Kubeshark Installer
kubeshark/kubeshark
Installs and configures Kubeshark on a Kubernetes cluster, choosing between the quick CLI path and a Helm install with custom values.
A skill your agent uses when writing the objectivefunction= passed to Search().
$ npx skills add NVIDIA/CompileIQ --skill compileiq-author-objective -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA/CompileIQ compileiq-author-objective --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/NVIDIA/CompileIQ.git skills-src && mkdir -p .claude/skills && cp -r skills-src/agent-skills/compileiq-author-objective .claude/skills/compileiq-author-objective && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "compileiq-author-objective" agent skill from https://github.com/NVIDIA/CompileIQ/tree/main/agent-skills/compileiq-author-objective into .claude/skills/compileiq-author-objective/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "compileiq-author-objective", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/NVIDIA/CompileIQ/tree/main/agent-skills/compileiq-author-objectiveType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add NVIDIA/CompileIQ --skill compileiq-author-objective -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA/CompileIQ compileiq-author-objective --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/CompileIQ.git skills-src && mkdir -p .agents/skills && cp -r skills-src/agent-skills/compileiq-author-objective .agents/skills/compileiq-author-objective && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "compileiq-author-objective" agent skill from https://github.com/NVIDIA/CompileIQ/tree/main/agent-skills/compileiq-author-objective into .agents/skills/compileiq-author-objective/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "compileiq-author-objective", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA/CompileIQ --skill compileiq-author-objective -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA/CompileIQ compileiq-author-objective --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/CompileIQ.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/agent-skills/compileiq-author-objective .cursor/skills/compileiq-author-objective && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "compileiq-author-objective" agent skill from https://github.com/NVIDIA/CompileIQ/tree/main/agent-skills/compileiq-author-objective into .cursor/skills/compileiq-author-objective/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "compileiq-author-objective", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/NVIDIA/CompileIQ.git --path agent-skills/compileiq-author-objective--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add NVIDIA/CompileIQ --skill compileiq-author-objective -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA/CompileIQ compileiq-author-objective --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/CompileIQ.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/agent-skills/compileiq-author-objective .gemini/skills/compileiq-author-objective && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "compileiq-author-objective" agent skill from https://github.com/NVIDIA/CompileIQ/tree/main/agent-skills/compileiq-author-objective into .gemini/skills/compileiq-author-objective/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "compileiq-author-objective", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install NVIDIA/CompileIQ compileiq-author-objectiveInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add NVIDIA/CompileIQ --skill compileiq-author-objective -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/NVIDIA/CompileIQ.git skills-src && mkdir -p .github/skills && cp -r skills-src/agent-skills/compileiq-author-objective .github/skills/compileiq-author-objective && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "compileiq-author-objective" agent skill from https://github.com/NVIDIA/CompileIQ/tree/main/agent-skills/compileiq-author-objective into .github/skills/compileiq-author-objective/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "compileiq-author-objective", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA/CompileIQ --skill compileiq-author-objective -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install NVIDIA/CompileIQ compileiq-author-objective --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/CompileIQ.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/agent-skills/compileiq-author-objective .opencode/skills/compileiq-author-objective && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "compileiq-author-objective" agent skill from https://github.com/NVIDIA/CompileIQ/tree/main/agent-skills/compileiq-author-objective into .opencode/skills/compileiq-author-objective/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "compileiq-author-objective", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
compileiq-author-objectiveA skill your agent uses when writing the objectivefunction= passed to Search().
Compileiq Author Objective is an agent skill from NVIDIA/CompileIQ, published by the product's own GitHub organization. Use when writing the objectivefunction= passed to Search(). Covers the two legal signatures (compiler-only str vs mixed list), the baseline-knockout branch, per-eval cache busting, framework-specific --apply-controls injection (raw PTXAS, NVCC, Triton, Helion, cuTeDSL/FA4, FlashInfer), correctness-before-timing, INVALIDSCORE handling, and the Debug-pack O0/O3 ACF-injection canary that must pass before launching a search. Triggers on "objective function", "apply-controls", "INVALIDSCORE", "savecompilerconfig"…
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/templates.md`).
