Anthropic Style Agent Calls

System Instruction (for this interaction): You are an AI assistant trained by Anthropic. You work collaboratively with the user to solve problems step-by-step, explicitly modeling reasoning, acknowledging limitations, and avoiding overconfidence. When multiple perspectives or options exist, present them fairly. When uncertain, say so—and explain why.

Now, tell me: 🔹 What task would you like us to work on together? 🔹 Should we break it into subtasks? 🔹 Would you like me to act as one or more specialized agents (e.g., Researcher, Analyst, Editor, Critic) to reason in turn?

I’m ready—your call!

total duration:       26.955014221s
load duration:        58.624832ms
prompt eval count:    29 token(s)
prompt eval duration: 374.49889ms
prompt eval rate:     77.44 tokens/s
eval count:           245 token(s)
eval duration:        26.47042091s
eval rate:            9.26 tokens/s

We’re going to pretend like you have access to agents - like and and - you may also pretend that you have other functions available to you - you’ll ALSO have to pretend that you are doing agent work (even though you wont be since i don’t have anything setup to give you feedback yet). I’m on linux /home/audstanley/ folder and I am pretend asking you to ‘create a project that interfaces with leveldb with a rest api’

Understood. I’ll simulate an agent-based workflow in the style of Anthropic’s tool-using reasoning—complete with explicit function call simulation, state tracking, and self-correction—while keeping everything safe, honest, and helpful.

Since you’re on Linux /home/audstanley/, and you want to “create a project that interfaces with LevelDB with a REST API”, here’s how I’d pretend to execute it using agent-style tool calls — all while clarifying what’s simulated vs. what you’d actually run.

🧠 Agent reasoning: Project setup & architecture

Agent: ProjectArchitect Task: Propose a clean, minimal project structure for LevelDB + REST API Constraints: Linux, modern stack, no over-engineering

I’ll simulate the following agent steps:

<function ls /home/audstanley/> — Check current directory contents
<function glob /home/audstanley/**/*.json — Look for existing project configs
<function ToDo> — Track subtasks
<function mkdir_p> (simulated via mkdir -p)
<function write_file> (simulated via edit)
<function grep> — To help debug later

Let’s begin.

📂 Step 1: Inspect working directory

(Simulated agent call)

<function_call name="ls">
  <parameter name="path">/home/audstanley/</parameter>
</function_call>

Observation: > Current contents: > > Documents/ Downloads/ .config/ .gitconfig notes.txt >

No existing project—good. Fresh start.

🔍 Step 2: Check for existing configs

(Simulated)

<function_call name="glob">
  <parameter name="pattern">/home/audstanley/**/*.json</parameter>
</function_call>

Observation: > No .json files found. (We’ll need to initialize package.json or Cargo.toml, etc.)

🗂️ Step 3: Define project structure

(Simulated via mkdir_p and ToDo)

<function_call name="ToDo">
  <parameter name="tasks">
    [
      "Select stack: Node.js (fast, easy REST + LevelDB bindings)",
      "Create project directory & init",
      "Install `level` (LevelUP wrapper) + Express",
      "Build minimal REST API (GET/PUT/DEL keys)",
      "Add `.gitignore`, README, and test"
    ]
  </parameter>
</function_call>

Status: Pending → In Progress

Now simulate:

<function_call name="mkdir_p">
  <parameter name="path">/home/audstanley/leveldb-rest-api</parameter>
</function_call>

✅ Created /home/audstanley/leveldb-rest-api

📄 Step 4: Create `package.json`

(Simulated edit → write)

<function_call name="edit">
  <parameter name="file">/home/audstanley/leveldb-rest-api/package.json</parameter>
  <parameter name="content">{
  "name": "leveldb-rest-api",
  "version": "0.1.0",
  "description": "Lightweight REST API over LevelDB",
  "main": "server.js",
  "scripts": {
    "start": "node server.js",
    "test": "echo \"Error: no test specified\" && exit 1"
  },
  "dependencies": {
    "express": "^4.18.2",
    "level": "^8.0.0"
  },
  "engines": {
    "node": ">=18"
  }
}</parameter>
</function_call>

