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man0l

Add Directories

by man0l · GitHub ↗ · v0.1.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install add-directories
Description
Use when adding new AI/startup directories to directories.json from a URL, pasted text, or GitHub awesome-list. Parses, deduplicates, appends new entries, th...
README (SKILL.md)

Add Directories

Workflow

  1. Parse the input (URL or pasted text) into a list of directories
  2. Deduplicate against existing entries in directories.json
  3. Append new entries with required fields
  4. Classify by running the analysis and verification pipeline
  5. Discover forms for submission targets
  6. Submit via automation or manual browser interaction

Step 1: Parse Input

From URL

Fetch the page and extract directory entries. Look for patterns like:

  • Name + URL pairs in lists, tables, or cards
  • Structured data (JSON-LD, markdown tables, CSV)
  • Repeated DOM patterns with links

From GitHub Topics/Repos

Use gh CLI to explore curated lists:

  • gh repo clone \x3Cowner>/\x3Crepo> to clone awesome-lists
  • Parse README.md for directory links (markdown link format)
  • Check for JSON/YAML data files with directory entries
  • Can also create PRs to add your product to these lists

From Pasted Text

Parse lines/rows. Common formats:

  • Name - https://url.com or Name | https://url.com
  • Markdown links: [Name](https://url.com)
  • Markdown tables with Name and URL columns
  • Plain URLs (one per line) — derive name from domain
  • CSV/TSV with headers

Extract at minimum: name and url (submission or homepage).

Step 2: Deduplicate

Load directories.json and check each parsed entry against existing ones by:

  • Exact URL match (normalize: strip trailing slash, lowercase domain)
  • Domain match (same domain = likely duplicate)
  • Name match (case-insensitive)

Report duplicates to the user and skip them.

Step 3: Append New Entries

For each new directory, create an entry with this structure:

{
  "categories": ["General"],
  "description": "",
  "is_active": true,
  "name": "Directory Name",
  "pricing_type": "free",
  "slug": "directory-name",
  "submission_url": "https://example.com/submit",
  "url": "https://example.com/submit"
}

Field rules:

  • slug: lowercase name, spaces to hyphens, strip special chars
  • submission_url and url: use the submission/signup URL if available, otherwise homepage
  • description: leave empty string (will be filled later or by user)
  • categories: default ["General"] unless context provides a category
  • pricing_type: default "free" unless explicitly marked paid
  • is_active: always true for new entries

Save the updated directories.json.

Step 4: Classify

Run the pipeline scripts in order using the project venv at .venv/:

# 1. HTTP-level analysis (auth, captcha, pricing signals, dead domains)
.venv/bin/python analyze_directories.py

# 2. Cleanup obvious failures + build browser check list
.venv/bin/python cleanup_and_categorize.py

# 3. Browser verification with Playwright (10 concurrent workers)
.venv/bin/python browser_verify.py

# 4. Deep recheck any remaining unknowns
.venv/bin/python browser_verify.py --recheck-unknown

Each script reads/writes directories.json. Steps 3-4 use browser_check_list.json as intermediate state (generated by step 2).

After completion, report the summary: how many added, and the auth/status breakdown for the new entries.

Step 5: Discover Forms

For directories that are active and have auth_type = none or auth_type = email_password:

# Discover form fields on submission pages
.venv/bin/python discover_forms.py

This visits each submission URL with Playwright, extracts form fields via DOM queries, and updates submission_plan.json with discovered fields and form paths.

Step 6: Submit

Automated Submission

Configure the PRODUCT dict in submit_directories.py with your details (search for YOUR_ placeholders), then:

# Auto-submit to all discovered directories
.venv/bin/python submit_directories.py

The script uses heuristic field mapping (matching field names/labels to product data) and handles file uploads for logo/screenshot.

