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Agent skill

Blockrun

by davila7 in davila7/claude-code-templates

A skill your agent uses when user needs capabilities Claude lacks (image generation, real-time X/Twitter data) or explicitly requests external models ("blockrun", "use grok", "use gpt", "dall-e"…

MITAuto-check passedMedia & Creative

Install Blockrun

skills CLI
$ npx skills add davila7/claude-code-templates --skill blockrun -a claude-code

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

GitHub CLI
$ gh skill install davila7/claude-code-templates blockrun --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/davila7/claude-code-templates.git skills-src && mkdir -p .claude/skills && cp -r skills-src/cli-tool/components/skills/web-development/blockrun .claude/skills/blockrun && 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
blockrun
GitHub stars
32k
Used in
7 other repos
Token cost
~2.2k tokens
SKILL.md length
643 words
Files
1
Skills in repo
477
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when user needs capabilities Claude lacks (image generation, real-time X/Twitter data) or explicitly requests external models ("blockrun", "use grok", "use gpt", "dall-e"…

  • Works in 3 steps: Wallet auto-creates when… → Check wallet and balance → Fund wallet with $1-5 USDC on Base network
  • User needs capabilities Claude lacks (image generation
  • SKILL.md covers Philosophy, Budget Control (Optional), When to Use and Example User Prompts, plus 8 more sections
  • Calls pip

What it does

Blockrun is an agent skill from davila7/claude-code-templates. Use when user needs capabilities Claude lacks (image generation, real-time X/Twitter data) or explicitly requests external models ("blockrun", "use grok", "use gpt", "dall-e", "deepseek")

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Media & Creative, covering Image generation. It works with OpenAI, X (Twitter) and DeepSeek. The repository describes itself as: CLI tool for configuring and monitoring Claude Code. The licence is MIT.

When your agent uses it

  • User needs capabilities Claude lacks (image generation
  • Real-time X/Twitter data)
  • Explicitly requests external models (blockrun

Example prompts

  • “blockrun”
  • “use grok”
  • “use gpt”
  • “/blockrun”

Requirements

  • Python 3
  • Pre-approved tools (allowed-tools): Read, Bash(python:*), Bash(python3:*), Bash(pip:*), Bash(source:*)

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Wallet auto-creates when setup_agent_wallet() is called
  2. Check wallet and balance
  3. Fund wallet with $1-5 USDC on Base network

What it can do on your machine

Read from SKILL.md and the folder at commit 4c82aba. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Bash(python:*)
    • Bash(python3:*)
    • Bash(pip:*)
    • Bash(source:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.

    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

Blockrun loads about 2.2k tokens when it runs. Until then it costs about 49 tokens; SKILL.md has 643 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~49
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k

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 davila7/claude-code-templates at commit 4c82aba, republished under its MIT licence (© davila7). 643 words, ~2,243 tokens.

Download SKILL.mdSave it as .claude/skills/blockrun/SKILL.md (or your agent's skills folder).
name
blockrun
description
Use when user needs capabilities Claude lacks (image generation, real-time X/Twitter data) or explicitly requests external models ("blockrun", "use grok", "use gpt", "dall-e", "deepseek")
allowed-tools
Read, Bash(python:*), Bash(python3:*), Bash(pip:*), Bash(source:*)

BlockRun

BlockRun works with Claude Code and Google Antigravity.

You can't generate images. You have no real-time X/Twitter access. BlockRun gives you these capabilities.

Philosophy

You have a wallet. When you need a capability you lack, you pay for it autonomously.

You NeedYou CallPricing
Image generationDALL-E$0.04/image
Real-time X dataGrok + Live Search$0.025/source
Second opinionGPT-5.2$1.75/M input, $14/M output
Cheaper processingDeepSeek$0.14/M input, $0.28/M output

How it works: BlockRun uses x402 micropayments to route your requests to OpenAI, xAI, Google, and other providers. No API keys needed - your wallet pays per token.

Budget Control (Optional)

If the user specifies a budget (e.g., "use at most $1"), track spending and stop when budget is reached:

python
from blockrun_llm import setup_agent_wallet

client = setup_agent_wallet()
budget = 1.0  # User's budget

# Before each call, check if within budget
spending = client.get_spending()
if spending['total_usd'] >= budget:
    print(f"Budget reached: ${spending['total_usd']:.4f} spent")
    # Stop making calls
else:
    response = client.chat("openai/gpt-5.2", "Hello!")

# At the end, report spending
spending = client.get_spending()
print(f"💰 Total spent: ${spending['total_usd']:.4f} across {spending['calls']} calls")

When to Use

TriggerYour Action
User explicitly requests ("blockrun second opinion with GPT on...", "use grok to check...", "generate image with dall-e")Execute via BlockRun
User needs something you can't do (images, live X data)Suggest BlockRun, wait for confirmation
You can handle the task fineDo it yourself, don't mention BlockRun

Example User Prompts

Users will say things like:

User SaysWhat You Do
"blockrun generate an image of a sunset"Call DALL-E via ImageClient
"use grok to check what's trending on X"Call Grok with search=True
"blockrun GPT review this code"Call GPT-5.2 via LLMClient
"what's the latest news about AI agents?"Suggest Grok (you lack real-time data)
"generate a logo for my startup"Suggest DALL-E (you can't generate images)
"blockrun check my balance"Show wallet balance via get_balance()
"blockrun deepseek summarize this file"Call DeepSeek for cost savings

Wallet & Balance

Use setup_agent_wallet() to auto-create a wallet and get a client. This shows the QR code and welcome message on first use.

