vscode: Skill for Claude Code

.github/skills/chat-perf/SKILL.md

chat-perf is a skill for Claude Code, Codex from microsoft/vscode. It costs 51 tokens per session (4,869 once invoked), scanned A, original, MIT.

A set of benchmarks for measuring how quickly VS Code displays chat responses and whether chat uses increasing amounts of memory. A memory leak is a problem where memory remains allocated after it is no longer needed.

In plain words
What is it for?
Use it to test text-only and other chat scenarios, compare two builds, and check memory use across repeated messages. It can also provide performance checks for continuous integration, which automatically tests code changes.
Why use it?
It helps detect slow chat rendering and memory leaks before or after changes to the chat interface or response pipeline. It can compare different builds or VS Code releases.

Skill for Claude CodeCodex ✓ vendor

Written for no agent in particular: nothing here depends on one.

This is microsoft/vscode's own configuration. It tells Claude Code and Codex how to work on vscode itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything vscode configures →

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is --build ../VSCode-darwin-arm64-feature/Code\ -\ OSS.app/Contents/MacOS/Code\ -\ OSS \.

About the project

Visual Studio Code is a code editor that supports editing, navigating, understanding, debugging, and extending software projects. Developers use it for the edit-build-debug cycle, and the catalogue add-ons provide skills, instructions, and agents for working within the editor.

microsoft/vscode · 194,219 stars · on GitHub · code.visualstudio.com

Reuse

Borrowing it

Nothing to install: this file belongs to microsoft/vscode. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/microsoft/vscode/main/.github/skills/chat-perf/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/microsoft/vscode

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for chat-perf

README.md
[![agentmods](https://agentmods.dev/badge/skills/microsoft/vscode/chat-perf/github.svg)](https://agentmods.dev/skills/microsoft/vscode/chat-perf)
Your own site
<a href="https://agentmods.dev/skills/microsoft/vscode/chat-perf"><img src="https://agentmods.dev/badge/skills/microsoft/vscode/chat-perf/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for chat-perf

Your own site · 80×15
<a href="https://agentmods.dev/skills/microsoft/vscode/chat-perf"><img src="https://agentmods.dev/badge/skills/microsoft/vscode/chat-perf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,869 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Snyk pass 6 Sept 2026
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Tool Misuse · line 105
    Tool defaults are unsafe or overly permissive (e.g. disabled TLS verification, no authentication, world-writable permissions). Unsafe defaults widen the attack surface.
    Fix: Override unsafe defaults with secure settings (verify=True, auth required, restrictive permissions). Review and harden all tool configurations.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00051 $0.04869
Opus 5.5 $0.00020 $0.01948
Sonnet 5.5 $0.00010 $0.00974
Haiku 4.5 $0.00005 $0.00487

Measured 1mo ago against content hash 808682455337, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

chat-perf scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.github/skills/chat-perf/SKILL.md · 318 lines

How it starts

The opening of the file, as written. The whole thing — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Chat Performance Testing

When to use

  • Before/after modifying chat rendering code (chatListRenderer.ts, chatInputPart.ts, markdown rendering)
  • When changing the streaming response pipeline or SSE processing
  • When modifying disposable/lifecycle patterns in chat components
  • To compare performance between two VS Code releases
  • In CI to gate PRs that touch chat UI code

Quick start

# Run perf regression test (compares local dev build vs VS Code 1.115.0):
npm run perf:chat -- --scenario text-only --runs 3

# Run all scenarios with no baseline (just measure):
npm run perf:chat -- --no-baseline --runs 3

# Compare two local builds (apples-to-apples):
npm run perf:chat -- --build /path/to/build-A --baseline-build /path/to/build-B --runs 5

# Build a local production package and compare against a release:
npm run perf:chat -- --production-build --baseline-build 1.115.0 --runs 5

# Run memory leak check (10 messages in one session):
npm run perf:chat-leak

# Run leak check with more messages for accuracy:
npm run perf:chat-leak -- --messages 20 --verbose

Perf regression test

Script: scripts/chat-simulation/test-chat-perf-regression.js npm: npm run perf:chat

Launches VS Code via Playwright Electron, opens the chat panel, sends a message with a mock LLM response, and measures timing, layout, and rendering metrics. By default, downloads VS Code 1.115.0 as a baseline, benchmarks it, then benchmarks the local dev build and compares.