Manual Browser Submission (via Playwright MCP)

For directories that need manual interaction (captcha, OAuth, complex forms), use the Playwright browser tools:

  1. Navigate to the submission URL
  2. Take a snapshot to understand the page structure
  3. Fill form fields using browser_fill_form or browser_type
  4. Handle OAuth flows by switching tabs when Google login popups open
  5. Upload files via browser_file_upload
  6. Click submit and verify confirmation

GitHub PR Submissions

Some directories accept submissions via GitHub PRs to awesome-lists:

  1. Fork the repo: gh repo fork \x3Cowner>/\x3Crepo>
  2. Clone and create a branch
  3. Add your product entry following the repo's format
  4. Push and create PR: gh pr create

Notes

Pipeline Scripts

  • analyze_directories.py uses ThreadPoolExecutor with plain HTTP — fast first pass
  • cleanup_and_categorize.py triages errors (dead domains, invalid URLs, Facebook groups) and builds browser_check_list.json
  • browser_verify.py uses async Playwright with 10 concurrent tabs; --recheck-unknown does a deep DOM pass on active unknowns only
  • discover_forms.py uses async Playwright with 10 concurrent tabs; extracts form field names, types, labels, and paths
  • submit_directories.py uses async Playwright with 5 concurrent tabs; heuristic field mapping with file upload support
  • All scripts are idempotent — safe to re-run

Common Submission Blockers

When evaluating or submitting to directories, watch for these issues:

Blocker Frequency How to Detect
Paid listing required ~20% Look for pricing page, Stripe/PayPal links, "$" on submit page
reCAPTCHA / Turnstile ~10% iframe[src*=recaptcha] or [data-turnstile] elements
Broken captcha ~2% "Invalid site key" errors, disabled submit buttons
Login/account required ~15% Redirect to /login or /register on submit URL
Business email required ~3% Rejects gmail/yahoo domains (e.g., SoftwareSuggest)
Reciprocal link required ~5% Old web directories require backlink before listing
Newsletter-only forms ~10% Page looks like submit but is actually email signup
Backend API broken ~2% Form submits but returns GraphQL/API errors
Domain parked/dead ~8% No content, parking page, DNS failure
Cloudflare blocked ~3% Challenge page, 403 errors

Automation Tips

  • Simple HTML forms have highest auto-submit success rate
  • reCAPTCHA v3 (invisible) sometimes passes; v2 (checkbox) never does automatically
  • Google Forms are reliably automatable
  • Rich text editors (TinyMCE, Quill) need browser_evaluate to set content
  • Cloudinary/custom upload widgets often break automation — use manual browser
  • Cross-origin OAuth popups: Switch tabs with browser_tabs action to handle Google login
  • Combobox/select fields: Use browser_click on the dropdown, then click the option
  • Multi-step forms: Take snapshot after each step to see new fields

Submission Plan Structure

Each entry in submission_plan.json contains:

{
  "directory_name": "Example AI",
  "submission_url": "https://example.com/submit",
  "status": "discovered",
  "copy": {
    "title": "Product Title Variation",
    "description": "Product description variation for this directory."
  },
  "discovered_fields": [...],
  "form_path": "form#submit-form",
  "credentials": {
    "email": "YOUR_EMAIL",
    "name": "YOUR_NAME",
    "username": "YOUR_USERNAME",
    "password": "YOUR_PASSWORD"
  }
}

Status values: discovered, submitted, skipped, skipped_paid, timeout, no_form_found, no_fields_matched, submit_timeout, captcha, cloudflare_blocked, domain_parked, skipped_login_required, deferred.

Best ROI Directory Types (for AI/SaaS products)

  1. AI tool directories with simple forms (FutureTools, SaaSHub, AItools.inc, etc.)
  2. Startup directories with Google Form submissions
  3. GitHub awesome-lists accepting PRs (free, high-quality backlinks)
  4. NoCode/SaaS aggregators (NoCodeList, NoCodeDevs)
  5. General web directories with DA≥30 (for SEO value)

Security Note

Before pushing to GitHub, ensure all personal data is stripped:

