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BF monte-carlo-monitoring-advisor

Analyze data coverage, create monitors for warehouse tables and AI agents. Covers coverage gaps, use-case analysis, data monitor creation, and agent observability.

sickn33/agentic-awesome-skills Agent Skills author: sickn33 MIT 1 file body ≈ 5 019 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Analyze data coverage, create monitors for warehouse tables and AI agents.

As a process F 53/100 · Will not run — References files that are not bundled: references/data-monitor-creation.md, references/agent-monitor-creation.md, references/data-*.md

AnalyzerAI and agentsInfrastructuretype 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
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
60
Run on models
none yet
Process rating
F
53/100
Will not run
References files that are not bundled: references/data-monitor-creation.md, references/agent-monitor-creation.md, references/data-*.md
Tools and files w 18
0
Result and completion w 14
0
When it triggers w 12
20
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: monte-carlo-monitoring-advisor (sickn33/agentic-awesome-skills)

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  2. The text references files that are not there: add them or drop the references.
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 · 0

✓ No critical or high findings

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

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5019 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: references/data-monitor-creation.md
  • warning missing-ref reference to a missing file: references/agent-monitor-creation.md
  • warning missing-ref reference to a missing file: references/data-*.md
  • warning missing-ref reference to a missing file: references/agent-*.md
  • note frontmatter-key unknown frontmatter key "risk"
  • note frontmatter-key unknown frontmatter key "source"
  • note frontmatter-key unknown frontmatter key "source_repo"
  • note frontmatter-key unknown frontmatter key "source_type"
  • note frontmatter-key unknown frontmatter key "date_added"
  • note frontmatter-key unknown frontmatter key "license_source"

Process rating: all ten parameters 53/100

Will not run. References files that are not bundled: references/data-monitor-creation.md, references/agent-monitor-creation.md, references/data-*.md
  • 0Tools and files. 4 referenced file(s) missing: references/data-monitor-creation.md, references/agent-monitor-creation.md, references/data-*.md
  • 0Result and completion. Does not say what the result is
  • 20When it triggers. No condition that starts the skill
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5019 tokens
  • 100Steps. 84 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 14 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (4 tags): a typed call is more reliable

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)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 163: enough signal without eating the budget
  • +4Structure: 28 headings
  • +3Step-by-step instructions: 84 items
  • +4Has examples (1 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.