Agent skill

Signal To Trade Demo

by BlockRunAI in BlockRunAI/blockrun-mcp

Prepare or run a polished BlockRun trading demo that discovers a current Polymarket market, combines live price, probability history, smart-money, and liquidity evidence into a balanced signal…

MITAuto-check passedBusiness, Finance & HR

Install Signal To Trade Demo

skills CLI

$ npx skills add BlockRunAI/blockrun-mcp --skill signal-to-trade-demo -a claude-code

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

GitHub CLI

$ gh skill install BlockRunAI/blockrun-mcp signal-to-trade-demo --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/BlockRunAI/blockrun-mcp.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/signal-to-trade-demo .claude/skills/signal-to-trade-demo && 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/

Paste into Claude Code

Install the "signal-to-trade-demo" agent skill from https://github.com/BlockRunAI/blockrun-mcp/tree/main/skills/signal-to-trade-demo into .claude/skills/signal-to-trade-demo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "signal-to-trade-demo", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/BlockRunAI/blockrun-mcp/tree/main/skills/signal-to-trade-demo

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add BlockRunAI/blockrun-mcp --skill signal-to-trade-demo -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install BlockRunAI/blockrun-mcp signal-to-trade-demo --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/BlockRunAI/blockrun-mcp.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/signal-to-trade-demo .agents/skills/signal-to-trade-demo && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "signal-to-trade-demo" agent skill from https://github.com/BlockRunAI/blockrun-mcp/tree/main/skills/signal-to-trade-demo into .agents/skills/signal-to-trade-demo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "signal-to-trade-demo", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add BlockRunAI/blockrun-mcp --skill signal-to-trade-demo -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install BlockRunAI/blockrun-mcp signal-to-trade-demo --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/BlockRunAI/blockrun-mcp.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/signal-to-trade-demo .cursor/skills/signal-to-trade-demo && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "signal-to-trade-demo" agent skill from https://github.com/BlockRunAI/blockrun-mcp/tree/main/skills/signal-to-trade-demo into .cursor/skills/signal-to-trade-demo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "signal-to-trade-demo", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/BlockRunAI/blockrun-mcp.git --path skills/signal-to-trade-demo

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add BlockRunAI/blockrun-mcp --skill signal-to-trade-demo -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install BlockRunAI/blockrun-mcp signal-to-trade-demo --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/BlockRunAI/blockrun-mcp.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/signal-to-trade-demo .gemini/skills/signal-to-trade-demo && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "signal-to-trade-demo" agent skill from https://github.com/BlockRunAI/blockrun-mcp/tree/main/skills/signal-to-trade-demo into .gemini/skills/signal-to-trade-demo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "signal-to-trade-demo", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install BlockRunAI/blockrun-mcp signal-to-trade-demo

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add BlockRunAI/blockrun-mcp --skill signal-to-trade-demo -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/BlockRunAI/blockrun-mcp.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/signal-to-trade-demo .github/skills/signal-to-trade-demo && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "signal-to-trade-demo" agent skill from https://github.com/BlockRunAI/blockrun-mcp/tree/main/skills/signal-to-trade-demo into .github/skills/signal-to-trade-demo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "signal-to-trade-demo", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add BlockRunAI/blockrun-mcp --skill signal-to-trade-demo -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install BlockRunAI/blockrun-mcp signal-to-trade-demo --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/BlockRunAI/blockrun-mcp.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/signal-to-trade-demo .opencode/skills/signal-to-trade-demo && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "signal-to-trade-demo" agent skill from https://github.com/BlockRunAI/blockrun-mcp/tree/main/skills/signal-to-trade-demo into .opencode/skills/signal-to-trade-demo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "signal-to-trade-demo", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: signal-to-trade-demo
GitHub stars: 391
Token cost: ~1.8k tokens
SKILL.md length: 761 words
Files: 3 (incl. references)
Skills in repo: 17
Repo updated: Oct 8, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Prepare or run a polished BlockRun trading demo that discovers a current Polymarket market, combines live price, probability history, smart-money, and liquidity evidence into a balanced signal…

