SKILLEMALL.ai

BD github-copilot-upgrader

Use this to update the Github Copilot CLI/SDK

The skillemall take

Promises to update GitHub Copilot CLI and SDK via Microsoft source integration. Grade B, no critical issues, but code quality at 76 is below par. Single file, no scripts. Never ran in sandbox, no model testing. Supports twelve platforms including Claude, Cursor, and DeepSeek.

Might help if you update Copilot frequently. Missing sandbox and model validation means real-world behavior is a blind spot. Install cautiously—test on a non-production environment first.

microsoft/vscode Agent Skills author: microsoft MIT 1 file body ≈ 815 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Use this to update the Github Copilot CLI/SDK

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationGitHubSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
D
43/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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    • note edit-residue the text marks something as outdated (lines 68): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 43/100

    • 0Result and completion. Does not say what the result is
    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 7 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 100Steps. 25 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 815 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 45: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -5TODO / placeholder text left in the skill
    • +1No license
    • +2Single-language instructions
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 25 items
    • +4Has examples (2 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.