SKILLEMALL.ai

BD auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

The skillemall take

This skill automates VS Code performance and memory profiling with heap snapshots, scenario screenshots, and result comparison. Promises to drive repeatable workflows before analysis.

Three files in the package, but broken references point to missing dependencies. Quality score sits at 74, process score at 44—both mediocre. No critical findings, yet the skill hasn't run on actual models. Platform support is broad: Claude through DeepSeek.

Worth installing if you need a foundation for a custom profiler. As a ready-made tool—no: you'll fix broken links and verify logic yourself.

microsoft/vscode Agent Skills author: microsoft MIT 3 files body ≈ 4 989 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Run agent-driven VS Code performance or memory investigations.

As a process D 44/100 · Unfinished process — References files that are not bundled: scripts/chat-memory-smoke.mts, scripts/chat-session-switch-smoke.mts, scripts/userDataProfile.mts

ProcedureVS CodeGitHubPlaywrightSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
D
44/100
Unfinished process
References files that are not bundled: scripts/chat-memory-smoke.mts, scripts/chat-session-switch-smoke.mts, scripts/userDataProfile.mts
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/chat-memory-smoke.mts
  • warning missing-ref reference to a missing file: scripts/chat-session-switch-smoke.mts
  • warning missing-ref reference to a missing file: scripts/userDataProfile.mts
  • warning missing-ref reference to a missing file: scripts/*.mts
  • warning missing-ref reference to a missing file: scripts/code.sh
  • warning missing-ref reference to a missing file: scripts/code.bat

Process rating: all ten parameters 44/100

Will not run. References files that are not bundled: scripts/chat-memory-smoke.mts, scripts/chat-session-switch-smoke.mts, scripts/userDataProfile.mts
  • 0Tools and files. 6 referenced file(s) missing: scripts/chat-memory-smoke.mts, scripts/chat-session-switch-smoke.mts, scripts/userDataProfile.mts
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 12 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 70Execution cost. Instruction body is 4989 tokens
  • 85Steps. 75 steps, 2 vague phrases
  • 100Failures and branches. 3 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 11 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (5 tags): a typed call is more reliable

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
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 305: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 75 items
  • +4Has examples (11 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.