oncall-init

oncall-init is a skill for Claude Code from anthropics/claude-tag-plugins. It costs 216 tokens per session (13,845 once invoked), scanned A, original, Apache-2.0.

A setup process for connecting a team's on-call or monitoring channel to automatic alert and incident handling.

In plain words
What is it for?
It helps configure monitoring for a team and add or update that team's information in shared on-call memory.
Why use it?
It stores the team's channels, rotation, procedures, and available connections so responders can use the same context during incidents.

Skill for Claude Code ✓ vendor

Written for Claude Code: shipped in a Claude Code plugin. Also seen: reads .claude/ paths; mentions CLAUDE.md; mentions Claude Code.

Part of the claude-tag-oncall plugin — 6 skills shipped together

Good fit It helps configure monitoring for a team and add or update that team's information in shared on-call memory.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/anthropics/claude-tag-plugins/oncall-init
About the project

anthropics/claude-tag-plugins is a collection of plugins that connect the Claude coding agent to SaaS services such as task trackers, databases, monitoring systems, and document platforms. Each plugin focuses on one service, so workspaces can enable the integrations they use.

anthropics/claude-tag-plugins · 76 stars · on GitHub

Install

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.

Any agent
npx skills add anthropics/claude-tag-plugins --skill oncall-init
Clone the repo
git clone --depth 1 https://github.com/anthropics/claude-tag-plugins

Made for: Claude Code.

Or install claude-tag-oncall, the plugin that ships this one along with the rest of its 6 skills.

Wrote 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.

agentmods badge for oncall-init

README.md
[![agentmods](https://agentmods.dev/badge/skills/anthropics/claude-tag-plugins/oncall-init/github.svg)](https://agentmods.dev/skills/anthropics/claude-tag-plugins/oncall-init)
Your own site
<a href="https://agentmods.dev/skills/anthropics/claude-tag-plugins/oncall-init"><img src="https://agentmods.dev/badge/skills/anthropics/claude-tag-plugins/oncall-init/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.

agentmods 80×15 button for oncall-init

Your own site · 80×15
<a href="https://agentmods.dev/skills/anthropics/claude-tag-plugins/oncall-init"><img src="https://agentmods.dev/badge/skills/anthropics/claude-tag-plugins/oncall-init.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 216 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 13,845 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00216 $0.13845
Opus 5.5 $0.00086 $0.05538
Sonnet 5.5 $0.00043 $0.02769
Haiku 4.5 $0.00022 $0.01384

Measured 1mo ago against content hash 1d4ee9dfbfe1, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

oncall-init 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 1mo 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.

claude-tag-oncall/skills/oncall-init/SKILL.md · 938 lines

How it starts

The opening of the file, as written. The whole thing — 938 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Oncall init (per team, one oncall memory)

This sets up Claude Tag for oncall for the team whose monitoring channel it was asked in, and saves the result where the whole Slack workspace can use it. Anyone can run it. A workspace usually has several oncall / monitoring channels, one per team or rotation. Running this in each of them appends that team's section (its alert and incident channels, rotation, process, available connectors) to the same single oncall memory the whole workspace shares. It never overwrites another team's section. Running it again in the same channel merges into that team's section instead of starting over, and records who ran it when.

Where this runs. Two kinds of channels matter, and the user should hear this in plain words during setup and at the close ("Run me in your team's oncall or monitoring channel. Other teams do the same in theirs, and what I save is reused automatically in every incident channel."):

  • Oncall / monitoring channels: a team's standing channel where alerts land and the rotation talks day to day (#payments-oncall, #db-alerts). Run this init from each one that wants it. Besides its section in the oncall memory, the monitoring channel gets a short note of its own (team and rotation, which bots post here, how loud to be) in its memory.
  • Incident / alert channels: short-lived channels opened per incident, or a shared alerts feed (#inc-…). Nothing is set up there by hand; when Claude lands in one, incident-init reads the oncall memory and picks the section for the team the incident belongs to. incident-investigate works mainly there (and in the monitoring channel, in an alert's thread); oncall-handoff runs mainly in the monitoring channel, usually on a schedule. Both read the oncall memory the same way.

