tenstorrent

Generate, refresh, and validate an LLK performance report by running a perf sweep end to end and checking the resulting perf_data CSV. Use when asked to produce or refresh a perf report for an op, run a perf sweep, or when a report is missing, partial, stale,…

Generate, refresh, and validate an LLK performance report by running a perf sweep end to end and checking the resulting perf_data CSV. Use when asked to produce or refresh a perf report for an op, run a perf sweep, or when a report is missing, partial, stale,…

Create, extend, debug, and validate Quasar LLK performance tests, their PerfRunType kernel paths, and tile/dimension sweep coverage. Use when adding perf_[op]_quasar.py, wiring PerfConfig, implementing UNPACK_ISOLATE / MATH_ISOLATE / PACK_ISOLATE /…

Create, extend, debug, and validate Quasar LLK performance tests, their PerfRunType kernel paths, and tile/dimension sweep coverage. Use when adding perf_[op]_quasar.py, wiring PerfConfig, implementing UNPACK_ISOLATE / MATH_ISOLATE / PACK_ISOLATE /…

Compare one LLK perf test between two commits on this machine — by default the branch HEAD against the exact main commit it was branched from (the merge-base, not latest main), or any two refs the user names (hash, tag, origin/main, HEAD~5). Runs the sweep on…

Analyze LLK performance-report CSV files and create evidence-backed parameter-impact reports in a Cursor Canvas. Use when asked how formats, fidelity, dimensions, accumulation, indexing, loop factors, or other parameters affect TILE_LOOP or another marker in…

Analyze LLK performance-report CSV files and create evidence-backed parameter-impact reports in a Cursor Canvas. Use when asked how formats, fidelity, dimensions, accumulation, indexing, loop factors, or other parameters affect TILE_LOOP or another marker in…

Audit LLK code for races on the backend CONFIG register file where differently-named fields share the SAME 32-bit config word — both cross-thread (unpack/math/pack write the same word) and intra-thread (a full-word write clobbers a sibling field the same…

Compare two nightly GitHub Actions runs and classify failures as new, persisting, or fixed

Fix transformers compatibility regressions in tt-xla and tt-forge-models after the pinned version was bumped. Called by the transformers-uplift CI orchestrator with a scope (api-check, model-test-uplifts, model-perf-uplift) and a captured failure context.…

Stash local changes, pull latest main, and display a structured commit summary. For tt_forge_models uplift commits, shows the affected models from the submodule log.

Analyze a PyTorch model, then design and implement an optimal multi-device sharding strategy for Tenstorrent hardware that minimizes collective-communication (CCL) ops. A strategy is both which parallelism to use (tensor / sequence / data) and how to shard…

Analyze CI benchmark workflow runs from GitHub Actions for the tt-xla project. Produces a markdown report covering failed jobs (with root-cause error extraction via logs and Glean), successful model performance metrics (samples/sec, TTFT, device perf), perf…

Review and fix language correctness and formatting in documentation files.

Triage one tt-forge-models training test failing with a bfloat16 dtype-mismatch RuntimeError (e.g. "mat1 and mat2 must have the same dtype, but got Float and BFloat16", "'<op>' not implemented for 'BFloat16'"). For cross-dtype operands, attempts a minimal…

Triage one tt-forge-models training test stuck at FAILED_FE_COMPILATION with reason "tt-forge-models doesn't implement unpack_forward_output for this model." Inspects the model's forward output, registers a handler or writes a per-loader override, and updates…

Diagnose data-corruption failures in tt-emule operations (wrong values, partial zeros, off-by-N row/col writes). Use when a regression test reports ATOL > 1e-3 on otherwise-functional kernel paths.

Registry of deliberate, non-ideal workarounds currently live in tt-emule (hacks we accepted to make something pass, NOT normal development practice). Read this before adding any new workaround, and when touching code that carries one — each entry records what…

Diagnose and fix emule regressions caused by bumping the tt-metal pin (and its bundled tt-umd submodule). Use when a pin bump turns the C++ or TTNN regression red — device-open crashes, JIT-compile errors, hangs, or new data mismatches — and you need to prove…

Verification checklist to walk before declaring a tt-emule mock complete. Use after implementing a stub (typically at the end of /implement-mock or /compute-llk-bringup) to catch the recurring failure modes — signature drift, no-op math, missing format…

Take an open tt-emule PR to a mergeable, ethos-compliant state. Use when asked to review a PR, address its comments, and prepare it to land — verifies every review point by build (not by trusting "addressed"), runs an emule-ethos pass for the bug classes…

Bring up or debug index-based compute ops (TopK, Sort, Argmax) in tt-emule — ops that return values + indices, where ties make the index choice non-unique. Use when implementing one of these ops or triaging its value/index test failures.

Specialization of `/implement-mock` for compute-kernel LLK shims (`<op>_tile` / `<op>_tile_init` under `include/jit_hw/api/compute/`). Use when bringing up a missing compute op or addressing its PCC failures.

Workflow for adding a faithful mock of a silicon API to tt-emule. Composes `/arch-lookup` (find HW spec) → emule-mapping strategy selection → stub implementation → verification against sentinel + tt-metal regression.

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.

