skilltotal

<!-- mcp-name: ai.skilltotal/skilltotal -->

# SkillTotal

[![PyPI](https://img.shields.io/pypi/v/skilltotal)](https://pypi.org/project/skilltotal/)
[![Python](https://img.shields.io/pypi/pyversions/skilltotal)](https://pypi.org/project/skilltotal/)
[![License](https://img.shields.io/pypi/l/skilltotal)](LICENSE)
[![CI](https://github.com/pezhik/skilltotal/actions/workflows/ci.yml/badge.svg)](https://github.com/pezhik/skilltotal/actions/workflows/ci.yml)
[![GitHub Marketplace](https://img.shields.io/badge/Marketplace-SkillTotal-2ea44f?logo=githubactions&logoColor=white)](https://github.com/marketplace/actions/skilltotal-ai-component-security-scan)
[![OpenSSF Scorecard](https://api.scorecard.dev/projects/github.com/pezhik/skilltotal/badge)](https://scorecard.dev/viewer/?uri=github.com/pezhik/skilltotal)

**AI Component Security Platform — open-source CLI engine.**

SkillTotal statically analyzes AI-related components — agent skills/plugins, MCP servers, npm /
Python packages, repositories, and **AI-generated projects you upload as an archive or file** — to
surface supply-chain risks, dangerous capabilities, prompt-injection surfaces, and data-exfiltration
paths **before** the component is installed or trusted. Point it at a path, a git URL, an
`npm:` / `pypi:` package, or a project archive (`.zip` / `.tar.gz`) / single file.

**Try it online (no install, no account):** [www.skilltotal.ai](https://www.skilltotal.ai) —
the website runs this same engine. Prefer the CLI? `pipx install skilltotal` (below).

It analyzes **only the component itself** — never your user, company, environment,
deployment, or runtime context. Every score and finding is derived exclusively from the
files inside the component.

> Core principle: **every confirmed finding carries evidence** (file, line range, code
> snippet). Anything that cannot be evidenced is placed in `needs_review`, never in
> `findings`, and never affects the score.

## Why SkillTotal

- **100% local & offline** — the component's code **never leaves your machine**. No account,
  no API token, no cloud upload (unlike cloud scanners that send your components to a backend).
- **Safe to point at untrusted components** — the engine analyzes without ever running them on
  your machine. (Optional dynamic analysis is a separate paid service that runs only in our
  isolated sandbox, with your consent.)
- **Zero runtime dependencies**, pure Python stdlib — auditable and easy to vendor/air-gap.
- **Deterministic** — regex + AST, no LLM in the static engine; the same input always yields
  the same report.
- **Evidence-anchored & low false-positive** — every finding points at an exact file:line.
- **Standards-aligned** — every component gets a behavioral **trait fingerprint** mapped to the
  **Cloud Security Alliance (CSA)** agentic threat model, **MAESTRO** threat-model layers, and
  **MITRE ATLAS** tactics — including a three-way *execution-context* read (embedded static
  credential → delegated OAuth/OIDC → least-privilege scoped identity) that shows the blast radius
  of a compromise, not just that a secret exists.
- **Free and open source** (Apache-2.0) — the full static report is free, forever.

## Install

Requires **Python 3.10+**. Zero runtime dependencies. `git` is required only for scanning
remote URLs.

Recommended for the CLI — [pipx](https://pipx.pypa.io) (isolated install; also works on
Debian/Ubuntu where bare `pip install` is blocked by PEP 668):

```bash
pipx install skilltotal
```

Or into a virtual environment / as a library:

```bash
pip install skilltotal
```

