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.
git clone --depth 1 https://github.com/yurilopes/pydoll-mcp-serverWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/yurilopes/pydoll-mcp-server/target)<a href="https://agentmods.dev/commands/yurilopes/pydoll-mcp-server/target"><img src="https://agentmods.dev/badge/commands/yurilopes/pydoll-mcp-server/target.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00930 |
| Opus 5 | $0.00000 | $0.00465 |
| Sonnet 5 | $0.00000 | $0.00186 |
| Haiku 4.5 | $0.00000 | $0.00093 |
Grade A, and why
target 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Target Commands
Target commands manage browser targets including tabs, windows, and other browsing contexts.
Overview
The target commands module provides functionality for creating, managing, and controlling browser targets such as tabs, popup windows, and service workers.
::: pydoll.commands.target_commands options: show_root_heading: true show_source: false heading_level: 2 filters: - "!^_" - "!^__"
Usage
Target commands are used internally by browser classes to manage tabs and windows:
from pydoll.commands.target_commands import get_targets, create_target, close_target
from pydoll.connection.connection_handler import ConnectionHandler
# Get all browser targets
connection = ConnectionHandler()
targets = await get_targets(connection)
# Create a new tab
new_target = await create_target(connection, url="https://example.com")
# Close a target
await close_target(connection, target_id=new_target.target_id)
Key Functionality
The target commands module provides functions for:
Target Management
get_targets()- List all browser targetscreate_target()- Create new tabs or windowsclose_target()- Close specific targetsactivate_target()- Bring target to foreground
Target Information
get_target_info()- Get detailed target information- Target types: page, background_page, service_worker, browser
- Target states: attached, detached, crashed
Session Management
attach_to_target()- Attach to target for controldetach_from_target()- Detach from targetsend_message_to_target()- Send commands to targets
Browser Context
create_browser_context()- Create isolated browser contextdispose_browser_context()- Remove browser contextget_browser_contexts()- List browser contexts
Target Types
Different types of targets can be managed:
Page Targets
# Create a new tab
page_target = await create_target(
connection,
url="https://example.com",
width=1920,
height=1080,
browser_context_id=None # Default context
)
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.
- 6d ago First seen · 147 lines · 0 tokens per session scan A 313735541843
target is a command published in the GitHub repository yurilopes/pydoll-mcp-server (1 stars, last pushed 23d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 930 tokens. 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 2026-08-31.
Other commands, from other repositories
auto-browse
Auto-browse — learn, optimize, and graduate browser operations or web data-mining workflows.
webapp-testing
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
can-i-use
Check browser support for web platform features against the project's browser targets.
gh-issue-use-cypress
Like /gh-issue-use-browser, but pinned to the Cypress MCP — use when your project runs the Cypress MCP for browser automation. Example — /gh-issue-use-cypress "Composer > Save" saving toasts failure but the record persists.
qa
Smoke or browser-walk a running app. Report only. Do not implement. Do not merge.
verify-pr
Verify a PR's frontend changes through browser automation.