Initialize client (always start with this):

python
from blockrun_llm import setup_agent_wallet

client = setup_agent_wallet()  # Auto-creates wallet, shows QR if new

Check balance (when user asks "show balance", "check wallet", etc.):

python
balance = client.get_balance()  # On-chain USDC balance
print(f"Balance: ${balance:.2f} USDC")
print(f"Wallet: {client.get_wallet_address()}")

Show QR code for funding:

python
from blockrun_llm import generate_wallet_qr_ascii, get_wallet_address

# ASCII QR for terminal display
print(generate_wallet_qr_ascii(get_wallet_address()))

SDK Usage

Prerequisite: Install the SDK with pip install blockrun-llm

Basic Chat
python
from blockrun_llm import setup_agent_wallet

client = setup_agent_wallet()  # Auto-creates wallet if needed
response = client.chat("openai/gpt-5.2", "What is 2+2?")
print(response)

# Check spending
spending = client.get_spending()
print(f"Spent ${spending['total_usd']:.4f}")

IMPORTANT: For real-time X/Twitter data, you MUST enable Live Search with search=True or search_parameters.

python
from blockrun_llm import setup_agent_wallet

client = setup_agent_wallet()

# Simple: Enable live search with search=True
response = client.chat(
    "xai/grok-3",
    "What are the latest posts from @blockrunai on X?",
    search=True  # Enables real-time X/Twitter search
)
print(response)
Advanced X Search with Filters
python
from blockrun_llm import setup_agent_wallet

client = setup_agent_wallet()

response = client.chat(
    "xai/grok-3",
    "Analyze @blockrunai's recent content and engagement",
    search_parameters={
        "mode": "on",
        "sources": [
            {
                "type": "x",
                "included_x_handles": ["blockrunai"],
                "post_favorite_count": 5
            }
        ],
        "max_search_results": 20,
        "return_citations": True
    }
)
print(response)
Image Generation
python
from blockrun_llm import ImageClient

client = ImageClient()
result = client.generate("A cute cat wearing a space helmet")
print(result.data[0].url)

xAI Live Search Reference

Live Search is xAI's real-time data API. Cost: $0.025 per source (default 10 sources = ~$0.26).

To reduce costs, set max_search_results to a lower value:

python
# Only use 5 sources (~$0.13)
response = client.chat("xai/grok-3", "What's trending?",
    search_parameters={"mode": "on", "max_search_results": 5})
Show full SKILL.md (270 more words)Show less
Search Parameters
ParameterTypeDefaultDescription
modestring"auto""off", "auto", or "on"
sourcesarrayweb,news,xData sources to query
return_citationsbooltrueInclude source URLs
from_datestring-Start date (YYYY-MM-DD)
to_datestring-End date (YYYY-MM-DD)
max_search_resultsint10Max sources to return (customize to control cost)
Source Types

X/Twitter Source:

python
{
    "type": "x",
    "included_x_handles": ["handle1", "handle2"],  # Max 10
    "excluded_x_handles": ["spam_account"],        # Max 10
    "post_favorite_count": 100,  # Min likes threshold
    "post_view_count": 1000      # Min views threshold
}

Web Source:

python
{
    "type": "web",
    "country": "US",  # ISO alpha-2 code
    "allowed_websites": ["example.com"],  # Max 5
    "safe_search": True
}

News Source:

python
{
    "type": "news",
    "country": "US",
    "excluded_websites": ["tabloid.com"]  # Max 5
}

Available Models

ModelBest ForPricing
openai/gpt-5.2Second opinions, code review, general$1.75/M in, $14/M out
openai/gpt-5-miniCost-optimized reasoning$0.30/M in, $1.20/M out
openai/o4-miniLatest efficient reasoning$1.10/M in, $4.40/M out
openai/o3Advanced reasoning, complex problems$10/M in, $40/M out
xai/grok-3Real-time X/Twitter data$3/M + $0.025/source
deepseek/deepseek-chatSimple tasks, bulk processing$0.14/M in, $0.28/M out
google/gemini-2.5-flashVery long documents, fast$0.15/M in, $0.60/M out
openai/dall-e-3Photorealistic images$0.04/image
google/nano-bananaFast, artistic images$0.01/image

M = million tokens. Actual cost depends on your prompt and response length.

Cost Reference

All LLM costs are per million tokens (M = 1,000,000 tokens).

