Official agent skill

Planetscale Safe Orchestrator

by planetscale in planetscale/skills

Master skill that runs the full PlanetScale safe best-practices assessment — inventory, engine review, Insights, Traffic Control, webhooks, schema recommendations, codebase instrumentation, and…

OfficialMITAuto-check passedBackend & APIs

Install Planetscale Safe Orchestrator

skills CLI
$ npx skills add planetscale/skills --skill planetscale-safe-orchestrator -a claude-code

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

GitHub CLI
$ gh skill install planetscale/skills planetscale-safe-orchestrator --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-safe-orchestrator .claude/skills/planetscale-safe-orchestrator && 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-safe-orchestrator
GitHub stars
133
Token cost
~2.9k tokens
SKILL.md length
1,291 words
Files
2
Skills in repo
15
Repo updated
First seen
Licence
MIT

At a glance

Master skill that runs the full PlanetScale safe best-practices assessment — inventory, engine review, Insights, Traffic Control, webhooks, schema recommendations, codebase instrumentation, and…

  • Works in 12 steps: Safety contract → Read-only inventory → Engine safety review → …
  • The user asks to run the full assessment
  • SKILL.md covers Purpose, Non-negotiable safety contract, Before you start and Progress checklist, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Planetscale Safe Orchestrator is an agent skill from planetscale/skills, published by the product's own GitHub organization. Master skill that runs the full PlanetScale safe best-practices assessment — inventory, engine review, Insights, Traffic Control, webhooks, schema recommendations, codebase instrumentation, and agent operating model — then produces a unified recommendations report. Never applies changes without explicit approval. Use when the user asks to run the full assessment, all skills, or PlanetScale best-practices review.

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

It sits in Backend & APIs, covering Webhooks. It works with PlanetScale. 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

  • The user asks to run the full assessment
  • PlanetScale best-practices review

Example prompts

  • “/planetscale-safe-orchestrator”

Workflow steps

12 steps, taken from the step headings in SKILL.md.

  1. Safety contract
  2. Read-only inventory
  3. Engine safety review
  4. Query Insights and tags
  5. Traffic Control (Postgres only)
  6. Webhook automation
  7. Schema recommendations agent loop
  8. Codebase SQLCommenter instrumentation
  9. MCP agent operating model
  10. Best-practices matrix coverage check
  11. Unified customer report
  12. Stop gate

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

    Links to these hosts (documentation or services it may open):

    • planetscale.com

    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 Safe Orchestrator loads about 2.9k tokens when it runs. Until then it costs about 111 tokens; SKILL.md has 1,291 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~111
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k

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). 1,291 words, ~2,902 tokens.

Download SKILL.mdSave it as .claude/skills/planetscale-safe-orchestrator/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
planetscale-safe-orchestrator
description
Master skill that runs the full PlanetScale safe best-practices assessment — inventory, engine review, Insights, Traffic Control, webhooks, schema recommendations, codebase instrumentation, and agent operating model — then produces a unified recommendations report. Never applies changes without explicit approval. Use when the user asks to run the full assessment, all skills, or PlanetScale best-practices review.

PlanetScale safe orchestrator (master skill)

Purpose

Run the complete PlanetScale safe best-practices skill pack end to end. Load and execute each sub-skill in order, accumulate evidence, and produce one unified recommendations report. The first pass is assessment-only.

Non-negotiable safety contract

Default to read-only.

You may inspect configuration, branches, query telemetry, recommendations, webhooks, roles, backups, traffic budgets, and repository code. You must not mutate PlanetScale, the database, the repository, the network posture, credentials, schema, production traffic controls, or automation endpoints without explicit approval of a named change set.

Class C/D/E mutations require approval per ../planetscale-change-gates-and-approval-contract/SKILL.md. When in doubt, stop and add to the proposed change set instead of executing.

One exception exists: if the operator explicitly acknowledges the risk and names a scope per ../planetscale-autonomous-execution-mode/SKILL.md, execution proceeds autonomously under that skill's status and halt discipline instead of stopping for per-change approval. The assessment phases below are identical either way.

