Semgrep
vigolium/piolium
Run Semgrep static analysis scan on a codebase using parallel subagents.
Model a method's taint propagation as a passThrough approximation.
$ npx skills add seqra/opentaint --skill create-pass-through-approximation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install seqra/opentaint create-pass-through-approximation --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/seqra/opentaint.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/create-pass-through-approximation .claude/skills/create-pass-through-approximation && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "create-pass-through-approximation" agent skill from https://github.com/seqra/opentaint/tree/main/skills/create-pass-through-approximation into .claude/skills/create-pass-through-approximation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-pass-through-approximation", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/seqra/opentaint/tree/main/skills/create-pass-through-approximationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add seqra/opentaint --skill create-pass-through-approximation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install seqra/opentaint create-pass-through-approximation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seqra/opentaint.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/create-pass-through-approximation .agents/skills/create-pass-through-approximation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "create-pass-through-approximation" agent skill from https://github.com/seqra/opentaint/tree/main/skills/create-pass-through-approximation into .agents/skills/create-pass-through-approximation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-pass-through-approximation", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add seqra/opentaint --skill create-pass-through-approximation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install seqra/opentaint create-pass-through-approximation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seqra/opentaint.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/create-pass-through-approximation .cursor/skills/create-pass-through-approximation && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "create-pass-through-approximation" agent skill from https://github.com/seqra/opentaint/tree/main/skills/create-pass-through-approximation into .cursor/skills/create-pass-through-approximation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-pass-through-approximation", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/seqra/opentaint.git --path skills/create-pass-through-approximation--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add seqra/opentaint --skill create-pass-through-approximation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install seqra/opentaint create-pass-through-approximation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seqra/opentaint.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/create-pass-through-approximation .gemini/skills/create-pass-through-approximation && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "create-pass-through-approximation" agent skill from https://github.com/seqra/opentaint/tree/main/skills/create-pass-through-approximation into .gemini/skills/create-pass-through-approximation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-pass-through-approximation", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install seqra/opentaint create-pass-through-approximationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add seqra/opentaint --skill create-pass-through-approximation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/seqra/opentaint.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/create-pass-through-approximation .github/skills/create-pass-through-approximation && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "create-pass-through-approximation" agent skill from https://github.com/seqra/opentaint/tree/main/skills/create-pass-through-approximation into .github/skills/create-pass-through-approximation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-pass-through-approximation", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add seqra/opentaint --skill create-pass-through-approximation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install seqra/opentaint create-pass-through-approximation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seqra/opentaint.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/create-pass-through-approximation .opencode/skills/create-pass-through-approximation && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "create-pass-through-approximation" agent skill from https://github.com/seqra/opentaint/tree/main/skills/create-pass-through-approximation into .opencode/skills/create-pass-through-approximation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-pass-through-approximation", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
create-pass-through-approximationModel a method's taint propagation as a passThrough approximation.
Create Pass Through Approximation is an agent skill from seqra/opentaint. Model a method's taint propagation as a passThrough approximation. Use for a dropped method whose propagation is simple copying
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/java.md`).
It sits in Security, covering Static analysis and SAST. The repository describes itself as: The open source taint analysis engine for the AI era. A formal dataflow analysis tool you can customize and self-host, built so AI agents drive your application security analysis… The licence is Apache-2.0.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit f945f92. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Create Pass Through Approximation loads about 1.7k tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 40 tokens; SKILL.md has 850 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from seqra/opentaint at commit f945f92, republished under its Apache-2.0 licence (© seqra). 850 words, ~1,658 tokens.
.claude/skills/create-pass-through-approximation/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Model a dropped method's taint propagation as a passThrough approximation — a config that tells the engine how data moves from a method's inputs to its outputs, so a flow the analyzer lost through the opaque call is restored.
