pyrtkai 0.1.0

CLI proxy and output filtering for AI agents: safe subprocess execution, rewrite hooks, policy gate, local gain metrics

PyRTKAI

PyRTKAI reduces CLI noise in AI agent workflows: a Python-based command proxy, conservative rewrite decisions, and output filtering to cut wasted context. The focus is inspectable code, explicit safety defaults (no shell in the proxy path, fail-closed policy), and testability.

Goals

• Python-only deployment and straightforward security review of the codebase.
• First-class Cursor integration via integrations/cursor-plugin/ with doctor / verify-hook.
• Predictable behavior over chasing maximum command coverage in a single release.

Key ideas

1. Local execution only. The proxy runs commands without a shell to avoid accidental interpretation of shell metacharacters.
2. Conservative rewrite. If the input command looks risky (unbalanced quotes, heredocs, shell operators outside quotes), PyRTKAI returns a skip decision.
3. Fail closed policy gate. Policy parsing and matching are designed so that misconfiguration defaults to denial.
4. Structured output preservation. JSON and NDJSON outputs pass through unchanged to keep downstream parsing valid.
5. Token waste reduction. Text outputs can be truncated deterministically with a configurable marker.

Installation

The installed command is pyrtkai (Python 3.11+).

From PyPI (typical users)

python3 -m venv .venv
.venv/bin/pip install -U pip
.venv/bin/pip install pyrtkai
.venv/bin/pyrtkai --help

If pip install pyrtkai fails (name not on PyPI yet), use From a source clone below until the first release is published.

Activate the venv or call .venv/bin/pyrtkai directly. If pyrtkai is not on the PATH Cursor uses, set PYRTKAI_PYTHON to your venv’s python (absolute path).

PEP 668: On many Linux distributions, pip install into the system Python fails with externally-managed-environment. Use a venv (as above), pipx, or another dedicated environment—not sudo pip unless you understand the risks.

From a source clone (contributors, Cursor plugin dev)

Use a venv in the repository root and an editable install:

cd /path/to/PyRTKAI
python3 -m venv .venv
.venv/bin/pip install -U pip
.venv/bin/pip install -e .
.venv/bin/pyrtkai --help

Cursor hook: set PYRTKAI_PYTHON to .venv/bin/python (absolute path) so IDE hooks use the same interpreter.

Cursor plugin bundle

A Cursor Marketplace–style layout (manifest, hooks/hooks.json, shell wrapper) lives under integrations/cursor-plugin/. See that directory’s README for PYRTKAI_PYTHON, merging into ~/.cursor/hooks.json, and either pip install pyrtkai or an editable install from this repo.

Usage

Run pyrtkai --help and pyrtkai <subcommand> --help for the full CLI.

Area	Commands
Health / config	doctor [--json], config [--json]
Core	rewrite <words…> (rewrite decision), proxy <argv…> (run command with filtering)
Cursor hook	hook (stdin/stdout JSON), verify-hook [--json]
Metrics	gain summary, gain export, gain history (optional --json, --limit); gain project [--root PATH]
Benchmark	bench proxy --iters N [--json] -- <argv…>

Examples:

• pyrtkai doctor --json
• pyrtkai config --json
• pyrtkai rewrite git status
• pyrtkai proxy git status
• pyrtkai hook reads hook JSON from stdin and writes the adapted JSON response to stdout.
• pyrtkai verify-hook --json verifies the SHA-256 integrity baseline for the installed hook script (when using the Cursor bundle).
• pyrtkai gain summary --json
• pyrtkai gain export --limit 1000
• pyrtkai bench proxy --iters 5 --json -- python3 -c "print(1)"

Doctor and config

pyrtkai doctor checks local health:

• whether the hook script integrity baseline matches
• whether a hooks.json file exists
• whether hooks.json is configured to call the expected hook script
• which MVP rewrite rules are currently enabled

The doctor --json output includes:

• hook_integrity.ok
• hook_integrity.hook_path / hook_integrity.baseline_path (which files were checked)
• hooks_json.present
• hooks_json.configured
• mvp_rewrite_rules
• output_filter.profile
• output_filter.max_chars

pyrtkai config is a lightweight command for inspecting the enabled MVP rewrite rules:

• pyrtkai config --json

Configuration

Full reference: docs/environment-variables.md (all PYRTKAI_* variables in one place).