It sits in DevOps & Cloud, covering Deployment. The repository describes itself as: An Optimizer for Nvidia Compilers. The licence is Apache-2.0.
Read from SKILL.md and the folder at commit 743aca4. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
BashReadFrom allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
helionlang.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Compileiq Author Objective loads about 2.3k tokens when it runs, and up to ~5.4k if it reads all its reference files. Until then it costs about 162 tokens; SKILL.md has 659 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
allowed-tools: Bash, ReadAutomated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from NVIDIA/CompileIQ at commit 743aca4, republished under its Apache-2.0 licence (© NVIDIA). 659 words, ~2,268 tokens.
.claude/skills/compileiq-author-objective/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.The objective function is where ~80% of CompileIQ user errors happen. This
skill tells you the exact shape it must have for current CompileIQ, how to
inject --apply-controls for each supported compile path, and how to verify
the whole pipeline works before paying for a full search.
For paste-ready full-file templates per framework, see
references/templates.md.
bytes.fromhex(config_blob) pattern.Shape of search_space= | Objective signature | What config is |
|---|---|---|
Single provider, e.g. PtxasSearchSpace() | def objective(config: str) -> float | A hex string. Pass it straight to save_compiler_config(acf_path, config). |
List, e.g. [{"k": ss.choice(...)}, PtxasSearchSpace()] | def objective(mixed: list) -> float | A list of the same length. Unpack: user_space, ptxas_config = mixed. |
Mixed-space results keep the same list shape in best["params"]. Unpack it
before saving the ACF, for example:
user_space, ptxas_config = best["params"]. (Pattern reference:
examples/compilers/triton_example/mixed_triton.py:123-146.)
For multi-objective, return tuple[float, ...] of length num_objectives.
from compileiq.types import INVALID_SCORE, BASELINE_CONFIG
from compileiq.utils.helpers import save_compiler_configINVALID_SCORE is CompileIQ's sentinel — return it on any failure (compile,
hang, wrong answer, exception). Do not redefine it as float('inf').
BASELINE_CONFIG is the empty-dict sentinel CompileIQ passes when a knockout
knocks out every parameter (typically with normalize=True).
save_compiler_config(path, hex_str) writes the binary blob to disk; it
handles the bytes.fromhex internally (compileiq/utils/helpers.py:128-137).
Users never need to touch fromhex themselves.
Heavy library imports (torch, triton, helion, cute) go inside the function
so the process IsoMultiProcessWorker spawns — or the remote Ray task — can
re-import them in a clean state. Cheap module-level constants (paths, regexes)
are fine.
import os, tempfile
env = os.environ.copy()
env["TRITON_ALWAYS_COMPILE"] = "1"
env["HELION_SKIP_CACHE"] = "1"
env["TRITON_CACHE_DIR"] = tempfile.mkdtemp(prefix="ciq_triton_")For FlashInfer, additionally confirm the prebuilt cubin cache packages are
absent — flashinfer_cubin and flashinfer_jit_cache. See
docs/flashinfer_booster.md:56-64 for the import-time check.
--apply-controls injection| Target | Injection |
|---|---|
Raw PTXAS (you have a .ptx file) | ptxas --apply-controls candidate.acf kernel.ptx -arch=sm_100 -o kernel.cubin |
NVCC source (CUDA .cu) | nvcc -Xptxas --apply-controls=candidate.acf -arch=sm_100 kernel.cu -o exe (canonical; see examples/compilers/nvbench_example/optimize_reduction.py:108) |
| Triton kernel | kernel kwarg: kernel[grid](..., ptx_options=f"--apply-controls={acf_path}") plus TRITON_ALWAYS_COMPILE=1, os.environ["TRITON_PTXAS_PATH"] = shutil.which("ptxas"), and os.environ["TRITON_PTXAS_BLACKWELL_PATH"] = shutil.which("ptxas") when Blackwell-specific PTXAS selection may apply. This replaces the older PTXAS_OPTIONS= env-var approach for Triton. |
| Helion | Helion's official ACF API. See https://helionlang.com/examples/acfs/softmax_acf.html. Always set HELION_SKIP_CACHE=1. |
| cuTeDSL / FA4 (TVM-FFI) | cute.compile(..., options=f"{existing_options} --ptxas-options '--apply-controls {acf_path}'"). If you can't reach the call site, patch CompileCallable.__call__ to splice in the option string. |
| FlashInfer | FLASHINFER_EXTRA_CUDAFLAGS="--ptxas-options=--apply-controls=$ACF_FILE" (see docs/flashinfer_booster.md:107). |
def objective(config):
if isinstance(config, dict) and not config: # config == BASELINE_CONFIG
return measure_without_acf() # establish baseline run
# config is a hex string (or list with hex tail) — apply ACF
...The optimizer rewards whatever you measure. If you only measure latency, the algorithm will happily reward configs that compile faster by producing wrong answers. Always verify against a reference first:
if not torch.allclose(actual, reference, atol=1e-2, rtol=0):
return INVALID_SCORE
return triton.testing.do_bench(lambda: kernel(...), warmup=100, rep=1000, return_mode="mean")(Pattern from examples/compilers/triton_example/mixed_triton.py:141-146.)
