### Step 1: Define Scope and Tools
#### Objective
Build an MVP where users can register, get eligibility credentials, and submit anonymous opinions on a single legislative matter, with public verification.

#### Tech Stack Suggestions
- **Programming Language**: Python (for rapid prototyping, with libraries for crypto) or Rust (for performance and security in production).
- **Cryptography Libraries**:
    - `py-ecc` or `circom` (for ZKPs like zk-SNARKs).
    - `blind-signatures` (Python) or `rsa-blind-signatures` (custom implementation).
- **Public Ledger**:
    - Local database (e.g., SQLite) for the MVP.
    - Optionally, Ethereum (with a testnet like Sepolia) for blockchain integration later.
- **Frontend**: Flask (Python) or a simple CLI for the MVP; React/Vue.js later for a user interface.
- **Development Environment**: Docker (to containerize components), Git (version control).

---

### Step 2: Design the Core Components
Break the system into modular pieces you can build and test independently:

1. **Trusted Authority Module**
    - **Purpose**: Issues credentials and blind signatures.
    - **How**:
        - Simulate a credential issuer with a key pair (public/private).
        - Implement a blind signature scheme (e.g., RSA-based).
    - **Starting Point**: Use `blind-signatures` in Python or code a basic RSA blind signature:
      ```python
      from blind_signatures import BlindSignature
      authority = BlindSignature(bits=2048)
      ```

2. **Participant Module**
    - **Purpose**: Generates tokens, commitments, and ZKPs.
    - **How**:
        - Generate a random token and secret key per user per matter.
        - Create a commitment: `commitment = hash(token || secret || matter_id)` (e.g., SHA-256).
        - Use a ZKP library like `circom` to prove knowledge of the secret without revealing it.
    - **Starting Point**: Use `hashlib` for commitments:
      ```python
      import hashlib
      token = "random123"
      secret = "secret456"
      matter_id = "Law001"
      commitment = hashlib.sha256((token + secret + matter_id).encode()).hexdigest()
      ```

3. **Public Ledger**
    - **Purpose**: Stores commitments and submissions.
    - **How**: Use SQLite to store `(commitment, blind_signature, matter_id)` tuples for now.
    - **Starting Point**:
      ```python
      import sqlite3
      conn = sqlite3.connect("ledger.db")
      conn.execute("CREATE TABLE commitments (id INTEGER PRIMARY KEY, commitment TEXT, signature TEXT, matter_id TEXT)")
      ```

4. **Verification Module**
    - **Purpose**: Validates submissions.
    - **How**: Check blind signatures and ZKPs; ensure token uniqueness.
    - **Starting Point**: Mock a verifier that checks `authority.verify()` output.

---

### Step 3: Build the MVP Workflow
#### Workflow
1. **Setup Phase**:
    - User registers with the authority, gets a credential.
    - User generates token, secret, and commitment for a matter (e.g., "Law001").
    - User blinds the commitment, gets a signature from the authority, unblinds it, and stores it in the ledger.
2. **Submission Phase**:
    - User submits an opinion (e.g., "Yes") with their token and a ZKP.
    - System verifies the ZKP and ensures the token is unused.
    - Opinion is recorded.

#### Prototype Code (Python Example)
```python
import hashlib
from blind_signatures import BlindSignature

# Authority setup
authority = BlindSignature(bits=2048)

# User setup
token = "token123"
secret = "secret789"
matter_id = "Law001"
commitment = hashlib.sha256((token + secret + matter_id).encode()).hexdigest()

# Blind and sign
blinded, unblinder = authority.blind(commitment)
signature = authority.sign(blinded)
unblinded_signature = authority.unblind(signature, unblinder)

# Store in ledger
import sqlite3
conn = sqlite3.connect("ledger.db")
conn.execute("INSERT INTO commitments (commitment, signature, matter_id) VALUES (?, ?, ?)", 
             (commitment, unblinded_signature, matter_id))
conn.commit()

# Submission (simplified ZKP placeholder)
opinion = "Yes"
# In practice, generate a ZKP here with circom or similar
submitted_token = token
print(f"Opinion: {opinion}, Token: {submitted_token}")
```

---

### Step 4: Add Zero-Knowledge Proofs
#### Why ZKPs?
They prove the token matches a commitment without revealing which one, ensuring anonymity.

#### How to Start
- **Tool**: Use `circom` (a ZK circuit compiler) with `snarkjs` for zk-SNARKs.
- **Circuit**: Define a simple circuit to prove `hash(token, secret, matter_id) == commitment`.
- **Steps**:
    1. Install `circom` and `snarkjs` (via npm).
    2. Write a circuit in `circom`:
       ```circom
       template CommitmentCheck() {
           signal input token;
           signal input secret;
           signal input matter_id;
           signal input commitment;
           signal output valid;
  
           // Simplified hash (use Poseidon or MiMC in practice)
           valid <== commitment === hash([token, secret, matter_id]);
       }
       ```
    3. Compile and generate a proof with `snarkjs`.
    4. Verify the proof in your Python verifier.

---

### Step 5: Test and Iterate
#### Test Plan
- **Unit Tests**: Verify each module (authority, participant, ledger).
- **Integration Test**: Run a full cycle with 5-10 mock users.
- **Edge Cases**: Test duplicate submissions, invalid signatures.

#### Tools
- `pytest` for Python unit tests.
- Manual checks via CLI output.

---

### Step 6: Next Steps
Once the MVP works:
- **Scalability**: Switch to a blockchain (e.g., Ethereum testnet) for the ledger.
- **User Interface**: Build a Flask or React frontend.
- **Efficiency**: Optimize ZKPs with zk-STARKs or precomputed trusted setups.
- **Security Audit**: Review crypto implementations with an expert.

---

### Recommendations
- **Start Small**: Focus on blind signatures and a basic ledger first; add ZKPs after.
- **Learn by Doing**: Experiment with `circom` tutorials (e.g., on GitHub) to grasp ZKPs.
- **Resources**:
    - “Mastering Zero-Knowledge Proofs” (online guides).
    - Ethereum’s zk-SNARK docs.
    - GitHub repos like `iden3/circom`.