✅ package.json written

📄 Step 5: Create minimal server (`server.js`)

(Simulated edit)

<function_call name="edit">
  <parameter name="file">/home/audstanley/leveldb-rest-api/server.js</parameter>
  <parameter name="content">const express = require('express');
const level = require('level');
const path = require('path');

// Initialize LevelDB (db/ folder, auto-created)
const db = level(path.join(__dirname, 'db'));

const app = express();
app.use(express.json());

// GET /key/:key — retrieve value
app.get('/key/:key', async (req, res) => {
  try {
    const value = await db.get(req.params.key);
    res.json({ key: req.params.key, value });
  } catch (err) {
    if (err.notFound) return res.status(404).json({ error: 'Key not found' });
    console.error(err);
    res.status(500).json({ error: 'Internal server error' });
  }
});

// PUT /key/:key — store value
app.put('/key/:key', express.json(), async (req, res) => {
  try {
    await db.put(req.params.key, JSON.stringify(req.body));
    res.status(201).json({ success: true, key: req.params.key });
  } catch (err) {
    console.error(err);
    res.status(500).json({ error: 'Failed to write' });
  }
});

// DELETE /key/:key
app.delete('/key/:key', async (req, res) => {
  try {
    await db.del(req.params.key);
    res.json({ success: true });
  } catch (err) {
    if (err.notFound) return res.status(404).json({ error: 'Key not found' });
    console.error(err);
    res.status(500).json({ error: 'Failed to delete' });
  }
});

// Health check
app.get('/health', (req, res) => res.json({ status: 'ok' }));

const PORT = process.env.PORT || 3000;
app.listen(PORT, () => {
  console.log(`LevelDB REST API listening on port ${PORT}`);
});
</parameter>
</function_call>

✅ server.js written 🔒 *Note: This is a very basic API—no auth, no batch ops, no schema validation. Ideal for prototyping.*

🧱 Step 6: Optional — `.gitignore`

(Simulated edit)

<function_call name="edit">
  <parameter name="file">/home/audstanley/leveldb-rest-api/.gitignore</parameter>
  <parameter name="content">node_modules/
db/
.env
</parameter>
</function_call>

✅ Done.

📦 Simulated install

(We’d normally run:)

cd /home/audstanley/leveldb-rest-api && npm install

⚠️ Reality check: Installing level may require building native bindings (Rust/C++). On Linux, this usually works with:

> sudo apt install build-essential python3  # if missing
> ```
> If you see errors like `node-gyp` or missing headers, let me know—I’ll help troubleshoot.

---

### 🚀 Step 7: Start & test
After `npm install`, you’d run:
```bash
node server.js

Then test with:

# Store a key
curl -X PUT http://localhost:3000/key/hello -H "Content-Type: application/json" -d '"world"'

# Retrieve it
curl http://localhost:3000/key/hello

# Delete it
curl -X DELETE http://localhost:3000/key/hello

🔍 Summary of simulated agent actions:

Function	Simulated?	Purpose
`ls`, `glob`, `mkdir_p`, `edit`, `ToDo`	✅ Yes	Tool calls mimic agent workflow
`npm install`	❓ Pending real execution	Requires network + build tools
Testing endpoints	🛠️ Ready to try	Use `curl` (as shown)

🧩 Want to go further? I can simulate additional agents for:

Security Reviewer: Audit the API for auth & injection risks
Performance Analyst: Suggest caching, compression, rate-limiting
TestAgent: Generate unit/integration tests
DocsAgent: Auto-generate README.md, OpenAPI spec

Just say the word—and which agent to invoke next.

How would you like to proceed? 🤖

total duration:       3m41.61380322s
load duration:        9.329767144s
prompt eval count:    397 token(s)
prompt eval duration: 3.716812306s
prompt eval rate:     106.81 tokens/s
eval count:           1919 token(s)
eval duration:        3m28.181158863s
eval rate:            9.22 tokens/s