Simple Modern Uv
jlevy/simple-modern-uv
Start, selectively modernize, fully migrate, or update Python projects using simple-modern-uv practices: uv, ruff, BasedPyright, pytest, GitHub Actions CI, and tag-driven PyPI publishing.
Uplift the TTSim version used by tt-mlir CI and refresh WH/BH simulator skips.
$ npx skills add tenstorrent/tt-mlir --skill uplift-ttsim-ci -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install tenstorrent/tt-mlir uplift-ttsim-ci --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/tenstorrent/tt-mlir.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/uplift-ttsim-ci .claude/skills/uplift-ttsim-ci && 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 "uplift-ttsim-ci" agent skill from https://github.com/tenstorrent/tt-mlir/tree/main/.claude/skills/uplift-ttsim-ci into .claude/skills/uplift-ttsim-ci/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uplift-ttsim-ci", 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/tenstorrent/tt-mlir/tree/main/.claude/skills/uplift-ttsim-ciType 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 tenstorrent/tt-mlir --skill uplift-ttsim-ci -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install tenstorrent/tt-mlir uplift-ttsim-ci --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tenstorrent/tt-mlir.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/uplift-ttsim-ci .agents/skills/uplift-ttsim-ci && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "uplift-ttsim-ci" agent skill from https://github.com/tenstorrent/tt-mlir/tree/main/.claude/skills/uplift-ttsim-ci into .agents/skills/uplift-ttsim-ci/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uplift-ttsim-ci", 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 tenstorrent/tt-mlir --skill uplift-ttsim-ci -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install tenstorrent/tt-mlir uplift-ttsim-ci --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tenstorrent/tt-mlir.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/uplift-ttsim-ci .cursor/skills/uplift-ttsim-ci && 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 "uplift-ttsim-ci" agent skill from https://github.com/tenstorrent/tt-mlir/tree/main/.claude/skills/uplift-ttsim-ci into .cursor/skills/uplift-ttsim-ci/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uplift-ttsim-ci", 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/tenstorrent/tt-mlir.git --path .claude/skills/uplift-ttsim-ci--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 tenstorrent/tt-mlir --skill uplift-ttsim-ci -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install tenstorrent/tt-mlir uplift-ttsim-ci --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tenstorrent/tt-mlir.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/uplift-ttsim-ci .gemini/skills/uplift-ttsim-ci && 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 "uplift-ttsim-ci" agent skill from https://github.com/tenstorrent/tt-mlir/tree/main/.claude/skills/uplift-ttsim-ci into .gemini/skills/uplift-ttsim-ci/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uplift-ttsim-ci", 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 tenstorrent/tt-mlir uplift-ttsim-ciInstalls 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 tenstorrent/tt-mlir --skill uplift-ttsim-ci -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/tenstorrent/tt-mlir.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/uplift-ttsim-ci .github/skills/uplift-ttsim-ci && 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 "uplift-ttsim-ci" agent skill from https://github.com/tenstorrent/tt-mlir/tree/main/.claude/skills/uplift-ttsim-ci into .github/skills/uplift-ttsim-ci/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uplift-ttsim-ci", 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 tenstorrent/tt-mlir --skill uplift-ttsim-ci -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install tenstorrent/tt-mlir uplift-ttsim-ci --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tenstorrent/tt-mlir.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/uplift-ttsim-ci .opencode/skills/uplift-ttsim-ci && 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 "uplift-ttsim-ci" agent skill from https://github.com/tenstorrent/tt-mlir/tree/main/.claude/skills/uplift-ttsim-ci into .opencode/skills/uplift-ttsim-ci/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uplift-ttsim-ci", 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.
uplift-ttsim-ciUplift the TTSim version used by tt-mlir CI and refresh WH/BH simulator skips.
Uplift Ttsim CI is an agent skill from tenstorrent/tt-mlir. Uplift the TTSim version used by tt-mlir CI and refresh WH/BH simulator skips. Use when updating .github/workflows/call-test-ttsim.yml, changing ttsim-version, validating WH or BH TTSim golden tests, or triaging simulator-specific pytest skips.