Sub-skills are sibling folders next to this skill, referenced by relative path; if a referenced path does not exist, locate the sibling skill whose frontmatter name matches and use it instead.

Ground all CLI and API usage in the official documentation rather than guessing: the docs index is at https://planetscale.com/docs/llms.txt (append .md to any docs URL for the markdown version) and the API reference is https://planetscale.com/docs/openapi.yaml. When a command or endpoint fails, check the docs for the correct form before recording an evidence gap. Tooling and access failures belong in the internal run log, never in the customer report.

Before you start

  1. Read this file completely.

  2. Copy the progress checklist below into your working notes and update it as you go.

  3. Collect inputs (ask or infer from AGENTS.md, MCP context, environment, repository):

    • Organization slug
    • Database name
    • Branch name
    • Engine: PlanetScale Vitess or PlanetScale Postgres
    • Production branch or branches
    • Connected application repository path, if available
    • Application language, framework, ORM, query builder, connection pooling
    • Operator tolerance: report-only, PR-generation, branch-only migrations, or supervised production apply

If inputs are missing, continue with discovery. Do not block on completeness.

Progress checklist

Copy and track:

Master assessment progress:
- [ ] Phase 0: Safety contract loaded
- [ ] Phase 1: Read-only inventory
- [ ] Phase 2: Engine safety review (Vitess OR Postgres)
- [ ] Phase 3: Query Insights and tags
- [ ] Phase 4: Traffic Control (Postgres only — skip for Vitess)
- [ ] Phase 5: Webhook automation
- [ ] Phase 6: Schema recommendations agent loop
- [ ] Phase 7: Codebase SQLCommenter instrumentation
- [ ] Phase 8: MCP agent operating model
- [ ] Phase 9: Best-practices matrix coverage check
- [ ] Phase 10: Unified customer report
- [ ] Phase 11: Change gates verified — stop, no mutations

Interface preference order

  1. PlanetScale MCP insights-only server — autonomous analysis without query execution
  2. Full PlanetScale MCP with read-only scope — schema or limited read queries
  3. pscale CLI and pscale api — structured inventory and exact API state
  4. Repository inspection — codebase analysis and instrumentation recommendations
  5. Direct SQL — read-only introspection only when operator grants database read access

The operator's stated interface constraint overrides this order. If the run is restricted to specific interfaces (for example CLI-only), use those interfaces; this is not a conflict and needs no workaround or note in the customer report beyond the Scope section's interfaces line.

Execution plan

For each phase: read the skill file, follow its instructions, capture its required output, and carry findings forward. Do not skip phases unless the checklist says to skip.

Phase 0 — Safety contract

Read: ../planetscale-change-gates-and-approval-contract/SKILL.md

Internalize operation classes A–E. All later phases operate under Class A unless the operator explicitly approves a named change.

Phase 1 — Read-only inventory

Read and execute: ../planetscale-readonly-inventory/SKILL.md

Deliverables to carry forward:

  • Inventory table with evidence (source, path/command, timestamp, confidence)
  • Missing evidence table
  • Risk flags
  • Confirmed engine (Vitess or Postgres)
  • Branch topology and production branch

If engine is still unknown after inventory, determine it before Phase 2.

Phase 2 — Engine safety review

Run exactly one:

EngineSkill file
Vitess../planetscale-vitess-safety-review/SKILL.md
Postgres../planetscale-postgres-safety-review/SKILL.md

Deliverables: engine-specific safety gaps, workflow gaps, and proposed changes requiring approval.

Phase 3 — Query Insights and tags

Read and execute: ../planetscale-query-insights-and-tags/SKILL.md

Deliverables: query risk table, tag coverage table, bad/high-cardinality tags, recommended tag schema, candidate Traffic Control slices, candidate schema and code changes.

Phase 4 — Traffic Control (Postgres only)

Skip this phase for Vitess. Mark checklist item complete with note "N/A — Vitess".

