Techstack Identification

Q: Why use Techstack Identification on TypingMind?

Because you install it once and use it with any model. Techstack Identification 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.

Q: How do I install Techstack Identification in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/transilienceai/communitytools/tree/main/skills/techstack-identification. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Q: Which AI models can use Techstack Identification?

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.

Q: How many AI models can I use with Techstack Identification?

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

Q: Is the Techstack Identification AI skill free?

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

Q: 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.

Q: 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.

Organization

transilienceai

techstack-identification

OSINT-based technology stack identification. Routes to 6 domain sub-skills (frontend, backend, infra, security, osint, correlation) to discover a target's stack from publicly available signals.

Overview

Publisher	transilienceai
Repository	`communitytools`
Skill name	`techstack-identification`
Stars	565
Forks	81
Bundled files	6
License	MIT
Links	Skill source Repository Homepage

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.
6 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by transilienceai on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/transilienceai/communitytools/tree/main/skills/techstack-identification
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/transilienceai/communitytools/tree/main/skills/techstack-identification

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/transilienceai/communitytools.git /tmp/communitytools
mkdir -p .claude/skills
cp -r /tmp/communitytools/skills/techstack-identification .claude/skills/techstack-identification

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Techstack Identification 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 Techstack Identification 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 Techstack Identification 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.

Tech Stack Identification

Passive OSINT reconnaissance to identify a target's technology stack. No credentials, no active scanning — only publicly available signals.

Quick Start


1. Provide company name (+ optional domain hint)
2. Run infra first (asset inventory) → frontend / backend / security / osint in parallel
3. Pass all signals into correlation → final report (JSON + Markdown)

Domain Sub-Skills

Sub-skill	Identifies	Read
frontend	JS frameworks, meta-frameworks, CSS libraries, build tools, CMS via DOM/HTML/JS	frontend/SKILL.md
backend	Web servers, runtimes, languages, frameworks, DB, APIs, CMS	backend/SKILL.md
infra	Cloud, CDN/WAF, DNS, TLS/CT, DevOps, asset discovery (domains/subdomains/IPs)	infra/SKILL.md
security	Security headers, CSP, email auth, security.txt, third-party SaaS	security/SKILL.md
osint	Public repos (GitHub/GitLab), job postings/ATS, Wayback Machine	osint/SKILL.md
correlation	Cross-validation, confidence scoring, conflict resolution	correlation/SKILL.md

Routing by Objective

Objective	Mount
Full stack discovery	infra → (frontend, backend, security, osint) → correlation
CDN/WAF identification only	infra
API surface mapping	backend
Supply-chain / SaaS exposure	security + osint
CVE matching by version	backend + frontend (then correlation)
Migration / historical context	osint (web archive) + correlation
CMS fingerprint	frontend (HTML generators) + backend (CMS paths/cookies)
Asset inventory only	infra (domain discovery, subdomain enum, IP attribution, CT)

Confidence Levels

High: 3+ independent sources OR explicit identifier (header/meta/global) + supporting evidence + version known
Medium: Single strong source OR multiple indirect signals (URL patterns, cookies, DOM attrs, job postings)
Low: Speculative — single weak signal, conflicting data, or archive-only evidence

Computed in correlation/. Target distribution: 50-70% High, 20-35% Medium, <15% Low.

Final Report Schema

json
{ "report_id": "uuid", "company": "string", "primary_domain": "string",
  "discovered_assets": {"domains", "subdomains", "ip_addresses", "certificates", "api_portals"},
  "technologies": {
    "frontend": [{"name", "version?", "confidence", "evidence": []}],
    "backend": [...], "infrastructure": [...], "security": [...],
    "devops": [...], "third_party": [...] },
  "confidence_summary": {"high_confidence", "medium_confidence", "low_confidence", "overall_score"} }

Rate Limits

crt.sh 10/min · GitHub (unauth) 60/h · HTTP 30/min/domain · DNS 30/min · Wayback CDX 15/min · WHOIS 5/min.

Ethics

Passive only. No active scanning, credentialed access, zone transfers, or brute force. Public sources only. Log every external request for audit.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Techstack Identification AI skill do?

OSINT-based technology stack identification. Routes to 6 domain sub-skills (frontend, backend, infra, security, osint, correlation) to discover a target's stack from publicly available signals.

Why use Techstack Identification on TypingMind?

Because you install it once and use it with any model. Techstack Identification 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 Techstack Identification in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/transilienceai/communitytools/tree/main/skills/techstack-identification. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Techstack Identification?

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 Techstack Identification?

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

Is the Techstack Identification AI skill free?

Yes. It is published on GitHub by transilienceai 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Tech Stack Identification

Quick Start

Domain Sub-Skills

Routing by Objective

Confidence Levels

Final Report Schema

Rate Limits

Ethics

Bundled files

Frequently asked questions

Related AI Skills

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