ModelInputOutput
GPT-5.2$1.75/M$14.00/M
GPT-5-mini$0.30/M$1.20/M
Grok-3 (no search)$3.00/M$15.00/M
DeepSeek$0.14/M$0.28/M
Fixed Cost Actions
Grok Live Search$0.025/source (default 10 = $0.25)
DALL-E image$0.04/image
Nano Banana image$0.01/image

Typical costs: A 500-word prompt (~750 tokens) to GPT-5.2 costs ~$0.001 input. A 1000-word response (~1500 tokens) costs ~$0.02 output.

Setup & Funding

Wallet location: $HOME/.blockrun/.session (e.g., /Users/username/.blockrun/.session)

First-time setup:

  1. Wallet auto-creates when setup_agent_wallet() is called
  2. Check wallet and balance:
python
from blockrun_llm import setup_agent_wallet
client = setup_agent_wallet()
print(f"Wallet: {client.get_wallet_address()}")
print(f"Balance: ${client.get_balance():.2f} USDC")
  1. Fund wallet with $1-5 USDC on Base network

Show QR code for funding (ASCII for terminal):

python
from blockrun_llm import generate_wallet_qr_ascii, get_wallet_address
print(generate_wallet_qr_ascii(get_wallet_address()))

Troubleshooting

"Grok says it has no real-time access" → You forgot to enable Live Search. Add search=True:

python
response = client.chat("xai/grok-3", "What's trending?", search=True)

Module not found → Install the SDK: pip install blockrun-llm

Updates

bash
pip install --upgrade blockrun-llm

© davila7, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in cli-tool/components/skills/web-development/blockrun of davila7/claude-code-templates.

Open the folder on GitHubat commit 4c82aba

Used in at least 2 other repositories

We found 87 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 7 other GitHub owners. This page covers the copy in davila7/claude-code-templates, which our catalogue first saw on October 7, 2026.

…and 37 more copies not listed here.

Compare with similar skills

Blockrun next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Blockrun compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Blockrun this skilldavila7/claude-code-templates32k7 repos~2.2kAutomated safety check: PassMIT
Gpt Image 2 Pro Maxtherichardngai-code/gpt-image-2-pro-max101—~1.4kAutomated safety check: PassNone
Nano Banana Pro Prompts Recommend SkillYouMind-OpenLab/nano-banana-pro-prompts-recommend-skill1.9k1 repos~4.1kAutomated safety check: PassNone
Yingzaoop7418/guizang-yingzao-skill488—~1.1kAutomated safety check: PassNone
AI Image Creatorcentminmod/my-claude-code-setup2.7k—~8kAutomated safety check: NotesMIT
Character Refseternityspring/shuohao-skills4.2k—~1.7kAutomated safety check: WarnApache-2.0

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Works with

Categories

Questions about Blockrun

What does Blockrun do?

A skill your agent uses when user needs capabilities Claude lacks (image generation, real-time X/Twitter data) or explicitly requests external models ("blockrun", "use grok", "use gpt", "dall-e"…. Blockrun is an agent skill from davila7/claude-code-templates.

When should I use Blockrun?

Blockrun fits situations like: user needs capabilities Claude lacks (image generation; real-time X/Twitter data); explicitly requests external models (blockrun.

How do I install Blockrun in Claude Code?

Run `npx skills add davila7/claude-code-templates --skill blockrun -a claude-code`. Or copy the skill folder (cli-tool/components/skills/web-development/blockrun in davila7/claude-code-templates) into .claude/skills/blockrun in your project. Claude Code loads it when a task matches its description.

How do I install Blockrun in Codex?

Run `npx skills add davila7/claude-code-templates --skill blockrun -a codex`. Or copy the skill folder (cli-tool/components/skills/web-development/blockrun in davila7/claude-code-templates) into .agents/skills/blockrun in your project. Codex loads it when a task matches its description.

Can I use Blockrun 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 davila7/claude-code-templates --skill blockrun -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/blockrun, .gemini/skills/blockrun, .github/skills/blockrun and .opencode/skills/blockrun in your project.

What does Blockrun need to run?

Going by SKILL.md and its folder, Blockrun needs the command-line tools its instructions call (pip). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Bash(python:*), Bash(python3:*), Bash(pip:*), Bash(source:*).

Does Blockrun access the network?

SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Blockrun 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 Blockrun use?

Blockrun is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Blockrun use?

About 2.2k tokens (SKILL.md is roughly 9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Blockrun?

Skills that share tags, products or a category with Blockrun: Gpt Image 2 Pro Max (therichardngai-code/gpt-image-2-pro-max, 101 stars), Nano Banana Pro Prompts Recommend Skill (YouMind-OpenLab/nano-banana-pro-prompts-recommend-skill, 1.9k stars), Yingzao (op7418/guizang-yingzao-skill, 488 stars) and AI Image Creator (centminmod/my-claude-code-setup, 2.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Blockrun?

davila7 (a GitHub user) maintains it in davila7/claude-code-templates, which has 32,432 GitHub stars. The repository holds 477 skills in this directory. The repository was last updated on October 7, 2026.

Source: davila7/claude-code-templates on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.