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309 lines
14 KiB
Markdown
309 lines
14 KiB
Markdown
# CLI Reference
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> **Version note.** This reference tracks `main`. PyPI 0.2.0 does not yet
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> include the generic research `openai_compatible` backend, Sleep handoff,
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> Sleep support for non-Azure OpenAI-compatible endpoints, the Sleep
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> `--preferences` flag, the research `cursor_exec` target harness, or Cursor
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> source/backend/plugin support, Pi source/backend support, or VS Code Copilot
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> transcript harvesting; use a source install from `main` for those features
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> until the next release.
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## Training
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```bash
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python scripts/train.py --config <config.yaml> [overrides...]
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# Installed equivalent:
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skillopt-train --config <config.yaml> [overrides...]
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```
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### Arguments
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| Argument | Description |
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|---|---|
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| `--config` | Path to YAML config file (required) |
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| `--cfg-options key=value [...]` | Override structured config parameters |
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### Examples
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```bash
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# Basic training
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python scripts/train.py \
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--config configs/searchqa/default.yaml \
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--out_root outputs/searchqa_run
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# With overrides
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python scripts/train.py \
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--config configs/searchqa/default.yaml \
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--cfg-options optimizer.learning_rate=16 optimizer.lr_scheduler=linear
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# With custom initial skill
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python scripts/train.py \
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--config configs/searchqa/default.yaml \
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--cfg-options env.skill_init=skills/my_seed.md
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```
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## Evaluation
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```bash
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python scripts/eval_only.py --config <config.yaml> --skill <skill.md>
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# Installed equivalent:
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skillopt-eval --config <config.yaml> --skill <skill.md>
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```
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### Arguments
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| Argument | Description |
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|---|---|
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| `--config` | Path to YAML config file (required) |
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| `--skill` | Path to skill document to evaluate (required) |
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| `--split` | `train`, `valid_seen`, `valid_unseen`, or `all` (default) |
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| `--cfg-options` | One or more `section.key=value` overrides |
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### Examples
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```bash
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# Evaluate best skill on test set
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python scripts/eval_only.py \
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--config configs/searchqa/default.yaml \
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--skill outputs/searchqa_run/best_skill.md \
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--split valid_unseen
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# Evaluate on validation set
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python scripts/eval_only.py \
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--config configs/searchqa/default.yaml \
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--skill outputs/searchqa_run/best_skill.md \
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--split valid_seen
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```
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`--skill` consumes the artifact produced by training. Unless `--out_root` is
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set for evaluation, `eval_only.py` creates a separate timestamped
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`outputs/eval_<env>_<model>_<timestamp>/` directory and writes
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`eval_summary.json` there; it does not modify the training run directory.
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For the generic OpenAI-compatible research backend, select the role backends
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explicitly:
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```bash
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python scripts/train.py \
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--config configs/searchqa/default.yaml \
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--cfg-options \
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model.optimizer_backend=openai_compatible \
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model.target_backend=openai_compatible \
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model.optimizer=deepseek-chat \
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model.target=deepseek-chat
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```
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To benchmark an installed, authenticated Cursor Agent through an environment
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that supports exec targets:
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```bash
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python scripts/eval_only.py \
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--config configs/searchqa/default.yaml \
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--skill skills/my_skill.md \
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--cfg-options \
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model.optimizer_backend=openai_chat \
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model.target_backend=cursor_exec \
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model.target=composer-2.5
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```
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`cursor_exec` runs the target only; the optimizer remains separately
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configured. Read-only rollouts use Cursor Ask mode. Rollouts that request file
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edits use `--force` inside the benchmark workspace, with Cursor sandboxing
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enabled. The harness refuses file-edit rollouts when the Cursor sandbox is
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disabled. Read-only Ask-mode rollouts may explicitly disable it. Override the
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executable or sandbox through `model.cursor_exec_path` and
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`model.cursor_exec_sandbox`.
