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Official agent skill

Planetscale Traffic Control Recommendations

by planetscale in planetscale/skills

Build a safe recommendation plan for PlanetScale Postgres Database Traffic Control budgets and rules without applying them.

OfficialMITAuto-check passedBackend & APIs

Install Planetscale Traffic Control Recommendations

skills CLI
$ npx skills add planetscale/skills --skill planetscale-traffic-control-recommendations -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install planetscale/skills planetscale-traffic-control-recommendations --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/planetscale/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/planetscale-traffic-control-recommendations .claude/skills/planetscale-traffic-control-recommendations && rm -rf skills-src

Use ~/.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/

Facts

Skill name
planetscale-traffic-control-recommendations
GitHub stars
133
Token cost
~1.2k tokens
SKILL.md length
579 words
Files
1
Skills in repo
15
Repo updated
First seen
Licence
MIT

At a glance

Build a safe recommendation plan for PlanetScale Postgres Database Traffic Control budgets and rules without applying them.

  • Works in 4 steps: warn mode first for normal rollout. → Observe warnings and false positives. → Tune tags, fingerprints, and thresholds. → …
  • Backend & APIs work in your project
  • SKILL.md covers Purpose, Preconditions, Candidate traffic slices and Budget modes, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Planetscale Traffic Control Recommendations is an agent skill from planetscale/skills, published by the product's own GitHub organization. Build a safe recommendation plan for PlanetScale Postgres Database Traffic Control budgets and rules without applying them.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Backend & APIs. It works with PlanetScale and PostgreSQL. The repository describes itself as: Skills that help you configure and get the most out of PlanetScale. The licence is MIT.

When your agent uses it

  • Backend & APIs work in your project

Example prompts

  • “/planetscale-traffic-control-recommendations”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. warn mode first for normal rollout.
  2. Observe warnings and false positives.
  3. Tune tags, fingerprints, and thresholds.
  4. Move to enforce only with explicit approval and an emergency rollback path.

What it can do on your machine

Read from SKILL.md and the folder at commit 999045c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Planetscale Traffic Control Recommendations loads about 1.2k tokens when it runs. Until then it costs about 42 tokens; SKILL.md has 579 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~42
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

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 passed

The automated check found no risky patterns in SKILL.md.

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 planetscale/skills at commit 999045c, republished under its MIT licence (© planetscale). 579 words, ~1,172 tokens.

Download SKILL.mdSave it as .claude/skills/planetscale-traffic-control-recommendations/SKILL.md (or your agent's skills folder).
name
planetscale-traffic-control-recommendations
description
Build a safe recommendation plan for PlanetScale Postgres Database Traffic Control budgets and rules without applying them.

Database Traffic Control recommendations

Purpose

For PlanetScale Postgres, recommend Traffic Control budgets and rules that protect critical traffic from runaway queries, traffic spikes, batch jobs, agents, and third-party integrations. Do not create or change budgets without approval.

Preconditions

Run this skill only for PlanetScale Postgres.

Before recommending rules, inspect:

  • Current budgets and rules.
  • Insights query patterns.
  • Current query tags.
  • Application routes and jobs.
  • Known critical paths.
  • Known expensive non-critical paths.
  • Active incidents or recent anomalies.

If query tags are missing, recommend tagging first unless a fingerprint-specific rule is clearly needed for an immediate known offender.

Candidate traffic slices

Look for:

  • Exports.
  • Reports.
  • Search endpoints.
  • Admin dashboards.
  • Backfills.
  • Workers and queues.
  • Webhooks from third-party systems.
  • BI tools.
  • Agent-generated read queries.
  • High-frequency polling.
  • Known expensive query fingerprints.
  • Customer-triggered endpoints with high variance.

Budget modes

Recommend in this order:

  1. warn mode first for normal rollout.
  2. Observe warnings and false positives.
  3. Tune tags, fingerprints, and thresholds.
  4. Move to enforce only with explicit approval and an emergency rollback path.

Do not recommend starting directly in enforce unless there is an active incident and the operator explicitly asks for emergency mitigation.

Rule strategy

Prefer tag-based rules when tags are stable and bounded:

  • source=agent
  • source=bi
  • feature=export
  • feature=report
  • route=/admin/reports
  • job=DailyBackfill
  • service=analytics-worker

Use fingerprint rules when:

  • A specific known query pattern is dangerous.
  • Tagging is missing or unreliable.
  • The query source is hard to attribute.

Use a separate budget for each materially different traffic class.

Do not combine unrelated traffic in one budget because it hides who is consuming the budget.

Suggested default budgets

Use these as recommendation patterns, not as values to apply blindly.

Agent budget

Target: queries tagged source=agent or source=mcp.

Intent: prevent agents from starving application traffic.

Mode: start in warn.

Recommendation: agents should prefer replicas and read-only scopes. Writes require human approval.

Export/reporting budget

Target: feature=export, feature=report, or specific report route/job.

Intent: keep customer-triggered reporting from consuming all database resources.

Mode: start in warn; consider enforce after observation.

Background job budget

Target: worker service, queue, or job tags.

Intent: prevent backfills and retries from starving interactive traffic.

Mode: warn first; enforce only after confirming queue backpressure behavior.

