ascend-npu-optimize-state
Manage temporary optimize workflow state in an Ascend NPU optimize workspace, including baseline acceptance, round start, same-round strategy-state updates…
Skill by Piagari
Chalk Labs
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About
Use cases: productivity
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
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- Secrets
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- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/ascend-npu-optimize-state
What's inside
- Skill name
ascend-npu-optimize-state- Description
- Manage temporary optimize workflow state in an Ascend NPU optimize workspace, including baseline acceptance, round start, same-round strategy-state updates, and round submission.
- License
- Apache-2.0
- Instructions
- 135 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (21)
- SKILL.md
- baseline-contract.json · references/
- round-contract.json · references/
- check.py · scripts/baseline/
- contract.py · scripts/baseline/
- cli.py · scripts/
- check.py · scripts/round/
- contract.py · scripts/round/
- kernel_continuity.py · scripts/round/
- local_optimum.py · scripts/round/
- cli.py · scripts/shared/
- json_io.py · scripts/shared/
- models.py · scripts/shared/
- paths.py · scripts/shared/
- results.py · scripts/shared/
- round_naming.py · scripts/shared/
- set_current_round_state.py · scripts/state_manage/
- start_round.py · scripts/state_manage/
- state_machine.py · scripts/state_manage/
- submit_baseline.py · scripts/state_manage/
- submit_round.py · scripts/state_manage/
SKILL.md (first lines)
# Optimize State
Use this skill to manage optimize workflow state through one structured CLI entrypoint:
```bash
python3 scripts/cli.py submit-baseline --baseline-dir baseline
python3 scripts/cli.py start-round --round-dir opt-round-1 --round-strategy exploration --analysis-policy pattern_entry --reason "..."
python3 scripts/cli.py set-current-round-state --round-strategy focused_tuning --analysis-policy ir_required --reason "..."
python3 scripts/cli.py submit-round --round-dir opt-round-2 --current-round 2 --final-round 4
```
## When To Use
- Use `submit-baseline` when `baseline/` needs to be accepted before any optimize round may begin or continue.
- Use `start-round` immediately before beginning work on a new `opt-round-N/`; it initializes the active round's workflow-owned strategy state.
- Use `set-current-round-state` when the active round's strategy or required evidence depth changes mid-round.
- Use `submit-round` after one round is complete and before the workflow may continue or stop.
## Subcommands
### `submit-baseline`
- Validates canonical baseline artifacts and `baseline/state.json`.
- Prints JSON only; read the `guideline` field for the pass/fix instruction.
- Treat returned `issues` as the baseline repair checklist.
- Baseline preparation still belongs to `ascend-npu-prepare-optimize-baseline`.
### `start-round`
- Enforces the runner-managed `.helix/state.json` workflow gate before a round begins.
- Requires `--round-strategy`, `--analysis-policy`, and `--reason`.
- Writes the active round's latest strategy state into `.helix/state.json`.
- Appends a structured `State Update` block to `opt-round-N/attempts.md`.
- Prints JSON only; read the `guideline` field and keep the returned `hard_rules` in force for the active round.
- Use this to bridge temporary runner-managed workflow state with the durable `opt-round-N/` you are about to work in.
#### `--round-strategy` Allowed Values
- `exploration`: narrow the next promising optimization direction before making a larger commitment.
- `structural_change`: pursue a larger rewrite in shape, layout, dataflow, or algorithm structure.
- `focused_tuning`: refine a direction that is already validated instead of searching broadly again.
- `stabilization`: repair correctness, compile stability, or fragile performance before further tuning.
- `plateau_review`: assess whether the current direction has reached a local plateau and needs a pivot or deeper evidence.
#### `--analysis-policy` Allowed Values
- `pattern_entry`: begin from code structure and pattern triage; deeper evidence is optional before the main edit.
- `profile_required`: require profiler evidence before the main edit.
- `ir_required`: require IR-backed attribution before the main edit.
- `compiler_source_required`: require compiler-source evidence because profiler and IR evidence have already narrowed the question to a compiler-side issue.
#### `--reason`
- Always pass a short explicit reason that explains why this round is entering the chosen strategy and evidence depth.
- This text is stored in workflow state and mirrored into the round's structured `State Update` block in `attempts.md`.
#### Common `start-round` Examples
- First exploratory round from code structure and pattern triage:
```bash
python3 scripts/cli.py start-round \
--round-dir opt-round-1 \
--round-strategy exploration \
--analysis-policy pattern_entry \
--reason "Start from pattern triage to narrow the first promising direction."
```
- Profiler-backed structural rewrite:
```bash
python3 scripts/cli.py start-round \
--round-dir opt-round-2 \
--round-strategy structural_change \
--analysis-policy profile_required \
--reason "Profiler evidence points to a bottleneck that likely needs a larger structural rewrite."
```
- Validated direction with deeper IR-backed tuning:
```bash
python3 scripts/cli.py start-round \
--round-dir opt-round-3 \
--round-strategy focused_tuning \
--analysis-policy ir_required \
--reason "The direction is already validated, but IR attribution is still needed before the next tuning edit."
```
### `set-current-round-state`
- Updates the current active round's workflow-owned strategy state without selecting a round by path.
- Locates the nearest ancestor optimize workspace from the current working directory, so it can be run from the workspace root or from inside `opt-round-N/` subdirectories.
- Requires `--reason` plus at least one of `--round-strategy` or `--analysis-policy`.
- Rejects no-op updates and same-round `analysis_policy` rollbacks.
- Appends a structured `State Update` block to the active round's `attempts.md`.
- Prints JSON only; read the `guideline` field and apply any returned `warnings`.
Use the same enum values listed above for `--round-strategy` and `--analysis-policy`.
#### Common `set-current-round-state` Examples
- Raise only the required evidence depth after profiling becomes necessary:
```bash
python3 scripts/cli.py set-current-round-state \
--analysis-policy profile_required \
--reason "Pattern triage is no longer sufficient; profiler evidence is now required before the next code change."
```
- Pivot the round into a larger structural rewrite:
```bash
python3 scripts/cli.py set-current-round-state \
--round-strategy structural_change \
--reason "The current evidence points to a larger dataflow or layout rewrite instead of another narrow tuning pass."
```
- Switch into stabilization when the direction still looks good but the implementation is fragile:
```bash
python3 scripts/cli.py set-current-round-state \
--round-strategy stabilization \
--analysis-policy ir_required \
--reason "The direction still looks promising, but correctness and performance are unstable and need repair before further tuning."
```From Piagari/helix, Apache-2.0.
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Signals
- Stars
- 0
- Forks
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- Open issues
- 0
- Last commit (this folder)
- Jul 15, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- Repository
- github.com/Piagari/helix
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Create, list, and inspect GitCode pull requests for the current project.
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Use when opening a new pull request for this repository requires the repo's branch, validation, and skill-script checking gates to run before PR creation.
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ascend-npu-optimize-state skill. Agent Mart. https://agentmart.dev/skills/piagari-ascend-npu-optimize-state (last updated 2026-10-24)