Before you start

  • Read the shared workspace memory index and look for an existing oncall entry, whatever it is named. If one exists, open it and look for a section for this team or this channel. Section found: this is a re-run; say "Updating the oncall setup (last run by <@U…>)" and edit that section in place at the end. Oncall memory found but no section for this team: say "Adding to the existing oncall setup (other teams already there: )" and append a new section at the end; leave every other team's section exactly as it is. Either way reuse the same file and its existing index line. Never create a second oncall memory or a second index line.
  • Skip what is already set up. Most of this setup is workspace-wide: the connectors, the repos, the paging and monitoring tools. If the oncall memory already records them (this requester ran setup in another channel, or another team did and the same tools serve both), do not walk anyone through them again. Say in one line what is already set up and where it came from, list only the items still open, and go straight to the channel-local part: which bots post here, how loud to be here, this channel's team and rotation, and its own note. One part is never skipped: connector availability. On every run, refresh included, redo step 1's inventory (the agent connectors and the agent's own tools) and exercise the read-only proving pull again rather than trusting the recorded table — connectors change between runs. Update the recorded table with what you find. The standing-instructions scan is never skipped either: on a re-run, check the recorded runbook docs and repos for standing instructions, and if you find some with no import decision recorded, ask step 2's one import question.
  • If this is a private channel, workspace memory is read-only from here. Say so in one line and ask them to run this from any public channel. Stop.
  • If this channel looks like a per-incident channel rather than a monitoring channel, say in one line that init is best run from the team's standing oncall / monitoring channel, then continue anyway (the oncall memory is the same either way; only the channel note is skipped).
  • Keep every conversational Slack reply short: six lines or fewer, plain sentences, no em dashes, no walls of text — the quoted templates and message formats in these steps are exempt and used as written, the closing message in step 6 (one bullet per behavior, pinned) included. Put a blank line between paragraphs and around lists: Slack collapses a single newline, so lines split only by one newline post as one fused paragraph.
  • Keep every message this setup posts short; the formats in these steps are upper bounds, not templates to fill, so drop any line you have nothing real for.
  • Show, don't tell. Whenever you report something during setup, show the real thing you found (the actual channels, bots, tools, people, numbers; a chart via the built-in dataviz skill when a trend says it better, e.g. pages per day) instead of describing what you could do. Name the source next to each number so someone can check it.
  • Stay at the altitude a reader can act on. Raw evidence (HTTP status codes, monitor ids, channel counts, per-search results) belongs in the oncall memory and in your own reasoning, not in the Slack messages. In Slack, say what works, what doesn't, and what to do about it.

Read the full file on GitHub · 938 lines

Files

What ships with it

2 files 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.

Changes

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.

  1. 1mo ago Changed · -10 lines · -82 tokens per session 1d4ee9dfbfe1
  2. 2mo ago First seen · 948 lines · 298 tokens per session scan A c6b6ce53ad44

Subscribe to this mod's changes

oncall-init is a skill published in the GitHub repository anthropics/claude-tag-plugins (76 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 216 tokens to every session and 13,845 once invoked, about $0.0009 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 2026-09-03.

Related

oncall-init compared with skills from other repositories

oncall-init next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
oncall-initanthropics/claude-tag-pluginsSkill761mo agoApache-2.0A216Claude Code
imagegenopenai/codexSkill133kyesterdayApache-2.0A113Codex
playwright-climicrosoft/playwrightSkill99kyesterdayApache-2.0A19Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginnersSkill79k4d agoMITA200Claude Code, Codex
systematic-debuggingobra/superpowersSkill313k3d agoMITA21Claude Code
next-cache-components-adoptionvercel/next.jsSkill143kyesterdayMITA95Claude Code
next-partial-prefetching-adoptionvercel/next.jsSkill143kyesterdayMITA103Claude Code