SKILLEMALL.ai

AB release-analysis

Analyze an upstream product, dependency, or platform release for downstream impact on the current repo. Use when the user gives a package or repo name such as `openclaw` or `GOG-CLI`, or asks about release notes, changelogs, tags, dependency bumps, or upstream announcements. Resolve the GitHub repository, read the latest release or tag notes, and assess breaking changes, redundant features, new opportunities, test needs, and recommended follow-up work for a wrapper or integration product such as AlphaClaw relative to OpenClaw.

chrysb/alphaclaw Agent Skills author: chrysb 1 file body ≈ 1 686 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Analyze an upstream product, dependency, or platform release for downstream impact on the current repo.

As a process B 66/100 · Nearly there — weak spots: inputs and preconditions, failures and branches, progress reporting

AnalyzerGitHubSoftware developmentWriting and documentsMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
B
66/100
Nearly there
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
    • 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: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note edit-residue the text marks something as outdated (lines 86): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 66/100

    • 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
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 85Steps. 93 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1686 tokens
    • 100Running it twice. Mutating operations check current state
    • low 11 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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 532: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 93 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.