Provided by the caller, fall back to the default value when omitted. Ask back only when a required input is missing and has no sensible default
project-root (optional) — root of the target project. Opentaint keeps all analysis artifacts under the fixed <project-root>/.opentaint/ directory, so every .opentaint/... path below resolves there. Default: current directorylanguage (required) — target language for this project and language-specific instructionsbatch (required) — the batch id; its passthrough entries live in .opentaint/tracking/approximations/<batch>.yaml, and you append the ones you build to that file's build.donemethods (optional) — a specific { method, signature } subset to (re)work instead of the whole passthrough bucket, when the caller needs only thoseTake the batch's passthrough methods not yet in build.done (or the specific methods you were handed) and study each from its real code: read the source (per the language reference). Model each method purely from what its own code does, independent of how the project uses it — the config describes the method's intrinsic propagation. Answer: where does the input data go? Data that arrives on the receiver or an argument — does it come back out, through the return value, an argument the method writes into, the receiver, or an object or field it stores into? Note too whether the object holds the data between calls (a setter stashes it and a getter hands it back later, or a builder accumulates it) — that needs a virtual field. That shape is what the config expresses.
Write one passThrough config per package under .opentaint/pass-through (the format and patterns are in the language reference). A method already in build.done and not explicitly handed in methods is built and trusted — leave it and its config as-is. Repair an explicitly handed method in its existing config; add a new method to its existing package config rather than rewriting the file. Two ideas drive the copy:
this and each argument: copy each to where its data flows, or to itself when it flows nowhereBefore returning, confirm you wrote a passThrough for every method you were to model, and that each config's copies actually match how the method moves data in its source — every position covered, and a writer and its reader sharing the identical virtual field. Append each written method not already present to build.done (per Tracking); a repaired method remains recorded there.
Short and concise report of what was done
.opentaint/pass-through/<package-kebab>.yaml — the passThrough config(s); one per package (a dependency can span several), the file named for that package (the whole-file form is in the language reference)build.done (new methods appended; repaired methods already recorded, per Tracking).opentaint/tracking/approximations/<batch>.yaml — one batch's callable classification, <batch> the plan's filename stem. Every callable sits in exactly one verdict bucket, keyed with the exact language-specific method and signature from the plan so distinct variants stay separate:
passthrough, dataflow — modeled carriers; each entry { method, signature }skipped — terminal non-carriers; each { method, signature, reason }engine_issues — a separate bucket for carriers the engine provably can't propagate (built but still dropped); each { method, signature, reason }. Terminal and treated just like skipped — the only difference is the reason. merge-skipped carries it into skipped.yaml as its own engine_issues group alongside the regular skipped methods.dependencies lists the dependency identifiers a dataflow test project needs. The build block tracks the build — test_project records each dataflow method's test-project status (done if a sample was written into the batch's test project, failed if none could be written so the method was excluded from it), and done holds the finished { method, signature }. Keep it clear from comments
passthrough:
- { method: "<qualified-member-a>", signature: "<language-signature-a>" }
dataflow:
- { method: "<qualified-member-b>", signature: "<language-signature-b>" }
skipped:
- { method: "<qualified-member-c>", signature: "<language-signature-c>", reason: "retains none of its input data" }
engine_issues: []
dependencies: []
build:
test_project:
- { method: "<qualified-member-b>", signature: "<language-signature-b>", status: done }
done: []This skill only appends each cleanly-built method to build.done as { method, signature } when absent. A newly assigned method that you failed to write stays out, so the loop comes back to it; an explicitly repaired method leaves its existing entry unchanged. Never touch the classification buckets or edit an entry already in build.done.
OpenTaint is a whole-program, interprocedural, field-sensitive alias analysis engine. It already propagates through visible application code, calls, aliases, and individual fields; custom rules and approximations model only the assigned source, sink, or opaque-method boundary. Compile-time constants and literals carry no taint, so a source or carrier whose output is only a constant introduces nothing.
© seqra, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (references) in skills/create-pass-through-approximation of seqra/opentaint.