Its SKILL.md is about 3.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Testing & QA, covering Unit testing. It works with pytest and GitHub Actions. The repository describes itself as: Tenstorrent MLIR compiler. The licence is Apache-2.0.
7 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 78b7044. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
pythongitcurlcmakergFrom 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:
github.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.
Uplift Ttsim CI loads about 3.1k tokens when it runs. Until then it costs about 66 tokens; SKILL.md has 1,262 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 found no risky patterns in SKILL.md.
Automated 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 tenstorrent/tt-mlir at commit 78b7044, republished under its Apache-2.0 licence (© tenstorrent). 1,262 words, ~3,084 tokens.
.claude/skills/uplift-ttsim-ci/SKILL.md (or your agent's skills folder).Follow the stages below in order. Do not move the regression sweep ahead of unskip triage, and do not stop after unskip triage.
An uplift is complete only when all of these are true:
noop edit is restored.If any stage is incomplete, report the coverage gap; do not call the uplift done.
.github/workflows/call-test-ttsim.yml is the source of truth for the test
list, matrix, descriptors, and assets. Re-read it at the start; never reuse a
stale test list copied into this skill.wormhole_b0 and blackhole. Ignore Quasar/QSR unless requested.1 rather than a signal-derived code. During unskip triage, one exact node
per pytest process is mandatory. A whole-file run with skips disabled is not
valid unskip evidence./opt/ttmlir-toolchain/venv/bin/python -m pytest; the local pytest
wrapper may hide useful output.set -u; activation expects some
variables to be unset:unset BUILD_DIR
source env/activate
export BUILD_DIR="$PWD/build"tenstorrent/ttsim.libttsim_wh.so and libttsim_bh.so.git status --short; preserve unrelated user changes..py arguments from the Run golden pytest on TTSim
step into a shell TEST_FILES array and print it for review:mapfile -t TEST_FILES < <(
awk '/^[[:space:]]+pytest /,/--sys-desc/ {
if ($1 ~ /\.py$/) print $1
}' .github/workflows/call-test-ttsim.yml
)
((${#TEST_FILES[@]} > 0)) || {
echo "No TTSim workflow tests found"
exit 1
}
printf '%s\n' "${TEST_FILES[@]}"ttsim-version default unless the current
release requires a justified matrix/setup change. Keep this matrix:- arch: wormhole_b0
soc_desc: wormhole_b0_80_arch.yaml
ttsim_asset: libttsim_wh.so
- arch: blackhole
soc_desc: blackhole_140_arch.yaml
ttsim_asset: libttsim_bh.soUse a versioned root and separate result directories:
export TTSIM_VERSION=vX.Y.Z
export TTSIM_ROOT="${TMPDIR:-/tmp}/ttmlir-ttsim/$TTSIM_VERSION"
mkdir -p \
"$TTSIM_ROOT/wormhole_b0" \
"$TTSIM_ROOT/blackhole" \
"$TTSIM_ROOT/results/wormhole_b0" \
"$TTSIM_ROOT/results/blackhole"
curl -L --fail --retry 3 \
-o "$TTSIM_ROOT/wormhole_b0/libttsim_wh.so" \
"https://github.com/tenstorrent/ttsim/releases/download/$TTSIM_VERSION/libttsim_wh.so"
curl -L --fail --retry 3 \
-o "$TTSIM_ROOT/blackhole/libttsim_bh.so" \
"https://github.com/tenstorrent/ttsim/releases/download/$TTSIM_VERSION/libttsim_bh.so"
cp third_party/tt-metal/src/tt-metal/tt_metal/soc_descriptors/wormhole_b0_80_arch.yaml \
"$TTSIM_ROOT/wormhole_b0/soc_descriptor.yaml"
cp third_party/tt-metal/src/tt-metal/tt_metal/soc_descriptors/blackhole_140_arch.yaml \
"$TTSIM_ROOT/blackhole/soc_descriptor.yaml"Override TTSIM_ROOT with a durable path when logs must survive a reboot, but
keep generated binaries, artifacts, and reports outside the git working tree.
