SKILLEMALL.ai

AC gap-analysis

Analyze gaps by comparing a defined current state with a justified target state, characterizing causes and uncertainty, prioritizing actionable interventions, and producing traceable matrices, roadmaps, and decision records. Use for capability, process, compliance, readiness, maturity, operating-model, or research-evidence gaps. Do not use for a vague list of problems, a standalone root-cause analysis, a generic SWOT, or legal or audit certification advice without a governing standard and qualified owner.

magnus919/agent-skills Agent Skills author: magnus919 MIT 14 files · 1 script body ≈ 1 340 tokens Open the sourcegithub.com↗ analyzed 25 h ago

Analyze gaps by comparing a defined current state with a justified target state, characterizing causes and uncertainty, prioritizing actionable interventions…

As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerSecurityOperations and projectsSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
C
63/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 13. 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 63/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 40Result and completion. Does not say what the result is
    • 50When it triggers. No condition that starts the skill
    • 100Tools and files. No external tools needed
    • 100Steps. 9 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1340 tokens
    • 100Running it twice. No mutating operations
    • low No test case covers injection arriving through data

    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
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 510: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 9 items
    • +4Reference files are cited in the instructions (5 of 5)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.