On Windows 10/11 without Python installed from the Microsoft Store, the
"App Execution Alias" stubs at %LOCALAPPDATA%\Microsoft\WindowsApps\python.exe
and python3.exe are symlinks to AppInstallerPythonRedirector.exe. These
stubs neither launch Python nor honor `-c`; calls print a bare "Python "
line and exit, silently breaking every JSON-parsing step in observe.sh.
Net effect: observations.jsonl is never written, CLV2 appears installed
correctly, and the only residual artifact is `.last-purge`.
This commit:
1. Adds `_is_windows_app_installer_stub` helper that detects the stub
via `command -v` output and optional `readlink -f` resolution.
2. Teaches `resolve_python_cmd` to skip stub candidates and fall
through to the next real interpreter (typically C:\...\Python3xx\python.exe).
3. Exports the stub-aware CLV2_PYTHON_CMD before sourcing
detect-project.sh, which already honors an already-set value,
so the shared helper does not re-resolve and re-select the stub.
POSIX-compatible. No behavior change on macOS / Linux / WSL where no
such stub exists.
Refs: observations.jsonl empty on Windows Claude Desktop users.
* fix(gateguard): rewrite routineBashMsg to use fact-presentation pattern
The imperative 'Quote user's instruction verbatim. Then retry.' phrasing
triggers Claude Code's runtime anti-prompt-injection filter, deadlocking
the first Bash call of every session. The sibling gates (edit, write,
destructive) use multi-point fact-list framing that the runtime accepts.
Align routineBashMsg with that pattern to restore the gate's intended
behavior without changing run(), state schema, or any public API.
Closes#1530
* docs(gateguard): sync SKILL.md routine gate spec with new message format
CodeRabbit flagged that skills/gateguard/SKILL.md still described the
pre-fix imperative message. Update the Routine Bash Gate section to
match the numbered fact-list format used by the new routineBashMsg().
Two bugs in skills/continuous-learning-v2/scripts/detect-project.sh that
silently split the same project into multiple project_id records:
1. Locale-dependent SHA-256 input (HIGH)
The project_id hash was computed with
printf '%s' "$hash_input" | python -c 'sys.stdin.buffer.read()'
which ships shell-locale-encoded bytes to Python. On a system with a
non-UTF-8 LC_ALL (e.g. ja_JP.CP932 / CP1252) the same project root
produced a different 12-char hash than the UTF-8 locale would produce,
so observations/instincts were silently written under a separate
project directory. Fixed by passing the value via an env var and
encoding as UTF-8 inside Python, making the hash locale-independent.
2. basename cannot split Windows backslash paths (MEDIUM)
basename "C:\Users\...\ECC作成" returns the whole string on POSIX
bash, so project_name was garbled whenever CLAUDE_PROJECT_DIR was
passed as a native Windows path. Normalize backslashes to forward
slashes before calling basename.
Both the primary project_id hash and the legacy-compat fallback hash
are updated to use the env-var / UTF-8 approach.
Verified: id is stable across en_US.UTF-8, ja_JP.UTF-8, ja_JP.CP932, C,
and POSIX locales; Windows-path input yields project_name=ECC作成;
ASCII-only paths regress-free.
P2: Description now says "Edit/Write/Bash (including MultiEdit)"
instead of listing MultiEdit as a separate top-level gate
P2: Write Gate and Anti-Patterns now use same "redacted or synthetic
values" wording as Edit Gate (was still "cat one real record")
All 3 gate doc sections now consistent. 9/9 tests pass.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
P1: Gate message asked for raw production data records — changed to
"redacted or synthetic values" to prevent sensitive data exfiltration
P2: SKILL.md description now includes MultiEdit (was missing after
MultiEdit gate was added in previous commit)
P2: Session key pruning now caps __prefixed keys at 50 to prevent
unbounded growth even in theoretical edge cases
9/9 tests pass.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
A PreToolUse hook that forces Claude to investigate before editing.
Instead of self-evaluation ("are you sure?"), it demands concrete facts:
importers, public API, data schemas, user instruction.
A/B tested: +2.25 quality points (9.0 vs 6.75) across two independent tasks.
- scripts/hooks/gateguard-fact-force.js — standalone Node.js hook
- skills/gateguard/SKILL.md — skill documentation
- hooks/hooks.json — PreToolUse entries for Edit|Write and Bash
Full package with config: pip install gateguard-ai
Repo: https://github.com/zunoworks/gateguard
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
