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AC supabase

Use this skill when developing applications with Supabase, running the Supabase CLI, designing migrations and RLS policies, testing database behavior, generating client types, deploying the official self-hosted Docker stack, or administering its Postgres, Auth, Storage, Realtime, Functions, API gateway, backups, upgrades, and security. Use it for managed and self-hosted projects. Do not use for generic PostgreSQL work with no Supabase services or conventions.

magnus919/agent-skills Agent Skills author: magnus919 MIT 12 files body ≈ 1 981 tokens Open the sourcegithub.com↗ analyzed 27 h ago

Use this skill when developing applications with Supabase, running the Supabase CLI, designing migrations and RLS policies, testing database behavior…

As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationDockerSupabasePostgreSQLInfrastructuretype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
99
Quality 40%
91
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Exfiltration read-dotenv references/agent-evals.md:34
      Reads a .env file (documentation of a security skill)
      cp .env.example .env   # add the provider key(s) agent-backed runs need
      security skill

    Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 57/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 17 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 85Steps. 14 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1981 tokens
    • low No test case covers injection arriving through data

    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
    • +3Output format is not stated: the model decides each time
    • -2localhost URLs: will not work for another user
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 463: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 14 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (9 of 9)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.