Drive Tui

drive-tui

Drive interactive terminal programs the way a human does: look at the screen, decide, press keys, wait, look again. A normal subprocess/pipe can't do this — line-buffered pipes hide menus, spinners, and prompts, and many programs refuse to run without a real TTY. This skill uses smartcli_core (a PTY + pyte screen model + semantic snapshots + readiness waits) behind a thin CLI, scripts/tui.py.

When to use

• Launching a program that draws a full-screen or line-mode UI and expects keystrokes (REPLs, installers, vim, agent CLIs, arrow-key menus, y/n prompts, password entry).
• A piped command hangs, prints nothing, or says "not a terminal".
• You need to see what an interactive program is showing right now, then act on it.
• Do NOT use for non-interactive commands whose full output you just want captured — run those directly.

Core mental model: the perceive → decide → act loop

Never fire keystrokes blind and never guess with sleep. Every interaction is one turn of this loop:

1. Perceive — take a snapshot. Read the header line (cursor position, selected row, status bar, errors) and the row-numbered body.
2. Decide — classify the screen: is it a menu, a text prompt, a confirmation, a spinner still loading, an error, or a finished result? Decide the single next action.
3. Act — translate intent into key tokens and send them (send-line, send-text, or keys).
4. Wait — call wait / wait-regex. NEVER sleep. The wait pumps output until the screen settles or an expected marker appears.
5. Confirm — re-snapshot and verify the screen changed as expected before the next action.

Setup

scripts/tui.py adds the repo root to sys.path itself, so run it from anywhere. It needs smartcli_core importable (default: three levels up from the script) and the deps pyte + pywinpty (Windows) already installed. Override the repo location with SMARTCLI_ROOT if needed.

All commands below are shown from the repo root. Use the exact form: python skills/drive-tui/scripts/tui.py ...

Two ways to drive

A. Persistent session (interactive, multi-turn) — the default

A detached daemon owns one live program; each command connects over a localhost-only socket, so state survives across separate shell calls. This is the real perceive→decide→act loop.

1. Start (prints a session id — capture it):

python skills/drive-tui/scripts/tui.py start --cmd "python" --cols 100 --rows 30

1. Wait for the first prompt, then snapshot is printed automatically:

python skills/drive-tui/scripts/tui.py wait-regex --id ">>> " --timeout-ms 15000

1. Act, then wait, then it re-snapshots:

python skills/drive-tui/scripts/tui.py send-line --id "print(6*7)" python skills/drive-tui/scripts/tui.py wait --id

1. Snapshot any time without acting:

python skills/drive-tui/scripts/tui.py snapshot --id Add --json for the structured Snapshot.to_json() form (selected span, menu_items, errors).

1. Check liveness / list / close:

python skills/drive-tui/scripts/tui.py alive --id (exit 0 alive, 1 dead) python skills/drive-tui/scripts/tui.py list python skills/drive-tui/scripts/tui.py close --id (always close when done)

Subcommands: start, snapshot, send-text, send-line, keys, wait, wait-regex, alive, close, list. wait/wait-regex print liveness + reason to stderr and the snapshot to stdout.

B. One-shot script (batch, non-interactive)

When you already know the whole sequence, run it in a single process against a fresh program. No session to manage. Write a JSON list of steps to a file and run: python skills/drive-tui/scripts/tui.py run --cmd "python" --steps steps.json --cols 100 --rows 30

Step objects (executed in order; each wait_*/snapshot prints a snapshot):

• {"action":"send_text","text":"..."} — type literally, no Enter.
• {"action":"send_line","text":"..."} — type + Enter.
• {"action":"send_keys","keys":["Down","Down","Enter"]} — key tokens.
• {"action":"wait_ready","marker":"regex"} — wait for marker OR stability (marker optional).
• {"action":"wait_regex","pattern":"regex","timeout_ms":10000} — wait strictly for the regex.
• {"action":"snapshot"} — print the current screen.

Reading a snapshot

to_text() output = one header line + row-numbered body:

[screen 24x80] cursor=r3c4  selected=r3[0:80]">>>"(cursor_line)  status="..."  errors=1
  0 | Python 3.14.6 ...
  3 | >>>

• Header: cursor=rNcM, optional selected=..., status="...", title, errors=N, screen_reverse.
• Body: | text. A * marks a selected/highlighted row. Blank runs collapse to ....
• selected_line is the key menu signal. In an arrow-key menu the highlighted (reverse-video / colored) row is the current choice — the snapshot surfaces it as the * row and in the header selected. Use it to know where the cursor sits before pressing Up/Down.

Deciding: classify the screen

• Prompt (>>> , $ , Password:, Continue? [y/N]) → send the answer with send-line, or a single key with keys.
• Menu (a */selected row, list of options) → move with keys Up/keys Down, choose with keys Enter. Do not type the option text.
• Spinner / progress / still loading → do not act; call wait again (it caps at max_wait_ms and returns the last screen).
• Error (errors=N in header, red text, "Traceback"/"failed") → stop and read; do not keep sending input.
• Finished result → capture the snapshot; act or close.

