SKILLEMALL.ai

AB research-methodology

Plan, conduct, evaluate, and synthesize rigorous research investigations with credible evidence and a traceable method, including source-to-claim closure for media evidence. Do not use this skill for repeated source extraction and durable note orchestration; use `research-and-vault` for that capture workflow, or `ffmpeg` for media operations.

magnus919/agent-skills Agent Skills author: magnus919 MIT 15 files body ≈ 2 096 tokens Open the sourcegithub.com↗ analyzed 26 h ago

Plan, conduct, evaluate, and synthesize rigorous research investigations with credible evidence and a traceable method, including source-to-claim closure for…

As a process B 72/100 · Nearly there — weak spots: inputs and preconditions, failures and branches

AnalyzerResearchtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
96
Run on models
none yet
Process rating
B
72/100
Nearly there
Inputs and preconditions w 11
0
Failures and branches w 10
0
Tools and files w 18
60
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: 14. 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 72/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 100Steps. 23 steps
    • 100Result and completion. Output format and completion criterion are stated
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2096 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress
    • 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
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 344: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 23 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (8 of 9)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 96.