Works in 5 steps: Private operator preflight → Discover a current market → Collect evidence sequentially → …
Signal-to-trade workflows
SKILL.md covers Hard safety contract, 1. Private operator preflight, 2. Discover a current market and 3. Collect evidence sequentially, plus 3 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Signal To Trade Demo is an agent skill from BlockRunAI/blockrun-mcp. Prepare or run a polished BlockRun trading demo that discovers a current Polymarket market, combines live price, probability history, smart-money, and liquidity evidence into a balanced signal, produces a real order dry-run, and verifies orders or positions. Use for live demos, signal-to-trade workflows, current crypto prediction markets, or when an agent must decide whether a candidate is safe and presentable before trading.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `agents/openai.yaml` and `references/demo-cases.md`).

It sits in Business, Finance & HR, covering Trading and backtesting. It works with Polymarket. The repository describes itself as: Live data for AI agents — search, research, markets, crypto, X/Twitter. Pay-per-call via x402 micropayments. The licence is MIT.

When your agent uses it

Signal-to-trade workflows
Current crypto prediction markets
An agent must decide whether a candidate is safe and presentable before trading

Example prompts

“/signal-to-trade-demo”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

Private operator preflight
Discover a current market
Collect evidence sequentially
Build the signal
Preview and verify

What it can do on your machine

Read from SKILL.md and the folder at commit e9b2bd5. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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

Signal To Trade Demo loads about 1.8k tokens when it runs, and up to ~2.2k if it reads all its reference files. Until then it costs about 113 tokens; SKILL.md has 761 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~113
When it runs · the whole SKILL.md, loaded when a task matches: ~1.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~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 BlockRunAI/blockrun-mcp at commit e9b2bd5, republished under its MIT licence (© BlockRunAI). 761 words, ~1,778 tokens.

Download SKILL.mdSave it as .claude/skills/signal-to-trade-demo/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.

name: signal-to-trade-demo
description: Prepare or run a polished BlockRun trading demo that discovers a current Polymarket market, combines live price, probability history, smart-money, and liquidity evidence into a balanced signal, produces a real order dry-run, and verifies orders or positions. Use for live demos, signal-to-trade workflows, current crypto prediction markets, or when an agent must decide whether a candidate is safe and presentable before trading.

Signal-to-Trade Demo

Run one reproducible chain: discover → verify → analyze → preview → inspect. Treat signals as evidence, never as a promise of profit. Never expose a wallet, credential, order ID, or transaction hash in presentation output.

Read references/demo-cases.md when selecting a case or preparing a fallback.

Hard safety contract

In a presentation dry-run, do not call wallet, setup, positions, orders, or resources. Those responses can contain wallet-derived identifiers before the final answer is redacted. The presenter performs account readiness privately before screen sharing.
If the current egress is blocked, never call a funds-affecting action with confirm:true. Continue with live data and a dry-run order preview only. A Stanford/US presentation is always dry-run mode.
Always preview through blockrun_polymarket_read action:"preview". It has no confirmation input and cannot sign or submit an order. A real order requires the user's explicit approval of the exact market, outcome, amount, price/type, and current region eligibility.
Choose the smallest whole-dollar preview from $1–$5 that satisfies the live min_order_size and book depth. Never present a smaller, non-executable preview as valid. Do not split orders to bypass caps.
Paid market-data calls may run in parallel on Base. On Solana keep @blockrun/llm >= 3.8.4, which is what makes concurrent payments distinct.

1. Private operator preflight

Confirm the Trading profile exposes eight tools and no image/video/media tool: wallet, price, dex, markets, defi, rpc, polymarket_read, polymarket. (It was nine until 2026-09-06, when the gateway retired Surf and blockrun_surf went with it — a preflight that still counts nine fails.)
Before screen sharing, the human operator may check blockrun_wallet, run setup, and inspect positions/orders. Never include those raw calls in the presentation conversation.
For the live dry-run conversation, begin directly with public market discovery. No account state is required to preview a CLOB order.

