SKILLEMALL.ai

BB comparison-tool-design

Designing side-by-side comparison tools (plan-compare, product-compare, alternative-compare) that help users decide rather than just listing features. Axis selection, default-comparison logic, recommendation discipline. Honest about feature-list-dump (every feature in a row, no decision support), hidden-recommendation (biased comparison pretending to be neutral), and honest-comparison-with-guidance (genuine comparison plus opinionated recommendation) patterns. Triggers on comparison tool, plan compare, product compare, alternative compare, vs page, decision support tool. Also triggers when conversion through comparison stages is poor, when users are abandoning at the comparison step, or when a comparison tool is being scoped for the first time.

rampstackco/claude-skills Agent Skills author: rampstackco 11 files body ≈ 3 908 tokens Open the sourcegithub.com↗ analyzed 7 h ago

Designing side-by-side comparison tools (plan-compare, product-compare, alternative-compare) that help users decide rather than just listing features.

As a process B 76/100 · Nearly there — weak spots: result and completion, running it twice

ProcedureDesigntype and topics are labelled automatically from the skill text
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
B
76/100
Nearly there
Result and completion w 14
0
Running it twice w 4
30
Failures and branches w 10
60
the three weakest of ten parameters · all ten

The same skill appears in 2 more places: claude-skills, claude-skills

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: 11. 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 76/100

    • 0Result and completion. Does not say what the result is
    • 30Running it twice. 1 mutating operations with no state check
    • 60Failures and branches. 2 branches
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 71 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3908 tokens
    • 100Progress reporting. Reports progress
    • low 13 top-level sections: this looks like several domains in one skill

    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
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 754: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 71 items
    • +4Reference files are cited in the instructions (9 of 9)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.