AC Machine Learning Roadmap
A roadmap connecting many of the most important concepts in machine learning, how to learn them and machine learning roadmap, python, data, data-science.
As a process C 54/100 · Has gaps — weak spots: when it triggers, failures and branches, consistency
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 · 0
✓ No critical or high findings
Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens)
Process rating: all ten parameters 54/100
- 0Failures and branches. Linear process with no failure handling
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 40Consistency. Frontmatter name (Machine Learning Roadmap) differs from the folder (ml-roadmap)
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 14 steps, 1 vague phrases
- 100Execution cost. Instruction body is 1073 tokens
- 100Progress reporting. Reports progress
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)
- -31 of 1 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 153: enough signal without eating the budget
- +4Structure: 7 headings
- +3Step-by-step instructions: 14 items
- +3Output format is stated explicitly
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.
External checks
ClawHub: clean
This is a simple local command-line logging tool for ML roadmap notes and content drafts, with plaintext history disclosed and no evidence of network access, credential use, hidden execution, or destructive behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026