Agent skill

Create Pass Through Approximation

by seqra in seqra/opentaint

Model a method's taint propagation as a passThrough approximation.

Apache-2.0Auto-check passedSecurity

Install Create Pass Through Approximation

skills CLI
$ npx skills add seqra/opentaint --skill create-pass-through-approximation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install seqra/opentaint create-pass-through-approximation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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-src

Use ~/.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/

Facts

Skill name
create-pass-through-approximation
GitHub stars
162
Token cost
~1.7k tokens
SKILL.md length
850 words
Files
2 (incl. references)
Skills in repo
16
Repo updated
First seen
Licence
Apache-2.0

At a glance

Model a method's taint propagation as a passThrough approximation.

  • Works in 3 steps: Understand the propagation → Write the config → Re-check your configs
  • A dropped method whose propagation is simple copying
  • SKILL.md covers Inputs, Workflow, Output and Tracking, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

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.

When your agent uses it

  • A dropped method whose propagation is simple copying
  • Tasks that involve Static analysis and SAST

Example prompts

  • “/create-pass-through-approximation”

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Understand the propagation
  2. Write the config
  3. Re-check your configs

What it can do on your machine

Read from SKILL.md and the folder at commit f945f92. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    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.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

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.

Always · name and description, kept in context so the agent knows when to use it
~40
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.9k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from seqra/opentaint at commit f945f92, republished under its Apache-2.0 licence (© seqra). 850 words, ~1,658 tokens.

Download SKILL.mdSave it as .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.
name
create-pass-through-approximation
description
Model a method's taint propagation as a passThrough approximation. Use for a dropped method whose propagation is simple copying
license
Apache-2.0
metadata.author
opentaint
metadata.version
0.3.0

Skill: Create PassThrough Approximation

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.

Inputs

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 directory
  • language (required) — target language for this project and language-specific instructions
  • batch (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.done
  • methods (optional) — a specific { method, signature } subset to (re)work instead of the whole passthrough bucket, when the caller needs only those

Workflow

1. Understand the propagation

Take 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.

2. Write the config

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:

  • Cover every position — this and each argument: copy each to where its data flows, or to itself when it flows nowhere
  • When the data lives in the object between calls, route the writer and the reader through a shared virtual field — a nominal storage location both name identically. What the writer stashes there is what the reader pulls back, if the two name it differently, the taint is lost.
3. Re-check your configs

Before 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.

Output

Short and concise report of what was done

Show full SKILL.md (351 more words)Show less
Artifacts:
  • .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)
  • the cleanly-built methods present in the batch file's build.done (new methods appended; repaired methods already recorded, per Tracking)
Summary:
  • the config paths written and the methods modeled

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

yaml
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.

Constraints

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.

  • Model one function per rule — never a regex/wildcard matcher or an all-arguments position to cover many at once; over-modeling copies taint through methods you never vetted and manufactures false positives
  • Keep produced configs comment-free

© 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

Files

SKILL.md and 1 other file (references) in skills/create-pass-through-approximation of seqra/opentaint.

  • SKILL.md
  • references/java.md

Open the folder on GitHubat commit f945f92

Compare with similar skills

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LLM Sast ScannerSunWeb3Sec/llm-sast-scanner286—~6.2kAutomated safety check: PassNone
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Categories

Questions about Create Pass Through Approximation

What does Create Pass Through Approximation do?

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.

When should I use Create Pass Through Approximation?

Create Pass Through Approximation fits situations like: A dropped method whose propagation is simple copying; tasks that involve Static analysis and SAST.

How do I install Create Pass Through Approximation in Claude Code?

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.

How do I install Create Pass Through Approximation in Codex?

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.

Can I use Create Pass Through Approximation in Cursor, Gemini CLI or GitHub Copilot?

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.

What does Create Pass Through Approximation need to run?

SKILL.md names no scripts, command-line tools or credentials: Create Pass Through Approximation is instructions for the agent only.

Does Create Pass Through Approximation access the network?

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.

Is Create Pass Through Approximation safe to install?

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.

What licence does Create Pass Through Approximation use?

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.

How many tokens does Create Pass Through Approximation use?

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.

What are the alternatives to Create Pass Through Approximation?

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.

Who maintains Create Pass Through Approximation?

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.