Show full SKILL.md (223 more words)Show less
Third-party integration budget

Target: source=integration, partner-specific bounded tags, or route templates for inbound integration calls.

Intent: isolate unpredictable partner behavior.

Mode: warn first.

Known fingerprint budget

Target: specific expensive query fingerprint.

Intent: contain a known pathological query while code or schema fixes are developed.

Mode: warn first unless emergency.

“Each tag value” strategy

When PlanetScale supports applying a budget separately for each unique value of a selected tag, recommend it for bounded tags such as:

  • application
  • service
  • route when normalized
  • job
  • feature
  • source

Do not recommend it for unbounded tags such as user IDs, request IDs, raw tenant IDs, emails, UUIDs, or raw URLs.

Limits and caveats to include

Every recommendation must explain:

  • Traffic Control limits resource use; it does not replace query tuning.
  • It is not a web application firewall.
  • It does not replace application-level rate limits.
  • Limits are guardrails, not exact guarantees for every failure mode.
  • Bad tags create bad rules.
  • Enforce mode can reject queries and affect application behavior.

Output format

For each proposed budget:

  • Budget name.
  • Target branch.
  • Mode: off, warn, or enforce.
  • Matched traffic slice.
  • Rule type: tag, fingerprint, keyspace, query kind.
  • Proposed tags or fingerprint.
  • Limit rationale.
  • Queries seen in Insights that justify it.
  • Safety risk.
  • Test/observe plan.
  • Rollback plan.
  • Approval requirement.

End with:

“No Traffic Control budgets or rules have been created, updated, deleted, or enforced.”

© planetscale, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in planetscale-traffic-control-recommendations of planetscale/skills.

Open the folder on GitHubat commit 999045c

Compare with similar skills

Planetscale Traffic Control Recommendations 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.

Planetscale Traffic Control Recommendations compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Planetscale Traffic Control Recommendations this skillplanetscale/skills133—~1.2kAutomated safety check: PassMIT
cmux Backend Rulesmanaflow-ai/cmux28k1 repos~682Automated safety check: PassCustom licence
Planetscaleericrisco/rsc-harness167—~2.8kAutomated safety check: PassMIT
PlanetScale Postgres Playbookplanetscale/database-skills7053 repos~1.8kAutomated safety check: PassMIT
PlanetScale Neki Overviewplanetscale/database-skills705—~2.1kAutomated safety check: PassMIT
Expert DatabaseReJeCtAll/ExpertTeam-Codex113—~692Automated safety check: PassMIT

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Works with

Categories

Questions about Planetscale Traffic Control Recommendations

What does Planetscale Traffic Control Recommendations do?

Build a safe recommendation plan for PlanetScale Postgres Database Traffic Control budgets and rules without applying them. Planetscale Traffic Control Recommendations is an agent skill from planetscale/skills, published by the product's own GitHub organization. Build a safe recommendation plan for PlanetScale Postgres Database Traffic Control budgets and rules without applying them.

When should I use Planetscale Traffic Control Recommendations?

Planetscale Traffic Control Recommendations fits situations like: backend & APIs work in your project.

How do I install Planetscale Traffic Control Recommendations in Claude Code?

Run `npx skills add planetscale/skills --skill planetscale-traffic-control-recommendations -a claude-code`. Or copy the skill folder (planetscale-traffic-control-recommendations in planetscale/skills) into .claude/skills/planetscale-traffic-control-recommendations in your project. Claude Code loads it when a task matches its description.

How do I install Planetscale Traffic Control Recommendations in Codex?

Run `npx skills add planetscale/skills --skill planetscale-traffic-control-recommendations -a codex`. Or copy the skill folder (planetscale-traffic-control-recommendations in planetscale/skills) into .agents/skills/planetscale-traffic-control-recommendations in your project. Codex loads it when a task matches its description.

Can I use Planetscale Traffic Control Recommendations 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 planetscale/skills --skill planetscale-traffic-control-recommendations -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/planetscale-traffic-control-recommendations, .gemini/skills/planetscale-traffic-control-recommendations, .github/skills/planetscale-traffic-control-recommendations and .opencode/skills/planetscale-traffic-control-recommendations in your project.

What does Planetscale Traffic Control Recommendations need to run?

SKILL.md names no scripts, command-line tools or credentials: Planetscale Traffic Control Recommendations is instructions for the agent only.

Does Planetscale Traffic Control Recommendations access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Planetscale Traffic Control Recommendations safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Planetscale Traffic Control Recommendations use?

Planetscale Traffic Control Recommendations is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Planetscale Traffic Control Recommendations use?

About 1.2k tokens (SKILL.md is roughly 4.7k 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 Planetscale Traffic Control Recommendations?

Skills that share tags, products or a category with Planetscale Traffic Control Recommendations: cmux Backend Rules (manaflow-ai/cmux, 28k stars), Planetscale (ericrisco/rsc-harness, 167 stars), PlanetScale Postgres Playbook (planetscale/database-skills, 705 stars) and PlanetScale Neki Overview (planetscale/database-skills, 705 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Planetscale Traffic Control Recommendations?

planetscale (a GitHub organization, an official publisher) maintains it in planetscale/skills, which has 133 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on October 7, 2026.

Source: planetscale/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.