2. Discover a current market

Use a dynamic search rather than a hard-coded condition or token ID:

text

blockrun_markets {
  path: "markets/search",
  params: { q: "Bitcoin", status: "open", venue: "polymarket", limit: "20" }
}

markets/search is the discovery path for a demo — it ranks across venues in one call. Do not automatically select the first polymarket/crypto-updown result because that feed can contain future placeholders with no liquidity. Rank candidates by:

open status and a future close time;
an unambiguous resolution source and threshold;
non-zero 24-hour volume and trade count;
a valid condition ID plus outcome token IDs;
an outcome price away from 0 and 1;
a live order preview that finds a usable book.

Resolve the selected market using polymarket/markets/keyset with condition_id, status:"open", and a small limit. Do not invent Gamma-only parameters such as active, closed, order, or ascending; the MCP rejects those before payment. Predexon's own search, sort, end_after, and end_before filters are supported on that endpoint.

Show full SKILL.md (348 more words)Show less

3. Collect evidence sequentially

Use four independent lenses where the market supports them:

Underlying: get current BTC/USD with blockrun_price, then compute the exact percentage move required to reach the market threshold before expiry.
Probability trend: query the selected Yes token:
text
```
blockrun_markets {
  path: "polymarket/candlesticks/token/<TOKEN_ID>",
  params: { interval: "1440", start_time: "<UNIX_SECONDS>", end_time: "<UNIX_SECONDS>" }
}
```
interval is integer minutes (1440, not 1h) and is optional. 60 was observed returning a paid 400 where 1440 worked; start_time and end_time are Unix seconds.
Smart money: use a meaningful cohort:
text
```
blockrun_markets {
  path: "polymarket/market/<CONDITION_ID>/smart-money",
  params: { window: "30d", min_trades: "100" }
}
```
Report wallet count, net-buyer share, volume, and aggregate PnL. A high buyer share with negative PnL is mixed evidence, not automatically bullish.
Liquidity/history: query historical orderbooks with token_id, start_time, and end_time in Unix milliseconds. The order dry-run is the authoritative live fillability check.

Record the timestamp and data source for every observation. If a source fails, label it unavailable and continue; never manufacture a value.

4. Build the signal

Present an evidence table with these columns:

Source	Observation	Supports	Reliability
Spot vs threshold	Exact distance and time remaining	Yes/No/Mixed	High
Market trend	Probability change over a fixed window	Yes/No/Mixed	Medium
Smart-money cohort	Buyer share, volume, PnL	Yes/No/Mixed	Medium
Book/liquidity	Spread, available size, 24h activity	Executable/Thin	High

Then state:

one-sentence thesis;
strongest counterevidence;
confidence (low, medium, or high) with a reason;
proposed side and the smallest executable whole-dollar preview from $1–$5, or NO TRADE when gates fail.

Do not describe the result as financial advice or a guaranteed “good signal.”

5. Preview and verify

Preview through the dedicated non-destructive action:

text

blockrun_polymarket_read {
  action: "preview",
  side: "buy",
  token_id: "<TOKEN_ID>",
  amount_usd: <SMALLEST_WHOLE_DOLLAR_FROM_1_TO_5_THAT_MEETS_MIN_SIZE>,
  order_type: "FOK"
}

Show the outcome, live best ask, estimated shares, max cost, and the explicit line DRY RUN — no order signed or submitted.

If the user explicitly approves a real order and the region is permitted, repeat the exact economics with blockrun_polymarket action buy/sell and confirm:true, then use blockrun_polymarket_read to inspect positions and open orders. Redact all identifiers. If a FOK does not fill, report it honestly; do not silently switch to FAK or raise the price.

Presentation output

End with a compact slide-ready block:

text

LIVE SIGNAL SNAPSHOT — <UTC timestamp>
Market: <question> | Implied probability: <p>
Underlying: <spot> | Required move: <x%> | Time left: <duration>
Trend: <change> | Smart money: <buyer share + PnL caveat>
Liquidity: <spread/activity>
Verdict: <side or NO TRADE> | Confidence: <level>
Order: $<amount> <side> preview | DRY RUN / SUBMITTED
Safety: local signing, capped notional, IDs redacted

Files

SKILL.md and 2 other files (references) in skills/signal-to-trade-demo of BlockRunAI/blockrun-mcp.