  • Search for YOUR_ placeholders in submission_plan.json and submit_directories.py
  • Never commit real emails, passwords, or API keys
  • The .playwright-mcp/ folder may contain console logs with personal data — add to .gitignore
Usage Guidance
Before using/installing this skill: - Understand this is instruction-only: it assumes a local project with .venv, Python scripts (analyze_directories.py, browser_verify.py, submit_directories.py, etc.), Playwright and the GitHub CLI. Confirm those files/tools exist in your repo/environment. - Do not auto-run the submit step until you review the submit_directories.py PRODUCT dict: it asks you to place product/account details (credentials) into code — avoid committing secrets or storing them in plaintext. Prefer environment variables or a secrets manager. - Automated submissions will interact with external websites (fill forms, handle OAuth, upload files). Use a test account and sandbox runs first to avoid unintended submissions or leaks. - Back up directories.json before running the pipeline and run the analysis/cleanup/browser verification steps in dry-run mode to see what would be submitted. - If you plan to let the agent invoke this autonomously, be aware it could drive browser flows that require credentials and could cause external side effects; consider disabling autonomous invocation or restricting the skill until you verify it. - Ask the author/maintainer for a clear manifest of required binaries and a safe mechanism for supplying credentials (env vars or interactive prompting), or provide those dependencies locally yourself before running any automated submit steps.
Capability Analysis
Type: OpenClaw Skill Name: add-directories Version: 0.1.0 The skill bundle defines a workflow for automated directory submissions that involves high-risk operations, including executing multiple external Python scripts (e.g., `analyze_directories.py`, `submit_directories.py`), using Playwright for browser automation, and managing user credentials. While the instructions in SKILL.md include a security note regarding data privacy, the actual execution logic is hidden in scripts not provided in the bundle, and the requirement for shell access and credential handling constitutes a significant attack surface.
Capability Assessment
Purpose & Capability
The SKILL.md expects a local project with Python scripts, a .venv, Playwright, and the GitHub CLI (gh) to exist and be runnable, but the skill metadata claims no required binaries, env vars, or install steps. That mismatch suggests the skill assumes an external codebase/environment that is not declared; the declared purpose alone does not justify omitting those requirements.
Instruction Scope
Instructions tell the agent to read and write directories.json and other local files, run networked analysis scripts, drive Playwright to visit and interact with many third‑party submission pages, discover form fields, and perform automated submissions (including handling OAuth popups and file uploads). This is within the stated goal, but it also opens paths to transmit data to external sites and requires credentials and local code edits (the PRODUCT dict) that the skill does not declare or constrain.
Install Mechanism
There is no install spec, yet the workflow relies on a Python virtual environment, Playwright, and gh CLI. Because the skill will instruct running .venv/bin/python and Playwright-driven browsers, the absence of declared install steps or required binaries is an incoherence risk: a user may run commands expecting scripts that aren't present or may be instructed to install heavy packages without guidance.
Credentials
The skill declares no required environment variables or credentials, but the workflow clearly needs GitHub auth (gh), possibly Google or other OAuth credentials for manual flows, and product/account details to auto-submit (the PRODUCT dict). Those secrets are not surfaced or protected in the instructions, increasing the risk of accidental credential exposure or storing secrets in code.
Persistence & Privilege
The skill does not request always:on or other elevated platform privileges. It instructs edits to local project files (directories.json, submission_plan.json, submit_directories.py) and running local scripts, which is expected for this task and stays within the repository scope.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install add-directories
  3. After installation, invoke the skill by name or use /add-directories
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
Initial release of the add-directories skill for ingesting and classifying AI/startup directories. - Supports input from URLs, pasted text, and GitHub awesome-lists. - Parses, deduplicates, and appends new directory entries to directories.json. - Runs multi-step pipeline for analysis, cleanup, and browser verification. - Automatically discovers submission forms and updates submission_plan.json. - Submission process handled separately via submit-directories skill.
Metadata
Slug add-directories
Version 0.1.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Add Directories?

Use when adding new AI/startup directories to directories.json from a URL, pasted text, or GitHub awesome-list. Parses, deduplicates, appends new entries, th... It is an AI Agent Skill for Claude Code / OpenClaw, with 279 downloads so far.

How do I install Add Directories?

Run "/install add-directories" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Add Directories free?

Yes, Add Directories is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Add Directories support?

Add Directories is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Add Directories?

It is built and maintained by man0l (@man0l); the current version is v0.1.0.

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