BC planetscale-cli-skills
PlanetScale CLI (pscale) command reference and workflows. Use for authentication, organizations, SSO, directory sync, teams, members, billing, invoices, payment methods, databases, branches, PostgreSQL point-in-time recovery, branch maintenance, extension catalogs, metrics, insights, diagnostics, SQL, deploy requests, schema migrations, keyspaces, Lookup Vindexes, VTGate sizing, database/deploy/tablet throttlers, aggressive cutover, Postgres switchovers, Traffic Control, PgBouncers, PostgreSQL read-only replicas, Postgres role connection targets, Postgres IP restrictions, Vitess read-only regions, backups, webhooks, audit logs, service tokens, passwords, binary-native agent guidance, Cloudflare D1 imports, and automation. Routes to specialized pscale sub-skills. Triggers on PlanetScale CLI, pscale, pscale --skill, restore point, point-in-time recovery, PITR, pscale maintenance, maintenance window, pscale metrics, performance report, pscale insights, pscale inspect, pscale sql, pscale role get, deploy request, deploy queue, unblock deploy, aggressive cutover, branch maintenance, branch extensions, branch switchover, lookup vindex, traffic control, force cutover, storage readiness, keyspace routing rules, database settings, database branch, VTGate resize, pgbouncer, read-only replica, pscale webhook, database webhook, webhook authorization header, billing, invoice, payment method, backup policy, database diagnostics, organization SSO, directory sync, org member, org team, or pscale import d1.
As a process C 56/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- Shorten the description to 1024 characters.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1515 chars, limit 1024 - note
description-budgetdescription takes 1515 of the ~15000-char shared budget for all skills - note
frontmatter-keyunknown frontmatter key "requirements"
Process rating: all ten parameters 56/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 31 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 18 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3389 tokens
- 100Progress reporting. Reports progress
- low 10 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 1515: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -31 of 4 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +4Structure: 19 headings
- +3Step-by-step instructions: 18 items
- +4Has examples (8 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 49.