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, flatbuffer schema and serialization, runtime implementation, OpModel,…

Given a `.mlir` file (or a directory of `.mlir` files) with TTIR ops, run the same TTIR normalization passes as `D2MFrontendPipeline` before D2M, then produce per-file outputs: `preprocessed.mlir`, `ttir-op-report.txt` (op counts from normalized IR), and…

Add a new composite op decomposition pattern to the TTMetal pipeline. Use when the user wants to decompose/lower a high-level TTIR op (e.g. rms_norm, sdpa, layer_norm, softmax) into primitive TTIR ops (matmul, add, multiply, etc.) for the D2M/TTMetal backend.…

Compile and optionally execute every func.func in an ops.mlir-style snippet file (or every .mlir file in a directory) using `run_ops_mlir_snippets.py`. Use when the user wants to compile or run TTIR op snippets on device, test ops.mlir files, or check which…

Elementwise TTIR→D2M→TTMetal path: tablegen, TTIRToD2M.cpp, D2MToTTKernel.cpp, and — only when the kernel API callee is new — TTKernelIncludesMap.h (per-op api/compute/eltwise_unary/*.h mapping for JIT). Does not edit D2MGenericRegionOps.cpp or…

Validate a tt-mlir PR against tt-xla by creating a cherry-picked branch and triggering CI. Invoked as: /validate-tt-mlir-against-tt-xla <PR number or URL>. Use this skill whenever the user wants to test, validate, qualify, or check a tt-mlir PR in tt-xla, or…

Add full builder API support (@tag, @parse, @split) for a TTIR op. Use this skill whenever the user wants to add builder support for a new TTIR op, upgrade an existing _op_proxy-based op to use @tag/@parse/@split decorators, or asks about how to add builder…

The complete CLI design language distilled from TT-Studio's `python run.py`, made portable to any repo: the command surface (one self-bootstrapping entrypoint, grouped `--help` panels, early-dispatch utility flags, lifecycle symmetry, re-viewable state), the…

Draft TT-Studio GitHub release notes in the house style: study the last one or two published releases for structure and voice, diff the current release branch against the previous release tag/commit, then group the changes into 🚀 New Features / 🐛 Bug Fixes /…

Make a change in TT-Studio the team way: branch off `dev` with a `<username>/<feature>` branch, keep the diff minimal and in-scope, verify the running app via its health endpoints before pushing, leave every other branch untouched, and open a PR against `dev`…

Bring up a model that tt-inference-server lists as supported but that TT-Studio can't deploy today — add it to the catalog, deploy it on real hardware, triage failures layer by layer (tt-studio → tt-inference-server → tt-metal), verify fixes by hot-patching…

The TT-Studio CLI skill — how the `python run.py` command-line interface (the `tt_setup/` package) is built and how to change it the TT-Studio way: Typer CLI conventions (flag grouping, early-dispatch utility flags, `--help`/`--help-env` docs), package layout…

Review third-party license attribution for TT-Studio when dependencies or bundled assets change, and keep the attribution files in sync. Use when a PR adds/updates a dependency (app/backend/requirements.txt, app/agent, inference-api, docker-control-service,…

Triage a TT-Studio bug-report ZIP / log bundle (named `tt-studio-logs-ttbr-*` or referenced as `ttbr-*`) to root-cause why a model deploy, board allocation, or Voice Agent pipeline failed. Use when the user shares a path to a TT-Studio log bundle, mentions a…

Project map for TT-Studio — what the platform is, where its docs live, its key components (React frontend, Django backend, FastAPI inference server, Docker), and the AI model types it supports. Use when you need a high-level orientation of the repo, want to…

File a bug report with a reproducer against Tenstorrent repos (tt-lang, tt-metal, tt-xla)

Set up and verify remote connection to Tenstorrent hardware. Provides tools for running kernels, copying files, and reading logs on remote devices.

TTNN trace capture and replay for eliminating dispatch overhead. Essential for real-time inference and multi-chip performance.

Profile and optimize TT-Lang kernels for performance. Covers auto-profiling, perf summary, signposts, and optimization workflow.

Comprehensive TT-Lang DSL reference including programming model, APIs, hardware constraints, and guides for translating CUDA, Triton, PyTorch, or TTNN kernels

TTNN operations library reference for Tenstorrent hardware. Covers tensor APIs, ops catalog, model conversion from PyTorch, and memory/layout configuration.

Checklist for adding or modifying code in the workflow engine (run_workflows.py plus the llm_module/report_module/test_module/workflow_module packages) — new models, workflows, media runners, spec tests, report kinds, or CLI flags — and wiring it back to the…

Checklist for onboarding a new LLM to the cpp_server inference backend so it serves through Dynamo — registering the model type, fetching tokenizer files, tokenizer static data (eos/stop/think tokens), and Dynamo discovery (reasoning + tool-call parsers,…

Capture on-CPU and off-CPU flamegraphs of the running tt_media_server_cpp main (Drogon) and worker processes using Linux perf + Brendan Gregg's FlameGraph. Use when the user asks to profile the C++ server, find a performance bottleneck, identify slow code…

Trigger Tenstorrent Blaze media server and tt-metal upstream Docker image builds with gh. Use when the user asks to build Blaze and Metal Docker images, run the tt-shield media server image workflow, or build tt-metal images from the tt-llm-engine submodule…

Delegates LLK test runs to the llk-test-runner agent using @.cursor/agents/llk-test-runner.md. Use when the user asks to run tests or mentions LLK tests. Ensure test commands run to completion before reading terminal output (no polling).

Run device performance benchmarks for tt-blacksmith single-chip training workloads. Use when the user asks to benchmark, profile, or measure performance of a training workload on Tenstorrent hardware, or mentions tracy, tt-perf-report, or device time analysis.

Guide the user through submitting a new entry to the Awesome Tenstorrent list. Use when the user wants to add, submit, or propose a project, library, tool, or resource to tt-awesome.

Author a tt-model.yaml — the CONTAINER (v5.1) manifest only — for a model in a tt-metal checkout, by reading its serve recipe and import closure and interviewing the user for what the directory cannot tell you. Use for "containerize this model", "write a…

Rebases this Tenstorrent fork of terraform-provider-netbox onto the latest e-breuninger upstream and cuts a new release. Use when the user asks to rebase onto upstream, sync with upstream, pull in upstream changes, update from e-breuninger, or release a new…