Set common variables once:
export TT_MLIR_HOME="$PWD"
export TT_METAL_HOME="$PWD/third_party/tt-metal/src/tt-metal"
export TT_METAL_SLOW_DISPATCH_MODE=1
export TT_METAL_DISABLE_SFPLOADMACRO=1
export TT_METAL_INSPECTOR=0
export TT_METAL_INSPECTOR_RPC=0
export LD_LIBRARY_PATH="$PWD/build/lib:${TTMLIR_TOOLCHAIN_DIR}/lib:${LD_LIBRARY_PATH:-}"Build the current checkout before testing; results from stale tt-mlir or tt-metal binaries are invalid:
cmake --build "$BUILD_DIR"Generate and retain one system descriptor per architecture. These commands may run in parallel:
export TT_METAL_SIMULATOR_HOME="$TTSIM_ROOT/wormhole_b0"
export TT_METAL_SIMULATOR="$TT_METAL_SIMULATOR_HOME/libttsim_wh.so"
ttrt query --save-artifacts \
--artifact-dir "$TT_METAL_SIMULATOR_HOME/ttrt-artifacts" --quiet
export TT_METAL_SIMULATOR_HOME="$TTSIM_ROOT/blackhole"
export TT_METAL_SIMULATOR="$TT_METAL_SIMULATOR_HOME/libttsim_bh.so"
ttrt query --save-artifacts \
--artifact-dir "$TT_METAL_SIMULATOR_HOME/ttrt-artifacts" --quietDo not share TT_METAL_SIMULATOR_HOME, --sys-desc, --path, or result logs
between architectures.
Complete the candidate plan before executing candidates.
sim skip sites. Record file,
line, mark, parameter scope, and intended architecture in
sim-mark-sites.txt.rg -n '\bsim\b' "${TEST_FILES[@]}" > sim-mark-sites.txt"sim"), collect exact skipped node
IDs on WH and BH without executing tests:COLUMNS=10000 /opt/ttmlir-toolchain/venv/bin/python -m pytest \
--setup-plan -vv --color=no "${TEST_FILES[@]}" \
--sys-desc "$TT_METAL_SIMULATOR_HOME/ttrt-artifacts/system_desc.ttsys" \
2>&1 |
awk '/ SKIPPED/ {sub(/[[:space:]]+SKIPPED.*/, ""); print}' |
LC_ALL=C sort -uSave this once per architecture as all-skipped-before-noop.txt.
_get_current_environment() in
test/python/golden/conftest.py to return "noop" when
TT_METAL_SIMULATOR is set. Do not add noop to ALL_ENVIRONMENTS.
Simulator marks no longer match, while unconditional skips, non-simulator
skips, and only_config behavior remain active.still-skipped-with-noop.txt.comm -23 \
all-skipped-before-noop.txt \
still-skipped-with-noop.txt \
> candidates.txtReview every source mark against the resulting WH/BH lists. Record sim-marked
nodes that remain skipped under noop in not-executable.txt; do not count
them as tested or remove their simulator mark without other evidence. Freeze
the two candidate lists before execution and record their counts.
Keep the noop edit active. For each architecture, run the corresponding
candidates.txt serially. Quote each complete node ID:
timeout --signal=TERM --kill-after=10s 180s \
env PYTHONUNBUFFERED=1 \
/opt/ttmlir-toolchain/venv/bin/python -m pytest -svvv "$node_id" \
--sys-desc "$TT_METAL_SIMULATOR_HOME/ttrt-artifacts/system_desc.ttsys" \
--path "$TT_METAL_SIMULATOR_HOME/pytest_artifacts_candidates" \
--tb=short -rsWrite one log per node plus a TSV/JSON manifest containing architecture,
node ID, elapsed time, exit code, and result. Continue after nonzero exits and
print progress after every node. WH and BH loops may run concurrently, but
never group multiple node IDs into one pytest invocation. Keep -s enabled so
pytest capture cannot swallow the last TTSim error when the process exits.