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## SkillOpt-Sleep
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```bash
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skillopt-sleep <action> [options]
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# Equivalent from a source checkout:
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python -m skillopt_sleep <action> [options]
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```
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Actions are `run`, `dry-run`, `status`, `adopt`, `harvest`, `schedule`, and
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`unschedule`. Common options include:
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| Argument | Description |
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| `--project PATH` | Project used for transcript scope, targets, state, and staging (default: current directory) |
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| `--scope invoked\|all` | Harvest this project or all projects |
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| `--source claude\|codex\|copilot\|cursor\|pi\|auto` | Transcript source; `auto` keeps Codex-then-Claude precedence and does not select Copilot, Cursor, or Pi |
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| `--backend mock\|claude\|codex\|copilot\|cursor\|pi\|handoff\|azure_openai` | Replay/optimizer backend |
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| `--model NAME` | Backend-specific model override |
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| `--cursor-home PATH` | Override `~/.cursor` for Cursor transcript harvesting |
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| `--pi-home PATH` | Parent directory containing Pi's `agent/sessions` tree (default: `~/.pi`) |
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| `--vscode-workspace-storage PATH` | Override VS Code's `User/workspaceStorage` root for Copilot transcript harvesting |
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| `--cursor-path PATH` | Path to the installed Cursor Agent CLI |
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| `--pi-path PATH` | Path to the installed Pi coding-agent CLI |
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| `--preferences TEXT` | House rules supplied to reflection |
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| `--lookback-hours N` | Initial transcript lookback; `0` scans all history |
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| `--max-sessions N` / `--max-tasks N` | Bound the harvested workload |
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| `--target-skill-path PATH` | Explicit skill document to stage/adopt |
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| `--tasks-file PATH` | Replay a reviewed task JSON file instead of harvesting |
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| `--edit-budget N` | Maximum bounded edits for the night |
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| `--progress` / `--json` | Progress or machine-readable output |
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| `--auto-adopt` | Apply an accepted staged proposal automatically |
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The `mock` and `handoff` backends make no network calls. A real backend sends
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mining, replay, judging, and reflection prompts derived from harvested
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transcripts and tasks to its selected provider. Review that provider's
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data-retention and privacy policy before processing sensitive sessions.
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### VS Code GitHub Copilot Chat source
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`--source copilot` reads local VS Code GitHub Copilot Chat session logs from
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the platform's stable and Insiders `User/workspaceStorage` locations, plus the
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portable location when `VSCODE_PORTABLE` is available. Use
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`--vscode-workspace-storage PATH` for a nonstandard root. Each workspace must
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have a readable adjacent `workspace.json` mapping to a local project; unmapped
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windows are skipped so project scoping cannot silently mix unrelated sessions.
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`--source auto` does not select Copilot.
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The harvester retains user-entered prompts, visible assistant Markdown, and
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tool names from requests confirmed as GitHub Copilot Chat. It excludes
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system-initiated notifications, reasoning, tool inputs and outputs, rendered
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context, and account/model metadata. Known secret-shaped strings are redacted
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as defense in depth, but review harvested tasks before sending them to a model
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provider. Transcript harvesting is independent of `--backend copilot`, which
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invokes the GitHub Copilot CLI for model calls.
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The managed `schedule` command does not persist `--source` or
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`--vscode-workspace-storage`. Before scheduling this source, set
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`"transcript_source": "copilot"` and, when needed,
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`"vscode_workspace_storage": "/absolute/path/to/workspaceStorage"` in
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`~/.skillopt-sleep/config.json`.
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### Pi source and backend
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`--source pi` reads local session JSONL files below
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`~/.pi/agent/sessions`; use `--pi-home PATH` to select the parent directory that
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contains `agent/sessions`. This local source does not require the Pi CLI or
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provider authentication. It retains user/assistant text, tool names, and lexical
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feedback found in user text, while excluding thinking, tool arguments, tool
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outputs, images, and unrelated metadata. The absolute project `cwd` from the
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session header is retained for scope filtering and may appear in miner prompts
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sent to a real backend and its provider. Known secret-shaped strings in retained
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message text are redacted as defense in depth, not as a guarantee. Pi is an explicit source: `--source auto`
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retains Codex-then-Claude precedence and does not select it.
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Transcript source and model backend are independent. `--backend pi` launches a
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locally installed, authenticated Pi CLI and makes real provider calls for
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mining, replay, judging, and reflection. Use `--pi-path PATH` to select its
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executable and `--model NAME` to override its configured model:
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```bash
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skillopt-sleep run --project "$(pwd)" \
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--source pi --backend pi --pi-path /absolute/path/to/pi \
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--model provider/model --max-sessions 5 --max-tasks 3 --progress
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```
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For these calls, SkillOpt disables Pi tools, skills, context files, extensions,
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prompt templates, themes, and session writes. Pi authentication and model
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configuration remain available. It also enables Pi's offline startup mode, so
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configured npm/git packages are not installed or updated and model catalogs are
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not refreshed; the selected model provider is still contacted for generation.
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These controls should not be treated as permanent or complete isolation. The
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provider selected in Pi receives the transcript-derived prompts.
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The managed `schedule` command preserves the backend but not `--source`,
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`--pi-home`, `--pi-path`, or `--model`. Before scheduling Pi, put
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`transcript_source`, `pi_home`, `pi_path`, and `model` in
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`~/.skillopt-sleep/config.json`; use an absolute `pi_path` and verify
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authentication for the scheduled account.