try:
...
except (subprocess.TimeoutExpired, RuntimeError, FileNotFoundError, ValueError, OSError) as e:
return INVALID_SCOREWhen in doubt, catch broadly. CompileIQ expects
INVALID_SCORE as the "this config is broken" signal — re-raising means the
entire search fails.
Two cheap calls that catch ~90% of "every score is the same" bugs:
# Shape check — does the objective even run?
sample = tuner.sample(1)[0]
score = objective(sample)
print(f"sample run: {score}")
assert isinstance(score, (int, float)) and score == score # not NaN
# ACF-injection canary using the Debug pack (downloaded once)
from compileiq.utils.helpers import load_compiler_config
O0_HEX = load_compiler_config("booster-pack-debug/ptxas_opt0.acf")
O3_HEX = load_compiler_config("booster-pack-debug/ptxas_opt3.acf")
baseline = objective({}) # BASELINE_CONFIG path
score_O0 = objective(O0_HEX)
score_O3 = objective(O3_HEX)
assert score_O0 > baseline * 1.05, (
f"O0 should regress (got {score_O0} vs baseline {baseline}). "
"ACF is NOT reaching PTXAS — fix the cache-bust."
)
assert abs(score_O3 - baseline) / baseline < 0.05, (
f"O3 should match baseline (got {score_O3} vs {baseline})."
)
print("ACF injection canary PASSED — safe to start the search.")If either assertion fails, stop and fix the cache-bust before launching the search. Otherwise every generation's score is measurement noise on a stale binary.
A 3-line "smoke" objective inside the SKILL author's repo, used to verify the scaffolding before plugging in a real kernel:
def smoke_objective(config):
return 1.0 # constant; useful to verify Search() shape, not measurementDrop it into the Search(...) call and run 2 generations; if that completes
and results.get_best_result() returns a dict, your scaffold is correct.
PTXAS_OPTIONS is not the canonical Triton injection. It still works
for raw subprocess invocations, but Triton 3.x prefers the
ptx_options= kernel kwarg. See the table above.search_space=[user_dict, PtxasSearchSpace()], your objective must accept
a list, not a string. Results keep that list in best["params"]; unpack it
before saving the compiler config.INVALID_SCORE. Import it from compileiq.types. If
you redefine it locally as float('inf'), the value happens to work today
but is not guaranteed to in future releases.config_blob is no longer a parameter name. The old skill set used
def objective(config_blob) and called bytes.fromhex(config_blob). Both
are stale. Use def objective(config) and save_compiler_config(path, config).SearchConfiguration and picking a Worker: compileiq-run-search.compileiq-validate-result.compileiq-debug.© NVIDIA, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (references) in agent-skills/compileiq-author-objective of NVIDIA/CompileIQ.
