Sast logo

Sast

Organization
Rune-kit
sast

Static analysis tool runner. Wraps ESLint, Semgrep, Bandit, Clippy, and language-specific analyzers with unified severity output. Use when deeper code analysis needed beyond pattern matching.

Overview

PublisherRune-kit
Repositoryrune
Skill namesast
Stars
88
Forks
26
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Rune-kit on GitHub. Read the source before you install it.

Installation

Install the Sast AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Rune-kit/rune/tree/master/skills/sast
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Rune-kit/rune.git /tmp/rune
mkdir -p .claude/skills
cp -r /tmp/rune/skills/sast .claude/skills/sast
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sast in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Sast on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Sast is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

sast

Purpose

Unified static analysis tool runner. While sentinel does regex-based security pattern matching and verification runs lint/type/test/build, SAST goes deeper — running dedicated static analysis tools that understand data flow, taint tracking, and language-specific vulnerability patterns.

Sentinel catches obvious patterns (hardcoded secrets, SQL string concat). SAST catches subtle ones (tainted data flowing through 3 function calls to a sink, unsafe deserialization behind a wrapper).

Triggers

  • Called by sentinel (L2) when deep analysis needed beyond pattern matching
  • Called by audit (L2) during security dimension assessment
  • Called by cook (L1) on security-sensitive code (auth, crypto, payments)
  • /rune sast — manual static analysis scan

Calls (outbound)

None — pure runner using Bash for all tools.

Called By (inbound)

  • sentinel (L2): deep analysis beyond regex patterns
  • audit (L2): security dimension in full audit
  • cook (L1): security-sensitive code paths
  • review (L2): when security patterns detected in diff

Execution

Step 1 — Detect Language and Tools

Use Glob to detect project language and available tools:

IndicatorLanguagePrimary ToolFallback
package.jsonJavaScript/TypeScriptnpx eslint --ext .js,.ts,.tsxnpx oxlint
tsconfig.jsonTypeScriptnpx tsc --noEmit + ESLint—
pyproject.toml / setup.pyPythonbandit -r . -f jsonruff check --select S .
Cargo.tomlRustcargo clippy -- -D warningscargo audit
go.modGogovulncheck ./...go vet ./...
.semgrep.yml / anyAnysemgrep --config auto—

Check tool availability:

Bash: command -v <tool> 2>/dev/null
→ If not installed: mark as SKIP with install instruction
→ If installed: proceed with scan

Step 2 — Run Primary Analysis

Run the detected primary tool on changed files (or full project if no diff):

For each available tool:
  Bash: <tool command> 2>&1
  → Capture stdout + stderr
  → Parse output into unified format (see Step 4)
  → Record: exit code, finding count, execution time

Tool-specific commands:

bash
# ESLint (JS/TS) — security-focused rules
npx eslint --no-eslintrc --rule '{"no-eval": "error", "no-implied-eval": "error"}' <files>

# Bandit (Python) — security scanner
bandit -r <path> -f json -ll  # medium+ severity only

# Semgrep (any language) — pattern-based analysis
semgrep --config auto --json --severity ERROR --severity WARNING <path>

# Clippy (Rust) — lint + security
cargo clippy --all-targets -- -D warnings -W clippy::unwrap_used

# govulncheck (Go) — vulnerability check
govulncheck ./...

Step 3 — Run Semgrep (If Available)

Semgrep provides cross-language analysis with community rules. Run regardless of primary language tool:

IF semgrep is installed:
  Bash: semgrep --config auto --json <changed-files-or-project>
  → Parse JSON output
  → Map severity: error→BLOCK, warning→WARN, info→INFO

If semgrep is NOT installed, log INFO: "semgrep not installed — install with pip install semgrep for deeper cross-language analysis."

Step 4 — Normalize to Unified Format

Map all tool outputs to unified severity:

BLOCK (must fix):
  - Bandit: HIGH confidence + HIGH severity
  - ESLint: error-level security rules
  - Semgrep: ERROR severity
  - Clippy: deny-level warnings
  - govulncheck: any known vulnerability

WARN (should fix):
  - Bandit: MEDIUM confidence or MEDIUM severity
  - ESLint: warning-level rules
  - Semgrep: WARNING severity
  - Clippy: warn-level suggestions

INFO (informational):
  - Bandit: LOW severity
  - Semgrep: INFO severity
  - Style/convention suggestions

Step 5 — Report

## SAST Report
- **Status**: PASS | WARN | BLOCK
- **Tools Run**: [list with versions]
- **Tools Skipped**: [list with install instructions]
- **Files Scanned**: [count]
- **Findings**: [count by severity]

### BLOCK (must fix)
- `path/to/file.py:42` — [tool] Possible SQL injection via string formatting (B608)
- `path/to/auth.ts:15` — [semgrep] JWT token not verified before use

### WARN (should fix)
- `path/to/utils.py:88` — [bandit] Use of `subprocess` with shell=True (B602)

### INFO
- `path/to/config.ts:10` — [eslint] Prefer `const` over `let` for unchanging variable

### Tool Coverage
| Tool | Status | Findings | Duration |
|------|--------|----------|----------|
| ESLint | RAN | 2 WARN | 1.2s |
| Semgrep | SKIPPED | — | — (not installed) |
| Bandit | N/A | — | — (not Python) |

Output Format

SAST Report with status (PASS/WARN/BLOCK), tools run, files scanned, findings by severity (BLOCK/WARN/INFO), and tool coverage table. See Step 5 Report above for full template.

Constraints

  1. MUST run all available tools for the detected language — not just one
  2. MUST attempt Semgrep regardless of primary language (if installed)
  3. MUST normalize all outputs to unified BLOCK/WARN/INFO — don't dump raw tool output
  4. MUST show install instructions for missing tools — not silently skip
  5. MUST report which tools ran and which were skipped — transparency
  6. MUST NOT block on missing tools — SKIP with instruction, not FAIL

Sharp Edges

Failure ModeSeverityMitigation
Tool not installed → entire scan skipped silentlyHIGHConstraint 4: show install instruction, continue with available tools
Raw tool output dumped without normalizationMEDIUMStep 4: always normalize to unified format
Only running one tool when multiple applyMEDIUMConstraint 1: run ALL available tools for the language
Semgrep community rules producing noiseLOWFilter to ERROR+WARNING severity only — skip INFO-level Semgrep
Long-running scan on large codebaseMEDIUMRun on changed files only when diff available, full scan only on manual invocation

Done When

  • Language detected from project config files
  • All available tools executed (or SKIP with install instruction)
  • Findings normalized to unified BLOCK/WARN/INFO format
  • Tool coverage table showing what ran and what was skipped
  • SAST Report emitted with overall verdict

Cost Profile

~300-800 tokens input, ~200-500 tokens output. Haiku + Bash commands. Tool execution time varies (1-30s depending on project size).

Frequently asked questions

What does the Sast AI skill do?

Static analysis tool runner. Wraps ESLint, Semgrep, Bandit, Clippy, and language-specific analyzers with unified severity output. Use when deeper code analysis needed beyond pattern matching.

Why use Sast on TypingMind?

Because you install it once and use it with any model. Sast is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Sast in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Rune-kit/rune/tree/master/skills/sast. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Sast?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Sast?

As many as you like. As long as a model supports skills, you can use Sast with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Sast AI skill free?

Yes. It is published on GitHub by Rune-kit under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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