Open the folder on GitHubat commit f945f92
Create Pass Through Approximation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Create Pass Through Approximation this skillseqra/opentaint | 162 | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | |
| Semgrepvigolium/piolium | 138 | 1 repos | ~2.4k | Automated safety check: Notes | MIT | |
| C To AstNarwhal-Lab/MagicSkills | 316 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Semgrep Security Scantrailofbits/skills | 7.4k | — | ~3.7k | Automated safety check: Notes | CC-BY-SA-4.0 | |
| LLM Sast ScannerSunWeb3Sec/llm-sast-scanner | 286 | — | ~6.2k | Automated safety check: Pass | None | |
| Sast SemgrepAgentSecOps/SecOpsAgentKit | 219 | 2 repos | ~2.4k | Automated safety check: Pass | Custom licence |
vigolium/piolium
Run Semgrep static analysis scan on a codebase using parallel subagents.
Narwhal-Lab/MagicSkills
Parse C source code into an Abstract Syntax Tree (AST). An agent skill from Narwhal-Lab/MagicSkills.
trailofbits/skills
Detects languages, proposes rulesets for approval, then runs the approved Semgrep scan across a codebase and merges the output into one SARIF file.
SunWeb3Sec/llm-sast-scanner
General-purpose Static Application Security Testing (SAST) skill for code vulnerability analysis.
AgentSecOps/SecOpsAgentKit
Static application security testing (SAST) using Semgrep for vulnerability detection, security code review, and secure coding guidance with OWASP and CWE framework mapping.
Automattic/agent-skills
A skill your agent uses when configuring, running, or fixing PHPStan static analysis in WordPress projects (plugins/themes/sites): phpstan.neon setup, baselines, WordPress-specific typing, and…
seqra/opentaint
Analyze an OpenTaint scan's dropped external methods and decide which of them are propagators and optionally sinks.
seqra/opentaint
Model a method's taint propagation as code-based dataflow approximation and refine it against a test project until the sample passes.
seqra/opentaint
Run one stage of the OpenTaint pipeline by coordinating leaf subagents and deterministic joins.
seqra/opentaint
Run an end-to-end OpenTaint application-security analysis while owning the long project build and scans and delegating each other pipeline stage.
seqra/opentaint
Build a target project into an opentaint project model. An agent skill from seqra/opentaint.
seqra/opentaint
Author and verify an OpenTaint rule. An agent skill from seqra/opentaint.
Categories
Model a method's taint propagation as a passThrough approximation. Create Pass Through Approximation is an agent skill from seqra/opentaint. Model a method's taint propagation as a passThrough approximation.
Create Pass Through Approximation fits situations like: A dropped method whose propagation is simple copying; tasks that involve Static analysis and SAST.
Run `npx skills add seqra/opentaint --skill create-pass-through-approximation -a claude-code`. Or copy the skill folder (skills/create-pass-through-approximation in seqra/opentaint) into .claude/skills/create-pass-through-approximation in your project. Claude Code loads it when a task matches its description.
Run `npx skills add seqra/opentaint --skill create-pass-through-approximation -a codex`. Or copy the skill folder (skills/create-pass-through-approximation in seqra/opentaint) into .agents/skills/create-pass-through-approximation in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add seqra/opentaint --skill create-pass-through-approximation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/create-pass-through-approximation, .gemini/skills/create-pass-through-approximation, .github/skills/create-pass-through-approximation and .opencode/skills/create-pass-through-approximation in your project.
SKILL.md names no scripts, command-line tools or credentials: Create Pass Through Approximation is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Create Pass Through Approximation is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.7k tokens (SKILL.md is roughly 6.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.3k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Create Pass Through Approximation: Semgrep (vigolium/piolium, 138 stars), C To Ast (Narwhal-Lab/MagicSkills, 316 stars), Semgrep Security Scan (trailofbits/skills, 7.4k stars) and LLM Sast Scanner (SunWeb3Sec/llm-sast-scanner, 286 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
seqra (a GitHub organization) maintains it in seqra/opentaint, which has 162 GitHub stars. The repository holds 16 skills in this directory. The repository was last updated on October 7, 2026.
Source: seqra/opentaint on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.