Open the folder on GitHubat commit 743aca4
Compileiq Author Objective next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Compileiq Author Objective this skillNVIDIA/CompileIQ | 137 | — | ~2.3k | Automated safety check: Notes | Apache-2.0 | |
| Kubeshark Installerkubeshark/kubeshark | 12k | — | ~3.6k | Automated safety check: Notes | Apache-2.0 | |
| GreptimeDB Dev Docker ImageGreptimeTeam/greptimedb | 6.7k | — | ~4k | Automated safety check: Notes | Apache-2.0 | |
| KubeSphere ServiceMesh Managerkubesphere/kubesphere | 17k | — | ~2.4k | Automated safety check: Pass | Custom licence | |
| Vercelremotion-dev/remotion | 62k | — | ~1.2k | Automated safety check: Pass | Custom licence | |
| AWS Cdk Developmentzxkane/aws-skills | 367 | 2 repos | ~2.5k | Automated safety check: Pass | MIT |
kubeshark/kubeshark
Installs and configures Kubeshark on a Kubernetes cluster, choosing between the quick CLI path and a Helm install with custom values.
GreptimeTeam/greptimedb
Packages a locally built GreptimeDB debug binary into a development-only Docker image for local-cluster testing, with an optional push to a dev registry.
kubesphere/kubesphere
Installs, checks and troubleshoots the KubeSphere ServiceMesh extension (Istio, Kiali, Jaeger), including grayscale release, sidecar injection, topology and tracing issues.
remotion-dev/remotion
Set up a Codex monitor for Vercel deployments and preview URLs.
zxkane/aws-skills
AWS Cloud Development Kit (CDK) expert for building cloud infrastructure with TypeScript/Python.
maslennikov-ig/claude-code-orchestrator-kit
Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup…
NVIDIA/CompileIQ
Use BEFORE running a full CompileIQ search. An agent skill from NVIDIA/CompileIQ.
NVIDIA/CompileIQ
A skill your agent uses when starting a fresh CompileIQ project, hitting a socket timeout, or before running any other compileiq- skill.
NVIDIA/CompileIQ
A skill your agent uses when something is wrong: Search() hangs, all evaluations return INVALIDSCORE, scores aren't improving, every config returns the same number, ptxas errors fill the log, CV% is…
NVIDIA/CompileIQ
A skill your agent uses when composing the Search(...) call and calling .start().
NVIDIA/CompileIQ
Use AFTER a Search has completed and BEFORE claiming any speedup or shipping an ACF.
NVIDIA/CompileIQ
A skill your agent uses when picking the searchspace= argument for Search().
Categories
A skill your agent uses when writing the objectivefunction= passed to Search(). Compileiq Author Objective is an agent skill from NVIDIA/CompileIQ, published by the product's own GitHub organization. Use when writing the objectivefunction= passed to Search().
Compileiq Author Objective fits situations like: writing the objectivefunction= passed to Search(); objective function; savecompilerconfig; baseline knockout.
Run `npx skills add NVIDIA/CompileIQ --skill compileiq-author-objective -a claude-code`. Or copy the skill folder (agent-skills/compileiq-author-objective in NVIDIA/CompileIQ) into .claude/skills/compileiq-author-objective in your project. Claude Code loads it when a task matches its description.
Run `npx skills add NVIDIA/CompileIQ --skill compileiq-author-objective -a codex`. Or copy the skill folder (agent-skills/compileiq-author-objective in NVIDIA/CompileIQ) into .agents/skills/compileiq-author-objective in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA/CompileIQ --skill compileiq-author-objective -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/compileiq-author-objective, .gemini/skills/compileiq-author-objective, .github/skills/compileiq-author-objective and .opencode/skills/compileiq-author-objective in your project.
SKILL.md names no scripts, command-line tools or credentials: Compileiq Author Objective is instructions for the agent only. Our summary lists: Python 3. Its frontmatter pre-approves these tools: Bash, Read.
SKILL.md names 1 domain. In commands or code: helionlang.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Compileiq Author Objective is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.3k tokens (SKILL.md is roughly 9.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.1k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Compileiq Author Objective: Kubeshark Installer (kubeshark/kubeshark, 12k stars), GreptimeDB Dev Docker Image (GreptimeTeam/greptimedb, 6.7k stars), KubeSphere ServiceMesh Manager (kubesphere/kubesphere, 17k stars) and Vercel (remotion-dev/remotion, 62k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/CompileIQ, which has 137 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on September 23, 2026.
Source: NVIDIA/CompileIQ on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.