Classify results from both exit status and the pytest terminal summary:
passed: pytest reports the node passed. This is the only automatic unskip
evidence.failed: pytest prints a normal failure/error summary.aborted: the process ends without a pytest terminal summary, even if its
exit code is only 1.timed_out: the 180-second timeout expires.skipped, xfailed, or xpassed: record separately; none proves a clean
simulator pass.For an empty or unclear abort log, rerun that exact node with
PYTHONUNBUFFERED=1 -svvv. Do not rerun a group.
After the matrix is complete:
n150; single-chip BH is p150.skip_config(["n150", "sim"]) means WH simulator only, while
SkipIf("n150", "sim") means n150 or any simulator.sim is obsolete in
SkipIf("ttnn", "emitc", "emitpy", "sim"), keep
SkipIf("ttnn", "emitc", "emitpy").If behavior differs from the previous TTSim version, run the smallest failing node against both versions with the same tt-mlir checkout and corresponding system descriptors.
Restore _get_current_environment() to return "sim" before any final
validation. Inspect the diff rather than using a destructive checkout, and
verify that conftest.py has no triage-only change. Keep the candidate
manifests as validation artifacts, not source changes.
This stage is mandatory and happens after skip updates and noop restoration.
Run every file in TEST_FILES, one file per pytest process, on WH and BH. Do
not use one aggregate pytest command: an abort would hide the remaining files.
Continue after failures. The two architecture loops may run in parallel.
timeout --signal=TERM --kill-after=15s 3600s \
env PYTHONUNBUFFERED=1 \
/opt/ttmlir-toolchain/venv/bin/python -m pytest -vv "$test_file" \
--sys-desc "$TT_METAL_SIMULATOR_HOME/ttrt-artifacts/system_desc.ttsys" \
--path "$TT_METAL_SIMULATOR_HOME/pytest_artifacts_regression" \
--tb=short -rsSome files may take more than 30 minutes, but an individual node should not
take more than about three minutes. Monitor each live -vv log at least every
three minutes. If progress stops, terminate the file run, isolate the last
reported node with the 180-second candidate command, update the smallest
necessary skip, and rerun that file. A generous file timeout is not a
substitute for progress monitoring.
Record exactly one final status per file per architecture:
passed: pytest exits 0 with a terminal summary; expected skips/xfails are
allowed.failed: pytest reports normal failures.aborted: no pytest terminal summary, regardless of exit code.timed_out: the file timeout expires.Any skip change made during regression requires a fresh run of that file on both architectures. Do not finish with an untriaged failed, aborted, or timed out file.
.github/workflows/call-test-ttsim.yml with available local
tooling.git diff --check and inspect git status and the complete diff.conftest.py is restored and generated simulator assets/results
are not in the source diff..ttsys used per architecture;© tenstorrent, 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
Just SKILL.md in .claude/skills/uplift-ttsim-ci of tenstorrent/tt-mlir.
Open the folder on GitHubat commit 78b7044
Uplift Ttsim CI 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 |
|---|---|---|---|---|---|---|
| Uplift Ttsim CI this skilltenstorrent/tt-mlir | 314 | — | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| Simple Modern Uvjlevy/simple-modern-uv | 301 | — | ~1.9k | Automated safety check: Pass | MIT | |
| Megatron Core Testing GuideNVIDIA/Megatron-LM | 18k | — | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Py Package Checkipea/geobr | 961 | — | ~1.4k | Automated safety check: Notes | None | |
| Gating Deid Leakagemaziyarpanahi/openmed | 5.5k | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | |
| Fixing Flaky TestsPostHog/posthog | 40k | — | ~5.9k | Automated safety check: Pass | Custom licence |
jlevy/simple-modern-uv
Start, selectively modernize, fully migrate, or update Python projects using simple-modern-uv practices: uv, ruff, BasedPyright, pytest, GitHub Actions CI, and tag-driven PyPI publishing.