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### Cursor source and backend
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`--source cursor` reads local Cursor JSONL transcripts from
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`~/.cursor/projects/<workspace>/agent-transcripts/*/*.jsonl`. Invoked scope uses
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Cursor's recorded workspace path, including when `--project` is a nested
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directory, and falls back to the sanitized storage name when metadata is not
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available. `--scope all` scans every workspace below `cursor_home`. The
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harvester retains user/assistant text, explicit turn errors, and tool names,
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while excluding tool arguments, tool outputs, and non-message records. It
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redacts known secret patterns and filters SkillOpt-generated replay sessions,
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but redaction is not a guarantee that outbound prompts contain no sensitive
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data.
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`--backend cursor` launches an installed, authenticated `cursor-agent`, sends
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prompts over stdin, and parses its JSON result. SkillOpt reads the target skill
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and includes its text in replay prompts; it does not invoke that file as a native
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Cursor skill. Ordinary mining, replay, judging, and reflection calls use
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read-only Ask mode in a new empty temporary workspace. Project file reads, file
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writes, and MCP tools are denied. `--project` does not change that execution
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workspace.
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Cursor tool-aware replay is temporarily disabled pending live Cursor
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permission-boundary validation. A task with a `tool_called` check fails nonzero
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before Agent mode starts and does not stage, adopt, cache, persist state, or
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advance the harvest checkpoint. Use another backend for such tasks. The current
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Cursor backend therefore does not provide end-to-end validation for skills that
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need repository inspection, real CLIs, browsers, running services, or file
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changes.
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There is no implemented fresh-worktree Cursor replay. If a report says
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`replay: mock`, that is the prompt-replay label and does not mean the mock model
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backend was selected. Both `run` and `dry-run` perform real-backend provider
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calls; `dry-run` suppresses staging, adoption, and persisted state changes, not
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spend. Session and task limits do not impose hard provider-call, token, time, or
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monetary budgets.
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Cursor and its selected model provider can receive the prompt content.
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Cursor-specific settings are available through the CLI, config, and environment:
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| Purpose | CLI | `~/.skillopt-sleep/config.json` | Environment |
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| Transcript home | `--cursor-home PATH` | `"cursor_home": "/path/to/.cursor"` | none |
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| Agent executable | `--cursor-path PATH` | `"cursor_path": "/path/to/cursor-agent"` | `SKILLOPT_SLEEP_CURSOR_PATH` |
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| Model | `--model NAME` | `"model": "NAME"` | `SKILLOPT_SLEEP_CURSOR_MODEL` |
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Use `cursor-agent --list-models` to inspect model identifiers available to the
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authenticated account. When cost depends on a model variant, confirm the billed
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variant in Cursor's usage reporting rather than relying only on its display
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name.
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Target the learned project skill explicitly so accepted updates are visible to
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Cursor without modifying the plugin's own `skillopt-sleep` workflow skill:
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```bash
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skillopt-sleep run --project "$(pwd)" \
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--source cursor --backend cursor \
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--target-skill-path .cursor/skills/skillopt-sleep-learned/SKILL.md \
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--max-sessions 5 --max-tasks 3 --progress
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```
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The first harvest uses a 72-hour lookback unless `--lookback-hours` is set. A
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value of `0` considers all available history while still respecting
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`--max-sessions`. A stateful `run`, including a run that mines no tasks, records
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a new harvest checkpoint; subsequent runs use that checkpoint rather than the
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initial lookback. Use `harvest` or `dry-run` to verify counts before the first
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stateful run.
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The managed `schedule` command persists the project, backend, time, and optional
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auto-adopt setting only. It does not copy source, Cursor paths, model, or target
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skill flags into the scheduled command. Put `transcript_source`, `cursor_home`,
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`cursor_path`, `model`, and `target_skill_path` in the user config before
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scheduling Cursor. Keep `target_skill_path` project-relative as
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`.cursor/skills/skillopt-sleep-learned/SKILL.md`, prefer an absolute
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`cursor_path`, and verify authentication for the scheduled account because cron
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and Task Scheduler may have a minimal environment.
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Backend-specific setup for compatible endpoints is documented in
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[OpenAI-compatible endpoints for SkillOpt-Sleep](../sleep/openai-compatible-endpoints.md).
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## WebUI
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```bash
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python -m skillopt_webui.app [--port PORT] [--share]
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```
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| Argument | Default | Description |
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| `--port` | 7860 | Port number |
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| `--host` | `0.0.0.0` | Server bind address |
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| `--share` | false | Create public Gradio link |
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The default host binds every network interface. Use `--host 127.0.0.1` when
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the dashboard should be reachable only from the local machine.
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