SKILLEMALL.ai
GitHub ↗ RU Sign in

BC daytona-seeded-cloud-demo

Daytona seeded cloud demo, demo credentials, Acme Robotics seed. Use when the user asks to spin up, keep running, seed, or prepare an OpenWork Cloud/Den Daytona demo instance.

different-ai/openwork Agent Skills author: different-ai NOASSERTION 1 file body ≈ 1 202 tokens Open the sourcegithub.com↗ analyzed 2 h ago

Daytona seeded cloud demo, demo credentials, Acme Robotics seed.

As a process C 58/100 · Has gaps — weak spots: steps, result and completion, inputs and preconditions

ProcedureSoftware developmentCommerceSecuritytype 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
B
90/100
safety, quality, tests
Safety 60%
98
Quality 40%
79
Run on models
none yet
Process rating
C
58/100
Has gaps
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Secrets in code secret-password-literal SKILL.md:51
      Hard-coded password / key literal (may be an example)
      Password: Open…123!
    • low Secrets in code secret-password-literal SKILL.md:128
      Hard-coded password / key literal (may be an example)
      - Password: `Open…123!`

    Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note edit-residue the text marks something as outdated (lines 80): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 58/100

    • 0Steps. Prose only: no discrete steps
    • 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
    • 100Tools and files. No external tools needed
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1202 tokens
    • 100Running it twice. Mutating operations check current state

    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)
    • +3No numbered steps or checklist
    • +3Output format is not stated: the model decides each time
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +3Description length 175: enough signal without eating the budget
    • +4Structure: 8 headings
    • +4Has examples (12 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.