Translating intent to keys (keys subcommand / send_keys)

Named tokens: Enter Tab BackTab Space Backspace Delete Escape Up Down Left Right Home End PageUp PageDown Insert F1–F12. Combos: C-c / ^C (Ctrl+C), M-x (Alt+x). Anything else is sent literally.

• Menus/keys → keys. Free text + submit → send-line. Text without submit (fills a field) → send-text.
• send-line submits with \r. A raw-mode app that needs \n → use send-text "...\n".

Choosing the right wait — do NOT sleep

• Know the exact text that means "ready" (a prompt, a banner) → wait-regex . Prefer this. It watches strictly for the regex and will NOT return early.
• Don't know the marker (screen just needs to settle after a keystroke) → wait (marker optional): returns on stability or a marker, capped by timeout.
• Startup gotcha: a program can sit quiet for seconds before its banner appears (Python's REPL banner arrives ~3s after spawn on Windows ConPTY). Plain wait/wait_ready may declare STABLE on the still-blank screen during that gap. So for the FIRST prompt after start, use wait-regex with a generous --timeout-ms (e.g. 15000), not bare wait.
• Regex tips: match against the whole screen text. Anchoring with $ needs multiline semantics — prefer a loose marker like ">>> " over ">>> $". Confirm the result with a follow-up snapshot.

Recovering when a program doesn't respond

1. Re-snapshot — confirm it actually didn't change (you may have missed output).
2. alive --id — if dead, the child exited; read the final snapshot for the reason, then close.
3. Still alive but stuck: try keys Enter (dismiss a pager/prompt) or keys Escape (leave a mode).
4. Interrupt a running command: keys C-c. Windows caveat: under ConPTY a raw Ctrl-C byte does NOT reliably raise an interrupt in a line-mode child (verified — time.sleep in the Python REPL was not interrupted). On Windows, if C-c fails, the reliable recovery is close --id and start a fresh session. On POSIX, C-c works normally.
5. Always close sessions you started (frees the daemon and the child).

Constraints / gotchas

• Never blind-sleep to wait for output — use wait / wait-regex; they pump the PTY and have hard timeouts.
• Always re-snapshot after acting; the snapshot before your keystroke is stale.
• Navigation sequences are standard xterm/VT100 (normal cursor mode). An app in application-cursor-keys mode may need different Up/Down bytes — if arrows don't move the selection, re-snapshot and try keys Down once more or use the app's letter/number shortcuts.
• The daemon binds 127.0.0.1 only — local process control, no network exposure.
• Paths above are relative to this skill's folder; run the script by its path from the repo root.
• Deeper API details: read references/core_api.md only when you need field-level specifics.

Knowledge base — look before you build

Before scripting a new interaction or pattern, consult the SmartCLI knowledge graph at D:/Project/SmartCLI/knowledge/INDEX.md. Its tui-patterns/ domain is a 1:1 conceptual map of the 8 recipes below — [[list-menu-navigation]], [[fuzzy-search-filter]], [[pager-navigation]], [[confirm-yes-no-dialog]], [[progress-spinner-waiting]], [[form-field-input]], [[repl-session]], [[wizard-installer-flow]] — plus the sourced foundations behind every gotcha in this skill: [[application-cursor-mode]] (the exact arrow-keys-don't-move bug), [[quiescence-detection]] and [[snapshot-stability-hash]] (how wait decides "settled"), [[key-encoding-reference]] (key tokens → bytes), [[cursor-row-binding]] and [[verify-movement-step-by-step]] (why matches bind to the cursor row and every action re-snapshots). Read the relevant note before inventing a recipe from scratch.

Pattern library — classify a screen, drive it with a recipe

Above is the manual loop through scripts/tui.py. For recurring paradigms there is a Python pattern library (skills/drive-tui/patterns/) that recognizes a screen and drives it for you. It works on smartcli_core Snapshot/PtySession objects, so use it from Python (import patterns), not the tui.py CLI. Add skills/drive-tui to sys.path, or run from there.

Classify / explain a screen

• classify(snapshot, threshold=0.05) -> [(Pattern, confidence), ...] — every registered pattern scored 0..1 against the snapshot, highest first. A pattern whose matches() raises is scored 0, never poisoning the ranking.
• explain(snapshot) -> str — a human/agent-readable description: raw facts (size, cursor, highlighted row + reason, menu spans, status bar, errors, screen-reverse) followed by the ranked paradigms with confidences.

import sys; sys.path.insert(0, "skills/drive-tui")
from patterns import registry
from patterns.classify import classify, explain

snap = session.snapshot()          # a smartcli_core PtySession
print(explain(snap))               # what does this screen look like?
best, conf = classify(snap)[0]     # top paradigm

The 8 recipes (registry names → tags)

Live catalog: [p.name for p in registry.all_patterns()].