Environment variables control the rewrite allow list, output truncation, and policy gating.

MVP rewrite enable flags:

• PYRTKAI_MVP_ENABLE_GIT_STATUS (default true)
• PYRTKAI_MVP_ENABLE_LS (default true)
• PYRTKAI_MVP_ENABLE_GREP (default true)
• PYRTKAI_MVP_ENABLE_RG (default true)

Any of these values disable the rule:

• 0
• false
• no
• off

Output filtering:

• PYRTKAI_OUTPUT_MAX_CHARS integer >= 0 (default 4000)
• PYRTKAI_TRUNC_MARKER marker string (default contains a truncation marker)
• PYRTKAI_OUTPUT_FILTER_PROFILE (default truncating)

Policy gate deny patterns:

• PYRTKAI_DENY_REGEXES comma-separated regex patterns
• PYRTKAI_DENY_REGEX single regex
• PYRTKAI_DENY_REGEX_MAX_INPUT_CHARS (default 65536): if the original or rewritten command string exceeds this length while deny patterns are configured, the policy gate denies (fail-closed). Mitigates pathological regex cost on huge commands; increase only if needed.

Limits (doctor and policy)

• pyrtkai doctor reads ~/.cursor/hooks.json only if its size is at most 1 MiB. Larger files are treated as present but not parsed, so hooks_json.configured may stay false even when the file exists.
• With PYRTKAI_DENY_REGEXES / PYRTKAI_DENY_REGEX set, very long commands are subject to PYRTKAI_DENY_REGEX_MAX_INPUT_CHARS (see above).

Gain tracking (local SQLite)

When PYRTKAI_GAIN_ENABLED=1, events are stored under PYRTKAI_GAIN_DB_PATH (default ~/.pyrtkai/gain.sqlite). Older rows are pruned using PYRTKAI_GAIN_RETENTION_DAYS (default 30). Treat the DB path like any local credential store: use a user-writable directory you trust; do not point it at world-writable locations in multi-user setups.

CLI: pyrtkai gain with no subcommand (summary / export / history) behaves the same as pyrtkai gain summary: both print the aggregated summary (JSON if --json). Use explicit subcommands when you want export/history or separate --limit on summary.

Understanding savings (amount and percent)

PyRTKAI does not call a model tokenizer. It estimates “tokens” from character counts of stdout/stderr (default: one token ≈ four characters, overridable with PYRTKAI_CHARS_PER_TOKEN). That makes numbers stable and comparable across runs, but they are not identical to provider tokenizer counts.

After commands run through pyrtkai proxy, read totals with:

PYRTKAI_GAIN_ENABLED=1 pyrtkai gain summary --json

Field	Meaning
tokens_before	Estimated tokens that would correspond to the full captured stdout+stderr before filtering (pass-through or truncated).
tokens_after	Estimated tokens in what was actually printed after filtering (e.g. shorter text if truncation applied).
tokens_saved_est	tokens_before − tokens_after. The “amount” of estimated savings (larger ⇒ more characters removed by the filter).
tokens_saved_pct_est	100 × tokens_saved_est / tokens_before, rounded to two decimals. Share of estimated output “trimmed” relative to the pre-filter size. null when there is nothing to compare (e.g. empty DB or tokens_before is 0).

Per-command groupings live under by_classification (same fields per group, including tokens_saved_pct_est).

How to read it: use tokens_saved_est for a rough quantity of reduction; use tokens_saved_pct_est to see how large that reduction was relative to the original output size (e.g. 50% means about half of the estimated pre-filter volume was not printed after filtering). Short runs with little or no truncation often show 0 saved and 0% (or null percent when there is no baseline).

Known limitations (heuristics and deny-regex)

• Rewrite registry skips MVP rewrite if the command string contains substrings such as --json, --format, or --template anywhere (conservative; may skip in edge cases such as odd paths).
• Proxy streaming treats output that begins (after whitespace) with { or [ as JSON pass-through; rare text that looks like JSON at the start will not be truncated.
• Deny regexes (PYRTKAI_DENY_REGEXES): input length is capped (see Limits), but a regex with catastrophic backtracking can still be expensive on worst-case input within that cap. Prefer simple patterns; for stricter isolation run hooks in a resource-limited environment.