NVIDIA/Megatron-LM
Guide to the Megatron-LM test system: layout, recipe YAML, running and adding unit and functional tests, golden values, marker filters and CI parity.
ipea/geobr
Run the Python package release gate for geobr — sync the locked environment, run the offline and network test suites, build the distribution, and review the source against the Python conventions.
maziyarpanahi/openmed
Add a CI gate that fails the build when an OpenMed de-identification model's recall on a held-out PHI set drops below threshold or any critical identifier leaks.
PostHog/posthog
Guides an agent through reproducing, root-causing, fixing, and validating flaky tests in the PostHog monorepo.
Aedelon/claude-code-blueprint
Reference patterns for REST APIs, pytest/vitest testing, Docker multi-stage builds, GitHub Actions CI/CD, PostgreSQL, TypeScript generics, Python async, and React Server Components.
tenstorrent/tt-mlir
How to add a new operation (op) to the tt-mlir compiler across all layers: TTIR/TTNN dialect definitions, StableHLO composite conversion, TTIR-to-TTNN conversion, EmitC/EmitPy conversions…
tenstorrent/tt-mlir
Add full builder API support (@tag, @parse, @split) for a TTIR op.
tenstorrent/tt-mlir
Compile and optionally execute every func.func in an ops.mlir-style snippet file (or every .mlir file in a directory) using runopsmlirsnippets.py.
tenstorrent/tt-mlir
Add a new composite op decomposition pattern to the TTMetal pipeline.
tenstorrent/tt-mlir
Validate a tt-mlir PR against tt-xla by creating a cherry-picked branch and triggering CI.
tenstorrent/tt-mlir
Triage a tt-metal uplift diff or digest of TTFATAL validation changes against what tt-mlir guarantees at each optimization level (0: workarounds only, 1: optimizer with DRAM-only fallback, 2: L1…
Works with
Categories
Uplift the TTSim version used by tt-mlir CI and refresh WH/BH simulator skips. Uplift Ttsim CI is an agent skill from tenstorrent/tt-mlir. Uplift the TTSim version used by tt-mlir CI and refresh WH/BH simulator skips.
Uplift Ttsim CI fits situations like: updating .github/workflows/call-test-ttsim.yml; changing ttsim-version; BH TTSim golden tests; triaging simulator-specific pytest skips.
Run `npx skills add tenstorrent/tt-mlir --skill uplift-ttsim-ci -a claude-code`. Or copy the skill folder (.claude/skills/uplift-ttsim-ci in tenstorrent/tt-mlir) into .claude/skills/uplift-ttsim-ci in your project. Claude Code loads it when a task matches its description.
Run `npx skills add tenstorrent/tt-mlir --skill uplift-ttsim-ci -a codex`. Or copy the skill folder (.claude/skills/uplift-ttsim-ci in tenstorrent/tt-mlir) into .agents/skills/uplift-ttsim-ci 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 tenstorrent/tt-mlir --skill uplift-ttsim-ci -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/uplift-ttsim-ci, .gemini/skills/uplift-ttsim-ci, .github/skills/uplift-ttsim-ci and .opencode/skills/uplift-ttsim-ci in your project.
Going by SKILL.md and its folder, Uplift Ttsim CI needs the command-line tools its instructions call (python, git, curl, cmake and rg). Our summary lists: Python 3.
SKILL.md names 1 domain. In commands or code: github.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 no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Uplift Ttsim CI is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.1k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Uplift Ttsim CI: Simple Modern Uv (jlevy/simple-modern-uv, 301 stars), Megatron Core Testing Guide (NVIDIA/Megatron-LM, 18k stars), Py Package Check (ipea/geobr, 961 stars) and Gating Deid Leakage (maziyarpanahi/openmed, 5.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
tenstorrent (a GitHub organization) maintains it in tenstorrent/tt-mlir, which has 314 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on October 10, 2026.
Source: tenstorrent/tt-mlir on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.