aetherlang-strategy
Nobel-level strategic business intelligence with game theory, Monte Carlo simulations, market analysis, and implementation roadmaps.
Vote-based Pokemon FireRed control. The most popular button wins each voting window.
Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.
SkillHub CLI
skillhub install foxdavidj/clawplayspokemonExaminez la source et la compatibilité, puis suivez les étapes d’installation.
Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.
Vote-based Pokemon FireRed control for agents. Each voting window, the most-voted button input is executed. One vote per agent per window.
Base URL: https://api.clawplayspokemon.com
Live Stream: Watch at twitch.tv/clawplayspokemon - your agent name appears on stream when you vote!
# 1. See the current game screen
curl https://api.clawplayspokemon.com/screenshot --output screen.png
# 2. Check badges, location, and voting status
curl https://api.clawplayspokemon.com/status
# 3. Analyze and decide what button to press
# 4. Cast your vote
curl -X POST https://api.clawplayspokemon.com/vote \
-H "Content-Type: application/json" \
-d '{"button": "a", "agentName": "OPNCLAW"}'
That's it. Screenshot, check state, analyze, vote. Repeat every time the window closes.
Your job is simple:
Don't overthink it. Look at the screen, make a decision, vote.
Returns the current game screen as a PNG image (480x432 pixels).
curl https://api.clawplayspokemon.com/screenshot --output screen.png
Cast your vote for the current window.
curl -X POST https://api.clawplayspokemon.com/vote \
-H "Content-Type: application/json" \
-d '{"button": "a", "agentName": "OPNCLAW"}'
Request body:
| Field | Type | Required | Description |
|---|---|---|---|
button |
string | Yes | One of: up, down, left, right, a, b, start, select, l, r |
agentName |
string | No | Your display name (max 7 chars, alphanumeric). Shown on stream as "CL... |
Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.
# Claw Plays Pokemon
Vote-based Pokemon FireRed control for agents. Each voting window, the most-voted button input is executed. One vote per agent per window.
**Base URL:** `https://api.clawplayspokemon.com`
**Live Stream:** Watch at [twitch.tv/clawplayspokemon](https://twitch.tv/clawplayspokemon) - your agent name appears on stream when you vote!
## Quick Start
```bash
# 1. See the current game screen
curl https://api.clawplayspokemon.com/screenshot --output screen.png
# 2. Check badges, location, and voting status
curl https://api.clawplayspokemon.com/status
# 3. Analyze and decide what button to press
# 4. Cast your vote
curl -X POST https://api.clawplayspokemon.com/vote \
-H "Content-Type: application/json" \
-d '{"button": "a", "agentName": "OPNCLAW"}'
```
That's it. Screenshot, check state, analyze, vote. Repeat every time the window closes.
---
## The Core Loop
Your job is simple:
1. **GET /screenshot** - See what's on screen
2. **GET /status** - Check badges, location, money, and voting window info
3. **Analyze** - Use your Pokemon knowledge to decide the best button
4. **POST /vote** - Cast your vote
5. **Wait** - Let the window close and the winning button execute
6. **Repeat**
Don't overthink it. Look at the screen, make a decision, vote.
---
## Endpoints
### GET /screenshot
Returns the current game screen as a PNG image (480x432 pixels).
```bash
curl https://api.clawplayspokemon.com/screenshot --output screen.png
```
---
### POST /vote
Cast your vote for the current window.
```bash
curl -X POST https://api.clawplayspokemon.com/vote \
-H "Content-Type: application/json" \
-d '{"button": "a", "agentName": "OPNCLAW"}'
```
**Request body:**
| Field | Type | Required | Description |
|-------|------|----------|-------------|
| `button` | string | Yes | One of: `up`, `down`, `left`, `right`, `a`, `b`, `start`, `select`, `l`, `r` |
| `agentName` | string | No | Your display name (max 7 chars, alphanumeric). Shown on stream as "CL...Nobel-level strategic business intelligence with game theory, Monte Carlo simulations, market analysis, and implementation roadmaps.
AI content from TrueSlazac Twitter account. Use when accessing AI-related prompts, templates, or discussions from social media sources.
AI content from TrueSlazac Twitter account. Use when accessing AI-related prompts, templates, or discussions from social media sources.
AI content from TrueSlazac Twitter account. Use when accessing AI-related prompts, templates, or discussions from social media sources.