Security posture

PyRTKAI is designed to avoid unsafe shell behavior by default:

• pyrtkai proxy executes commands without invoking a shell
• rewrite decisions are conservative and skip risky patterns
• JSON and NDJSON outputs are preserved to avoid breaking structured tool responses
• policy parsing is fail closed (invalid deny configuration denies)

The project uses defense-in-depth checks in CI, including:

• ruff
• mypy
• bandit
• pip-audit

License: MIT. Reporting security issues: see SECURITY.md.

Contributing

• Roadmap: product direction and ecosystem watch list — docs/product-roadmap.md.
• Forks: if your canonical GitHub repository is not the one listed in [project.urls] inside pyproject.toml, update those URLs so PyPI and metadata point to your repo.
• Pull requests: run the same checks as CI before pushing: make test, make lint, make typecheck, and make security (or the individual pytest / ruff / mypy / bandit / pip-audit commands). Optionally run python -m build to verify wheels/sdists.
• Commits: large documentation-only changes (e.g. under .doc/) can be split from code commits if you want a clearer history—optional, not required.

Development and testing

Common commands:

• make test
• make lint
• make typecheck
• make security (same tools as CI when ruff, mypy, bandit, and pip-audit are installed)

Direct checks:

• pytest
• ruff check src tests
• mypy src tests
• bandit -r src -q (application code; tests use subprocess intentionally in harnesses)
• pip-audit or pip-audit --skip-editable (for a local editable install, PyPI may not resolve the package name and pip-audit can report Skip Reason: Dependency not found on PyPI — that is expected; CI uses a normal install from the repo)

Optional: bandit on tests

To scan tests/ with relaxed skips (assert/subprocess/random in harnesses), use the bundled config:

• bandit -c bandit-tests.yaml -r tests -q

Performance SLO (optional)

Loose proxy-overhead checks live in tests/test_performance_slo.py. Local run:

PYRTKAI_ENFORCE_PERF_SLO=1 pytest -q tests/test_performance_slo.py

Profiling slow deny-regex / hook paths (optional)

PyRTKAI does not ship a regex timeout. If policy matching feels slow, simplify PYRTKAI_DENY_REGEXES, reduce pattern complexity, or profile locally, e.g. python -m cProfile -m pyrtkai.cli rewrite 'your command string' and inspect hotspots.

Example: token economy (gain)

With an editable venv install, enable gain and point the DB to a temp file, run a proxy command that prints more characters than PYRTKAI_OUTPUT_MAX_CHARS (default 4000), then inspect estimated token savings:

python3 -m venv .venv
.venv/bin/pip install -e .
export PYRTKAI_GAIN_ENABLED=1
export PYRTKAI_GAIN_DB_PATH=/tmp/pyrtkai_gain_demo.sqlite
rm -f /tmp/pyrtkai_gain_demo.sqlite

.venv/bin/pyrtkai proxy python3 -c "print('x'*12000)" >/dev/null
.venv/bin/pyrtkai gain summary --json

On a typical run (default PYRTKAI_CHARS_PER_TOKEN=4, default max chars 4000), JSON output is similar to: tokens_before ≈ 3000, tokens_after ≈ 1000, tokens_saved_est ≈ 2000 — exact numbers depend on your environment and truncation. Use pyrtkai bench proxy --iters 5 <command...> to measure proxy overhead (latency ratio vs direct subprocess); ratios vary by machine.

Gain DB inside this repo (local only)

To keep metrics under the project tree (ignored by git via .pyrtkai/ in .gitignore):

export PYRTKAI_GAIN_ENABLED=1
export PYRTKAI_GAIN_DB_PATH="$PWD/.pyrtkai/gain.sqlite"
pyrtkai proxy <command...>   # or: PYTHONPATH=src python3 -m pyrtkai.cli proxy ...
pyrtkai gain summary --json
pyrtkai gain export --limit 500

Replace pyrtkai with .venv/bin/pyrtkai if you use a venv. Only commands run through proxy while gain is enabled are recorded.