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 agentmods add skills/render-oss/render-plugin-claude-code/render-scalingnpx skills add render-oss/render-plugin-claude-code --skill render-scalinggit clone --depth 1 https://github.com/render-oss/render-plugin-claude-codeWhat 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 | $0.00065 | $0.01171 |
| Opus 5 | $0.00032 | $0.00585 |
| Sonnet 5 | $0.00013 | $0.00234 |
| Haiku 4.5 | $0.00006 | $0.00117 |
Grade A, and why
render-scaling 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 2d 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Render Scaling
This skill covers how to scale Web Services, Private Services, and Background Workers on Render: manual instance counts, Professional+ autoscaling, plan (instance type) choices, and platform limits. Deeper tables and tuning guidance live under references/.
When to Use
- Setting or changing instance count (Dashboard, CLI, API, or Blueprint)
- Configuring autoscaling (min/max, CPU and memory targets)
- Choosing vertical (plan) vs horizontal (more instances) scaling
- Understanding constraints (disks, static sites, cron/workflows, 100-instance cap)
- Cost implications of multi-instance and per-second billing
- Blueprint fields:
numInstances,scaling,plan
Manual Scaling
- Set instance count from 1 to 100 via the Dashboard, CLI, or API.
- All instances share the same instance type (plan); you cannot mix plans on one service.
- Changes apply immediately: Render provisions new instances and deprovisions excess capacity as needed.
Autoscaling
- Available on Professional and higher workspaces only.
- Configure minimum and maximum instances and targets for CPU and/or memory utilization (1–90% each).
- At least one metric must be enabled (CPU or memory). If both CPU and memory autoscaling toggles are off, autoscaling is disabled.
- If both manual instance settings and autoscaling are configured, autoscaling wins—manual count does not override the scaling policy in effect.
Autoscaling Formula
Render computes a candidate instance count from utilization vs target:
new_instances = ceil(current_instances * (current_utilization / target_utilization))
- When both CPU and memory targets are set, the platform uses the larger of the two
new_instancesvalues (the more conservative scale-out).
Scaling Constraints
| Constraint | Behavior |
|---|---|
| Per service | Maximum 100 instances |
| Persistent disk | Cannot scale to multiple instances—single instance only |
| Static sites | Not scalable (served by CDN) |
| Cron jobs & Workflows | Scaling model does not apply (different execution model) |
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.
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.
- 2d ago First seen · 123 lines · 65 tokens per session scan A d9741ad68172
render-scaling is a skill published in the GitHub repository render-oss/render-plugin-claude-code (0 stars, last pushed 13d ago), licensed MIT. It adds 65 tokens to every session and 1,171 once invoked, about $0.0003 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…