For Postgres, read and execute: ../planetscale-traffic-control-recommendations/SKILL.md

Deliverables: proposed budgets (name, mode, traffic slice, rule type, limits rationale, test/rollback plan).

If query tags are weak, note "tagging first" per that skill and defer enforce-mode recommendations.

Phase 5 — Webhook automation

Read and execute: ../planetscale-webhook-automation-recommendations/SKILL.md

Deliverables: webhook inventory, missing subscriptions, destination quality review, automation opportunities, unsafe automation risks.

Phase 6 — Schema recommendations agent loop

Read and execute: ../planetscale-schema-recommendations-agent-loop/SKILL.md

Deliverables: per-recommendation triage (type, severity, evidence, safe implementation path, validation/rollback plan).

Phase 7 — Codebase SQLCommenter instrumentation

Read and execute: ../planetscale-codebase-sqlcommenter-instrumentation/SKILL.md

Skip only if no repository is available. Note "no repository reviewed" in the final report.

Deliverables: detected stack, current tagging state, recommended package/path, proposed tag schema, files likely to change.

Phase 8 — MCP agent operating model

Read and execute: ../planetscale-mcp-agent-operating-model/SKILL.md

Deliverables: recommended MCP server choice, AGENTS.md additions, allowed/disallowed autonomous work, proposed agent loops.

Show full SKILL.md (535 more words)Show less
Phase 9 — Best-practices matrix coverage check

Read and execute: ../planetscale-best-practices-matrix/SKILL.md

Cross-check every matrix item against Phases 1–8 findings. For each item record:

  • Applies: yes / no / unknown
  • Current state
  • Gap
  • Recommendation ID (see ID scheme below)
  • Approval requirement

Fill gaps: if a matrix item was not covered by earlier phases, gather missing evidence now (read-only only).

Phase 10 — Unified customer report

Read and execute: ../planetscale-customer-report-template/SKILL.md

Synthesize all phase deliverables into one report. Do not dump raw phase outputs — merge, deduplicate, and rank by impact.

Recommendation ID scheme
PrefixDomain
OBS-*Insights and query tags
VIT-*Vitess safety and deploy workflow
PG-*Postgres roles, pg_strict, Traffic Control, PITR, network
WEB-*Webhooks and automation
APP-*Repository instrumentation
AGENT-*MCP and agent workflows

Assign stable IDs across the report. Reference the same IDs in the proposed change set.

Ranking guidance

Order recommendations by:

  1. Production safety and availability risk (highest first)
  2. Observability gaps blocking diagnosis or Traffic Control
  3. Automation that reduces mean time to detect/respond
  4. Performance and schema improvements with clear evidence
Phase 11 — Stop gate

Re-read: ../planetscale-change-gates-and-approval-contract/SKILL.md

Verify:

  • No Class C/D/E actions were taken
  • Every proposed mutation has an ID, target, interface, effect, risk, rollback, and test plan
  • Report ends with the required final sentence

Stop. Do not apply changes — unless a valid autonomous-mode acknowledgment (per ../planetscale-autonomous-execution-mode/SKILL.md) accompanied the request, in which case present the report and the execution plan, then continue directly into execution under that skill.

Required final report structure

Use the template in ../planetscale-customer-report-template/SKILL.md. Minimum sections:

  1. Scope — org, database, branches, engine, repository, interfaces, time window; changes applied: none

  2. Executive summary — 3–7 bullets on highest-risk gaps and highest-value improvements

  3. Current state — database topology, safety workflow, observability, automation, repository instrumentation (with evidence)

  4. Recommendations — ranked table with IDs, target, benefit, risk, approval needed, test first, evidence

  5. Proposed change set requiring approval — every Class C/D item with exact change, interface, rollback, production impact

  6. Changes intentionally not applied — explicit list of what was not changed

  7. Evidence appendix — source, command/path, timestamp, value, notes

  8. Final required sentence (verbatim):

    No changes have been applied. Approve specific change IDs before any mutation.

