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BC docker-compose-monitoring-stack

Deploys a complete monitoring stack with Prometheus, Grafana, and Node Exporter using Docker Compose.

andersonamaral2/Claude-Code-to-Deep-Agents-Skills-Converter Agent Skills author: andersonamaral2 MIT 1 file body ≈ 2 506 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Deploys a complete monitoring stack with Prometheus, Grafana, and Node Exporter using Docker Compose.

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

GeneratorDockerInfrastructuretype 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%
97
Quality 40%
79
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
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 · 3

    ✓ No critical or high findings

    Medium and low: 3
    • low Exfiltration read-dotenv SKILL.md:98
      Reads a .env file
      set -a && source .env && set +a
    • low Exfiltration read-dotenv SKILL.md:264
      Reads a .env file
      set -a && source .env && set +a
    • low Exfiltration read-dotenv SKILL.md:395
      Reads a .env file
      set -a && source .env && set +a

    Files scanned: 1. 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
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 29 mutating operations with no state check
    • 40Consistency. Frontmatter name (docker-compose-monitoring-stack) differs from the folder (deep-agents-output-2)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 25 steps
    • 100Execution cost. Instruction body is 2506 tokens

    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 101: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +4Structure: 31 headings
    • +3Step-by-step instructions: 25 items
    • +4Has examples (29 code blocks)

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