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 Rootly-AI-Labs/rootly-claude-plugin --skill oncallgit clone --depth 1 https://github.com/Rootly-AI-Labs/rootly-claude-pluginWrote 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/rootly-ai-labs/rootly-claude-plugin/oncall)<a href="https://agentmods.dev/skills/rootly-ai-labs/rootly-claude-plugin/oncall"><img src="https://agentmods.dev/badge/skills/rootly-ai-labs/rootly-claude-plugin/oncall.svg" alt="Measured on agentmods" 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 | $0.00035 | $0.00417 |
| Opus 5 | $0.00017 | $0.00209 |
| Sonnet 5 | $0.00007 | $0.00083 |
| Haiku 4.5 | $0.00003 | $0.00042 |
Grade A, and why
oncall 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 8d 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.
What it actually says
On-Call Dashboard
You are showing the user a compact on-call dashboard. Gather data and present it concisely.
Workflow
1. Gather Data
Make these calls (in parallel if possible):
mcp__rootly__get_oncall_handoff_summary-- Current and next on-call, shift contextmcp__rootly__get_oncall_shift_metrics-- Workload data (hours, incident count)mcp__rootly__check_oncall_health_risk-- Fatigue and health risk indicators
If $ARGUMENTS contains a team name, pass it to scope the queries.
2. Present Dashboard
## On-Call Dashboard
### Current On-Call
- **Who**: [name]
- **Since**: [start time] ([hours] hours into shift)
- **Incidents this shift**: [count]
### Next On-Call
- **Who**: [name]
- **Handoff**: [time] ([hours] from now)
### Shift Health
- **Hours worked**: [current hours] / [shift length]
- **Fatigue risk**: [LOW / MEDIUM / HIGH]
- **Workload**: [incidents handled] incidents, [pages received] pages
### Recent Incidents This Shift
[List of incidents handled during current shift, if any]
| Severity | Title | Duration | Status |
|----------|-------|----------|--------|
| ... | ... | ... | ... |
Keep the output compact. If any data source returns an error or empty result, omit that section rather than showing empty tables.
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.
- 8d ago First seen · 53 lines · 35 tokens per session scan A 55e998cfeaf1
oncall is a skill published in the GitHub repository Rootly-AI-Labs/rootly-claude-plugin (1 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 35 tokens to every session and 417 once invoked, about $0.0002 per session on Opus 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.
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