Handling partial runs

If MCP, CLI, API, or repository access is unavailable:

  • Continue with available interfaces
  • Record missing evidence in the report
  • Lower confidence on affected recommendations
  • Do not invent state — mark unknown

After the report

Two paths into execution:

Per-change approval. The operator approves specific change IDs:

  1. Re-read ../planetscale-change-gates-and-approval-contract/SKILL.md
  2. Execute only the named IDs
  3. Produce the post-execution report defined in that skill

Autonomous mode. The operator explicitly acknowledges the risk with a named scope ("I accept the risk — apply all report recommendations to storefront-demo, production included"):

  1. Read ../planetscale-autonomous-execution-mode/SKILL.md and validate the acknowledgment against its activation contract
  2. Present the dependency-ordered execution plan, then execute end to end with continuous status, per-step verification, and the halt rules from that skill
  3. Produce the run summary and run log

Never interpret "apply best practices", "fix everything", or "go ahead" as either approval or risk acknowledgment.

Quick invocation

When the user says "run the full assessment" or "run all PlanetScale best-practices skills":

  1. Load this skill
  2. Run Phases 0–11 in order
  3. Return the unified report
  4. Stop

© 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

SKILL.md and 1 other file in planetscale-safe-orchestrator of planetscale/skills.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit 999045c

Compare with similar skills

Planetscale Safe Orchestrator 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 Safe Orchestrator compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Planetscale Safe Orchestrator this skillplanetscale/skills133—~2.9kAutomated safety check: PassMIT
cmux Backend Rulesmanaflow-ai/cmux28k1 repos~682Automated safety check: PassCustom licence
Novu Design Workflownovuhq/novu40k—~2.6kAutomated safety check: PassCustom licence
Stripe Appsfossasia/eventyay1.7k2 repos~3.6kAutomated safety check: PassApache-2.0
Golivemikehasa/golive-skill1.2k—~13kAutomated safety check: NotesMIT
Dingtalk Messageagentscope-ai/ReMe3.6k—~1.6kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Planetscale Safe Orchestrator

What does Planetscale Safe Orchestrator do?

Master skill that runs the full PlanetScale safe best-practices assessment — inventory, engine review, Insights, Traffic Control, webhooks, schema recommendations, codebase instrumentation, and…. Planetscale Safe Orchestrator is an agent skill from planetscale/skills, published by the product's own GitHub organization. Master skill that runs the full PlanetScale safe best-practices assessment — inventory, engine review, Insights, Traffic Control, webhooks, schema recommendations, codebase instrumentation, and agent operating model — then produces a unified recommendations report.

When should I use Planetscale Safe Orchestrator?

Planetscale Safe Orchestrator fits situations like: the user asks to run the full assessment; planetScale best-practices review.

How do I install Planetscale Safe Orchestrator in Claude Code?

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

How do I install Planetscale Safe Orchestrator in Codex?

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

Can I use Planetscale Safe Orchestrator 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-safe-orchestrator -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-safe-orchestrator, .gemini/skills/planetscale-safe-orchestrator, .github/skills/planetscale-safe-orchestrator and .opencode/skills/planetscale-safe-orchestrator in your project.

What does Planetscale Safe Orchestrator need to run?

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

Does Planetscale Safe Orchestrator access the network?

SKILL.md names 1 domain. As links in the text: planetscale.com. This is read from the text; nothing was executed.

Is Planetscale Safe Orchestrator 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 Safe Orchestrator use?

Planetscale Safe Orchestrator 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 Safe Orchestrator use?

About 2.9k tokens (SKILL.md is roughly 12k 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 Safe Orchestrator?

Skills that share tags, products or a category with Planetscale Safe Orchestrator: cmux Backend Rules (manaflow-ai/cmux, 28k stars), Novu Design Workflow (novuhq/novu, 40k stars), Stripe Apps (fossasia/eventyay, 1.7k stars) and Golive (mikehasa/golive-skill, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Planetscale Safe Orchestrator?

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.