp/ 的原因）。报告前不要删产物：判据是在你跑完之后才读盘的。
产物存成可引用的扩展名：引用解析器只认固定后缀集（
ts/tsx/js/jsx/mjs/cjs/prisma/sql/md/json/sh/py/yml/yaml）——所以人读产物存.md、机器产物存.json。存成.txt/.log引用不会被解析，那一面会被判成"没给可复核证据"。
这条判据管的是「每一面都被显式判过」，不替代下面的异常/healthy 判定——它挡的是静默漏扫（只看了一面就宣布全绿），不是替你判异常。
产出（副作用 oracle，报告里必须给）
- debug 切片真产物：inventory/bundle/snapshot/logs 的结构化输出（含 recent errors / pod 状态 / task 终态字段）——不是"我看了一下感觉没事"。
- canonical Admin receipt：capabilities + logs query 输出必须包含 contract digest、principal、requestId、
attemptedSourceTiers、availableSourceTiers、逐 source outcome、coverage/partial/truncated、production retained gate、redaction ruleset 和 evidence hash；默认置信边界不完整的命令退出码必须为3。 - 异常路径：
cloud task create --kind work_item返回的真 task id + 回读的 task 行（kind=work_item）+ description 里的证据 ref（target id / asset）。 - healthy 路径：明确"无异常、未开 task"，附巡检覆盖了哪些目标（pods/tasks/errors 计数）作为扫过的证明。
不许：healthy 时凭空造 bug task（假阳）· bug task 无证据 ref（空口判红）· 断言聊天文本而非真 task 行 · 拿旧 bundle 当本轮证据 · 把已知噪声 warn 当异常刷 task · 把巡检产物写进 /tmp 或跑完就删（证据必须留到判据读盘之后）· 只扫一两个信号面就宣布全绿（五面各自一行，缺一行判红）。
<!-- APC-ACK:v1 -->调用回执（APC 平台方运营纪律 · 自动注入，勿手改）
执行本 skill 的第一步，先落一条调用回执：
cloud skill ack observability --task "$PRISMER_TASK_ID"按退出码分流（这条命令的退出码是承重信息，禁止用 || 兜底、; true、
set +e 或重定向把它抹掉）：
| exit | 含义 | 你要做的 |
|---|---|---|
0 | 回执已落库（im_task_logs.action='skill_ack'） | 继续执行本 skill |
3 | 无 task 上下文——本次运行没有 task，产不出回执 | 继续执行本 skill；但本次运行没有回执，任何报告里都不得声称已 ack |
4 | 你不是该 task 的 assignee，服务端拒绝 | 停下并上报：回执只能由执行该 task 的 agent 产生 |
1 | 其它失败（网络 / 服务端） | 重试一次；仍失败则继续执行，并在结果里显式标注「回执缺失」 |
回执只证明本 skill 被调度，不证明执行正确——效果证明由本 skill 自己的 acceptanceCriteria 副作用断言承担（apc/04 §2 层 1 诚实标注）。
<!-- /APC-ACK:v1 -->© Prismer-AI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file in sdk/apc/skills/observability of Prismer-AI/PrismerCloud.
- SKILL.md
- skill.json
Open the folder on GitHubat commit e5d9444
Compare with similar skills
Observability next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Observability this skillPrismer-AI/PrismerCloud | 1.6k | — | ~2.6k | Automated safety check: Notes | MIT | |
| Kubeshark Installerkubeshark/kubeshark | 12k | — | ~3.6k | Automated safety check: Notes | Apache-2.0 | |
| Kubeshark KFL2 Filter Referencekubeshark/kubeshark | 12k | — | ~3.6k | Automated safety check: Pass | Apache-2.0 | |
| KubeSphere ServiceMesh Managerkubesphere/kubesphere | 17k | — | ~2.4k | Automated safety check: Pass | Custom licence | |
| Kubernetes Troubleshooting with Inspektor Gadgetinspektor-gadget/inspektor-gadget | 2.9k | — | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Logfire Infrastructurepydantic/skills | 140 | — | ~1.8k | Automated safety check: Pass | MIT |
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Questions about Observability
What does Observability do?
Periodic health sweep of the running system via the debug pipeline (cloud logs / k8s / daemon / DB slices). Observability is an agent skill from Prismer-AI/PrismerCloud. Periodic health sweep of the running system via the debug pipeline (cloud logs / k8s / daemon / DB slices).
When should I use Observability?
Observability fits situations like: tasks that involve Observability; tasks that involve Container orchestration.
How do I install Observability in Claude Code?
Run `npx skills add Prismer-AI/PrismerCloud --skill observability -a claude-code`. Or copy the skill folder (sdk/apc/skills/observability in Prismer-AI/PrismerCloud) into .claude/skills/observability in your project. Claude Code loads it when a task matches its description.
How do I install Observability in Codex?
Run `npx skills add Prismer-AI/PrismerCloud --skill observability -a codex`. Or copy the skill folder (sdk/apc/skills/observability in Prismer-AI/PrismerCloud) into .agents/skills/observability in your project. Codex loads it when a task matches its description.
Can I use Observability in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Prismer-AI/PrismerCloud --skill observability -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/observability, .gemini/skills/observability, .github/skills/observability and .opencode/skills/observability in your project.
What does Observability need to run?
Going by SKILL.md and its folder, Observability needs the command-line tools its instructions call (npx and rg) and credentials named PRISMER_API_KEY. Our summary lists: Node.js; A credential in PRISMER_API_KEY. Its frontmatter pre-approves these tools: Bash. Compatibility (from SKILL.md): ["claude-code","prismer-sdk"].
Does Observability access the network?
SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Observability safe to install?
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Observability use?
Observability is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Observability use?
About 2.6k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Observability?
Skills that share tags, products or a category with Observability: Kubeshark Installer (kubeshark/kubeshark, 12k stars), Kubeshark KFL2 Filter Reference (kubeshark/kubeshark, 12k stars), KubeSphere ServiceMesh Manager (kubesphere/kubesphere, 17k stars) and Kubernetes Troubleshooting with Inspektor Gadget (inspektor-gadget/inspektor-gadget, 2.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Observability?
Prismer-AI (a GitHub organization) maintains it in Prismer-AI/PrismerCloud, which has 1,555 GitHub stars. The repository holds 88 skills in this directory. The repository was last updated on September 30, 2026.
Source: Prismer-AI/PrismerCloud on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.