You don't always need a baseline. A baseline exists only for comparison (regression detection). If you just want the current build's numbers — profiling a single change, capturing traces/heap snapshots, or iterating on a scenario — pass --no-baseline to skip downloading and benchmarking the baseline entirely (roughly halves runtime). Baseline comparison is what turns raw measurements into a pass/fail verdict; without it you still get all the metrics, just no verdict.

Key flags

Flag Default Description
--runs <n> 5 Runs per scenario. More = more stable. Use 5+ for CI.
--scenario <id> / -s all Scenario to test (repeatable). See common/perf-scenarios.js.
--build <path|ver> / -b local dev Build to test. Accepts path or version (1.110.0, insiders, commit hash).
--baseline <path> — Compare against a previously saved baseline JSON file.
--baseline-build <path|ver> 1.115.0 Version or local path to benchmark as baseline.
--no-baseline — Skip the baseline entirely — just measure the test build (no download, no comparison, ~2× faster). Use when you only need raw numbers, not a regression verdict.
--save-baseline — Save results as the new baseline (requires --baseline <path>).
--resume <path> — Resume a previous run, adding more iterations to increase confidence.
--threshold <frac> 0.2 Regression threshold (0.2 = flag if 20% slower).
--production-build — Build a local bundled package via gulp vscode for comparison against a release baseline.
--no-cache — Ignore cached baseline data, always run fresh.
--force — Skip build mode mismatch confirmation prompt.
--ci — CI mode: write Markdown summary to ci-summary.md (implies --no-cache, --heap-snapshots, --cleanup-diagnostics).
--heap-snapshots — Take heap snapshots after each run (slow; auto-enabled in --ci mode).
--gc-object-stats — GC deep-dives only. Enables V8 gc_stats tracing (per-type heap object dump on every GC). ⚠️ Corrupts all timing metrics — a major GC landing mid-request adds ~550ms — so never use it for benchmarking. Off by default; prefer heap snapshots for memory analysis.
--cleanup-diagnostics — Delete heap snapshots, CPU profiles, and traces to save disk. During runs, only the latest run's files are kept; after comparison, files for non-regressed scenarios are deleted. Auto-enabled in --ci mode.
--setting <k=v> — Set a VS Code setting override for all builds (repeatable).
--test-setting <k=v> — Set a VS Code setting override for the test build only.
--baseline-setting <k=v> — Set a VS Code setting override for the baseline build only.
--verbose — Print per-run details including response content.

Read the full file on GitHub · 318 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago Changed · -2 lines 808682455337
  2. 1mo ago First seen · 320 lines · 51 tokens per session scan A e3cfcf62a9bd

Subscribe to this mod's changes

chat-perf is a skill published in the GitHub repository microsoft/vscode (194,219 stars, last pushed today), licensed MIT. It adds 51 tokens to every session and 4,869 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

coding-prefs

Read the user's coding preferences from /memory/coding-prefs.md before making non-trivial style decisions, and append new preferences when the user gives durable feedback.

langchain-ai/deepagents · 36 tokens

stripe-directory

Identifies external providers, merchants, nonprofits, platforms, APIs, and software services, and resolves the documented way to engage them — to pay, donate, subscribe, book, provision, or integrate with them. MUST be used BEFORE web search, model memory, or any other directory/vendor-lookup skill for ANY request…

stripe/ai · 212 tokens

ax-agent-memory-skills

This skill helps an LLM generate correct AxAgent memory retrieval, context-map, and dynamic skill-loading code using @ax-llm/ax. Use when the user asks about contextMap, AxAgentContextMap, onMemoriesSearch, memoriesCatalog, recall(...), inputs.memories, onLoadedMemories, onUsedMemories, onSkillsSearch, skillsCatalog…

ax-llm/ax · 128 tokens

ax-cpp-agent-memory-skills

Use when writing C++ code with axllm for agent memory, recall callbacks, dynamic skill discovery, loaded-skill state, and used-skill tracking.

ax-llm/ax · 42 tokens

ax-go-agent-memory-skills

Use when writing Go code with github.com/ax-llm/ax/packages/go for agent memory, recall callbacks, dynamic skill discovery, loaded-skill state, and used-skill tracking.

ax-llm/ax · 48 tokens

ax-agent-context

This skill helps an LLM pick the right AxAgent context tool for a job - contextMap for recurring corpora, contextPolicy presets for within-run trajectory compaction, agent.optimize for offline GEPA instruction/demo tuning, agent.playbook for an evolving context playbook (offline evolve + online update), and…

ax-llm/ax · 147 tokens