SKILLEMALL.ai

CB start-4-1

4.1 Setup. Use when the student types /start-4-1.

The skillemall take

The skill triggers on /start-4-1 command and initializes module 4 of a project management course. One file, 1641 tokens of instructions. Safety score 95, quality 81, process 66. One medium-level finding that doesn't block execution. References intact, no lint errors.

This means the skill will run across all major platforms (Claude, Cursor, DeepSeek, etc.), but the execution workflow has some rough edges—likely in logic flow or documentation clarity. Fine for course onboarding, just verify the student lands in the right place.

carlvellotti/claude-code-pm-course Claude Code author: carlvellotti 1 file body ≈ 1 641 tokens Open the sourcegithub.com↗ analyzed 5 d ago

4.1 Setup. Use when the student types /start-4-1.

As a process B 66/100 · Nearly there — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
89/100
safety, quality, tests
Safety 60%
95
Quality 40%
81
Run on models
none yet
Process rating
B
66/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • medium Broad scope meta-broad-allowed-tools SKILL.md:1
      Broad tool permissions pre-approved: Bash
      allowed-tools: Read Write Bash AskUserQuestion

    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 66/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 14 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 20 steps
    • 100Failures and branches. 4 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1641 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 49: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 20 items
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.