From source (development):

```bash
pip install -e ".[dev]"
```

## Usage

```bash
# Human-readable report
skilltotal scan ./path/to/component

# Scan a remote repository (shallow git clone)
skilltotal scan https://github.com/owner/repo

# Scan a project archive or a single file (e.g. an AI-generated project downloaded as a ZIP)
skilltotal scan ./my-project.zip
skilltotal scan ./app.tar.gz
skilltotal scan ./suspicious.py

# Scan a package from a registry (latest, or a pinned version)
skilltotal scan npm:left-pad
skilltotal scan npm:left-pad@1.3.0
skilltotal scan pypi:requests
skilltotal scan pypi:requests==2.31.0

# JSON to stdout
skilltotal scan ./component --json

# SARIF 2.1.0 (GitHub Code Scanning / IDE)
skilltotal scan ./component --sarif --output report.sarif

# Write the report to a file (SARIF if --sarif, else JSON)
skilltotal scan ./component --output report.json

# CI gate: exit code 2 by severity level or by risk score
skilltotal scan ./component --fail-on-high             # alias for --fail-on high
skilltotal scan ./component --fail-on medium
skilltotal scan ./component --fail-on-score 50

# Skip paths (repeatable; combined with the config file's `exclude`)
skilltotal scan ./component --exclude "vendor/*" --exclude "*.min.js"

# Opt-in provenance for npm:/pypi: sources (registry metadata -> needs_review, never scored)
skilltotal scan npm:some-lib --provenance

# Baseline: snapshot current findings, then suppress them on later scans
skilltotal scan ./component --write-baseline .skilltotal-baseline.json
skilltotal scan ./component --baseline .skilltotal-baseline.json --fail-on-high

# Diff two versions of a component: what changed between them?
# Each side is any scannable source (path/archive/git/npm:/pypi:) or a saved --json report.
skilltotal diff npm:some-lib@1.2.3 npm:some-lib@1.2.4
skilltotal diff ./old-checkout ./new-checkout --json
skilltotal diff old-report.json new-report.json
# CI gate: fail (exit 2) if the new version INTRODUCES a high/critical finding
skilltotal diff npm:some-lib@1.2.3 npm:some-lib@1.2.4 --fail-on-new high

# Pre-install guard: allow/block decision (exit 2 on block) you can chain before installing
skilltotal guard npm:some-mcp-server && claude mcp add some-mcp-server -- npx some-mcp-server
skilltotal guard --installed            # check every AI component already on this machine
skilltotal guard npm:x --block-on malicious   # block only on malicious indicators

# Inventory: discover AI components already installed on this machine and scan them
# (reads agent configs for Claude Desktop/Code, Cursor, Windsurf, VS Code, Gemini, and
#  local skills; derives an npm:/pypi:/local source per MCP server and runs the engine)
skilltotal inventory
skilltotal inventory --json
skilltotal inventory --no-scan          # list only, do not scan
skilltotal inventory --project .        # also include this project's agent configs
skilltotal inventory --sbom             # AI-BOM: CycloneDX 1.6 JSON of your agent stack,
                                        # scan verdicts attached as component properties

# List every detection rule
skilltotal rules list
skilltotal rules list --json
```

**Baseline** suppresses findings by a stable fingerprint of
`(rule id, file, code snippet)` — independent of line numbers, so it survives edits.
Suppressed findings are removed before scoring and do not affect the risk score.

**Diff** reports new / resolved / changed findings, evidence-level additions and removals
(matched by the same line-independent fingerprint as the baseline, so pure line shifts are
not noise), capability changes, and the risk-score delta. `--fail-on-new LEVEL` gates only
on risk the new version *introduces* — existing accepted findings never trip it, so it fits
upgrade reviews ("is 1.2.4 riskier than the 1.2.3 we already vetted?") without a baseline
file.

**Guard** is the install-time answer to "should I trust this component right now?".
Malicious indicators always block; scored risk at/above `--block-on` blocks;
**capabilities alone never block** — a legitimate MCP server with shell/network access
passes, so the guard stays quiet enough to leave enabled everywhere (unlike a raw
`--fail-on high` gate, which would trip on most of the ecosystem's honest capability
findings).

**Provenance** (`--provenance`, opt-in) adds registry-metadata signals for `npm:` /
`pypi:` sources: *recently published*, *deprecated / yanked*, *no recent releases*, *no
repository link*. Metadata is context about a component, not component content — so these
signals go to `needs_review` and **never** affect the score or verdict, and the default
scan stays 100% component-only and offline.

**Project config** (optional) — commit a `.skilltotal.toml` instead of repeating flags
(CLI flags override it):

```toml
fail_on = "high"           # low | medium | high | critical
fail_on_score = 50         # or gate on the 0-100 risk score
exclude = ["vendor/*", "*.min.js"]
ignore = ["ST-NET-PY"]     # rule ids to drop
baseline = ".skilltotal-baseline.json"

# Per-rule policy: reviewable gate decisions that live in the repo, not in a dashboard.
[policy]
"ST-SHELL-PIPE-EXEC" = "block"   # gate trips (exit 2) whenever this rule fires,
                                 # even with no fail_on configured
"ST-DYN-PY" = "warn"             # explicit accept-but-show: reported, still counts toward
                                 # the risk score, but exempt from the fail_on severity gate
"ST-SENS-WORD" = "ignore"        # suppressed entirely (same effect as `ignore`)
```

Suppress a single finding inline with a `# skilltotal:ignore` (or `# skilltotal:ignore[ST-ID]`)
comment on its line.

`python -m skilltotal ...` works identically to the `skilltotal` console script.

### Exit codes

| Code | Meaning |
|------|---------|
| 0 | Success |
| 1 | Usage / collection error (e.g. path missing, clone failed) |
| 2 | A configured gate tripped (`--fail-on`/`--fail-on-high` severity, `--fail-on-score`, or `diff --fail-on-new`) |

> **Gate semantics:** `--fail-on`/`--fail-on-high` trip on the **severity of any single finding**,
> not the aggregate `risk_score`. A component can report `risk_level: low` (score 0) and still fail
> the gate if it has a high-severity finding — including a powerful *capability* (e.g. shell or
> network access), which is reported but never scored as malicious. To gate on the score instead,
> use `--fail-on-score`