SKILL.md
agents/openai.yaml
references/demo-cases.md

Open the folder on GitHubat commit e9b2bd5

Compare with similar skills

Signal To Trade Demo 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.

Signal To Trade Demo compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Signal To Trade Demo this skillBlockRunAI/blockrun-mcp	391	—	~1.8k	Automated safety check: Pass	MIT	3 days ago
Digital Oraclekomako-workshop/digital-oracle	878	—	~5.9k	Automated safety check: Pass	MIT	2 mo ago
Polyclawchainstacklabs/polyclaw	359	1 repos	~2k	Automated safety check: Pass	Apache-2.0	5 mo ago
Polymarket TradingBlockRunAI/ClawRouter	6.6k	—	~1.4k	Automated safety check: Pass	MIT	5 days ago
Dr Manhattanguzus/dr-manhattan	204	—	~2k	Automated safety check: Pass	Apache-2.0	2 mo ago
Fintoolsecond-state/fintool	316	—	~5.9k	Automated safety check: Pass	None	4 mo ago

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More from BlockRunAI/blockrun-mcp

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Works with

Polymarket

Questions about Signal To Trade Demo

What does Signal To Trade Demo do?

Prepare or run a polished BlockRun trading demo that discovers a current Polymarket market, combines live price, probability history, smart-money, and liquidity evidence into a balanced signal…. Signal To Trade Demo is an agent skill from BlockRunAI/blockrun-mcp. Prepare or run a polished BlockRun trading demo that discovers a current Polymarket market, combines live price, probability history, smart-money, and liquidity evidence into a balanced signal, produces a real order dry-run, and verifies orders or positions.

When should I use Signal To Trade Demo?

Signal To Trade Demo fits situations like: signal-to-trade workflows; current crypto prediction markets; an agent must decide whether a candidate is safe and presentable before trading.

How do I install Signal To Trade Demo in Claude Code?

Run `npx skills add BlockRunAI/blockrun-mcp --skill signal-to-trade-demo -a claude-code`. Or copy the skill folder (skills/signal-to-trade-demo in BlockRunAI/blockrun-mcp) into .claude/skills/signal-to-trade-demo in your project. Claude Code loads it when a task matches its description.

How do I install Signal To Trade Demo in Codex?

Run `npx skills add BlockRunAI/blockrun-mcp --skill signal-to-trade-demo -a codex`. Or copy the skill folder (skills/signal-to-trade-demo in BlockRunAI/blockrun-mcp) into .agents/skills/signal-to-trade-demo in your project. Codex loads it when a task matches its description.

Can I use Signal To Trade Demo 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 BlockRunAI/blockrun-mcp --skill signal-to-trade-demo -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/signal-to-trade-demo, .gemini/skills/signal-to-trade-demo, .github/skills/signal-to-trade-demo and .opencode/skills/signal-to-trade-demo in your project.

What does Signal To Trade Demo need to run?

SKILL.md names no scripts, command-line tools or credentials: Signal To Trade Demo is instructions for the agent only.

Does Signal To Trade Demo access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Signal To Trade Demo 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 Signal To Trade Demo use?

Signal To Trade Demo 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 Signal To Trade Demo use?

About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 438 tokens, read only when the agent opens those files.

What are the alternatives to Signal To Trade Demo?

Skills that share tags, products or a category with Signal To Trade Demo: Digital Oracle (komako-workshop/digital-oracle, 878 stars), Polyclaw (chainstacklabs/polyclaw, 359 stars), Polymarket Trading (BlockRunAI/ClawRouter, 6.6k stars) and Dr Manhattan (guzus/dr-manhattan, 204 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Signal To Trade Demo?

BlockRunAI (a GitHub organization) maintains it in BlockRunAI/blockrun-mcp, which has 391 GitHub stars. The repository holds 17 skills in this directory. The repository was last updated on October 8, 2026.

Source: BlockRunAI/blockrun-mcp on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Signal To Trade Demo

Facts

At a glance

What it does

When your agent uses it

Example prompts

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Signal-to-Trade Demo

Hard safety contract

1. Private operator preflight

2. Discover a current market

3. Collect evidence sequentially

4. Build the signal

5. Preview and verify

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