techstack-identification

A passive investigation workflow for identifying a website or company’s technology stack from public information. OSINT means intelligence gathered from openly available sources, without logging in or actively scanning systems.

In plain words
What is it for?
Use it to identify frameworks, programming languages, databases, cloud services, domains, security settings, and other publicly visible technology choices.
Why use it?
It helps determine how a target is built when the technical details are not documented publicly in one place. It compares signals from the frontend, backend, hosting, security settings, public code, job listings, and archived pages.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/transilienceai/communitytools/techstack-identification
Any agent
npx skills add transilienceai/communitytools --skill techstack-identification
Clone the repo
git clone --depth 1 https://github.com/transilienceai/communitytools

Made for: Claude Code, Codex.

Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 830 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00045 $0.00830
Opus 5 $0.00023 $0.00415
Sonnet 5 $0.00009 $0.00166
Haiku 4.5 $0.00005 $0.00083

Measured 3d ago against content hash 997684d33913, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

techstack-identification scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/techstack-identification/SKILL.md · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

Read the full file on GitHub · 69 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 69 lines · 45 tokens per session scan A 997684d33913

Subscribe to this mod's changes

techstack-identification is a skill published in the GitHub repository transilienceai/communitytools (498 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 830 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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