| name | drives | intent | tags | |------|--------|--------|------| | repl | interactive REPL/shell prompt | one code line to run | repl, shell, prompt, interactive | | menu_select | arrow-key vertical menu | int index or substring | menu, list, navigation | | pager | less/more/man/git-log | to_end / next_page / search: | pager, scroll | | search_filter | fzf / Ctrl-R / palette | the query string | fuzzy, filter, incremental | | confirm | [y/N] / (yes/no) dialog | bool (or yes/no string) | dialog, yesno | | form | labelled input fields | dict/list/str of field values | form, input | | progress | spinner / progress bar | optional completion regex | spinner, progress, wait | | wizard | multi-step installer | list of per-step actions | wizard, multistep, installer |

Call a recipe

Get the registered singleton and call .drive(session, intent, **kw). It runs the perceive→act→wait→confirm loop against the live session and returns a PatternResult(ok, detail, snapshot, data) — ok is a real screen assertion, snapshot is the last screen as evidence, data is the pattern-specific payload.

from patterns import registry

# REPL: run a line, confirm a fresh prompt returned + cursor advanced
res = registry.get("repl").drive(session, intent="6*7")
assert res.ok; print(res.data["output"])          # ['42']

# menu: move the highlight to a target and press Enter (confirms the bar moved)
registry.get("menu_select").drive(session, intent="Charlie")   # or intent=2
registry.get("menu_select").drive(session, intent=0, press=False)  # position only

# pager: page to the bottom
registry.get("pager").drive(session, intent="to_end", max_pages=200)

# search: narrow a fuzzy list, then pick the top match
registry.get("search_filter").drive(session, intent="grapef", stop_at=1, accept=True)

# confirm: answer yes (commits with Enter if a line-mode child only echoed)
registry.get("confirm").drive(session, intent=True)

# form: fill fields, Tab between, Enter to submit
registry.get("form").drive(session, intent={"Name": "Ada", "Email": "a@b.c"})

# progress: wait for a done marker, else for the animation to settle (hard ceiling)
registry.get("progress").drive(session, intent=r"DONE!", max_wait_ms=60000)

# wizard: drive a scripted multi-step flow
registry.get("wizard").drive(session, intent=[
    {"keys": ["Down", "Enter"]}, {"pattern": "confirm", "value": True}, None])

Module-level convenience helpers: patterns.recipes.repl_session.run_line(session, code, **kw) and patterns.recipes.paginate.read_all(session, max_pages=200, key="Space") -> (text, PatternResult) (accumulates the pager's full text across pages, dedup'ing repainted boundary rows).

Recipe drive kwargs worth knowing:

• repl: expect= (confirm a marker instead of waiting for STABLE), timeout_ms, quiet_ms, min_wait_ms.
• menu_select: max_steps, settle_ms, press (send Enter, default True), enter_wait_ms.
• pager: max_pages, key (Space|PageDown|f, default Space; f is the less/more forward-page key).
• search_filter: incremental (default True), stop_at (match-count threshold, default 1), accept (Enter to pick), settle_ms.
• form: next_key (default Tab), submit (default Enter); intent may be a dict, a list of (label, value), or a single string.
• progress: max_wait_ms, quiet_ms (pure observer, sends no keys; returns timeout rather than a false complete if it never settles).
• wizard: advance_key (default Enter), max_steps. Each intent item is {"pattern": name, "value": intent}, {"keys": [...]}, or None/{} for auto (classify + best recipe, fallback advance_key).

Recipes fail loud on bad params (empty/mistyped intent raises ValueError) rather than doing something silently wrong.

Add a NEW pattern

Drop one module in patterns/recipes/ — pkgutil auto-imports it and @register wires it into all_patterns/classify. A module that fails to import is logged (stderr + registry.load_errors()) and skipped; it never breaks the rest of the catalog. Avoid import-time side effects that can't fail-soft.

Contract (patterns/base.py):

• Subclass Pattern; set name (lowercase, unique), description, tags.
• matches(self, snapshot) -> float (0..1): cheap, no side effects. Bind signals to the CURSOR ROW and cell attributes (selected, menu_items, status_bar) — NOT bare body text, since prompts and [y/N] strings also echo in scrollback. Use the helpers Pattern.cursor_row_text(snap), Pattern.last_rows_text(snap, n), Pattern.visible_text(snap), Pattern.rx(pat, text, flags).
• drive(self, session, intent=None, **kw) -> PatternResult: perceive→act→wait→confirm. NEVER blind-sleep; always re-snapshot after acting; always bound waits (wait_stable/wait_for with a hard ceiling). Return PatternResult(ok, detail, snapshot=, data={...}) where ok is asserted from the screen.
• Decorate with @patterns.registry.register above the class.

from smartcli_core import PtySession, Snapshot
from patterns.base import Pattern, PatternResult
from patterns import registry

@registry.register
class TabBar(Pattern):
    name = "tabbar"
    description = "a top tab bar; switch tabs with the arrow/Tab keys."
    tags = ("tabs", "navigation")

    def matches(self, snap

…

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [dwgx](https://github.com/dwgx)
- **Source:** [dwgx/SmartCLI](https://github.com/dwgx/SmartCLI)
- **License:** MIT

Install and usage instructions live in the source repository linked above.