Agent Skill

Instructions that AI agents receive when connecting to the Cred Protocol MCP server

Agent Skill Instructions

When an AI agent connects to the Cred Protocol MCP server, it automatically receives the following instructions during initialization. These guide the agent on tool selection, score interpretation, and best practices.

These instructions are delivered via the MCP instructions field — no extra configuration needed. You can also use this page as a reference when building custom agents.

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When to Use These Tools

Use Cred Protocol tools when users ask about:

• Wallet creditworthiness, trust, or risk assessment
• Financial health or portfolio analysis of an Ethereum address
• Identity verification or attestation checks
• Sybil detection (is this a real person or a bot?)
• DeFi lending eligibility or underwriting decisions
• Comparing multiple wallets or batch assessments
• Transaction flow and counterparty analysis
• AI agent discovery, reputation, or on-chain registration

Tool Selection Guide

Start here — pick the right tool for the job:

User Intent	Tool	Notes
”Is this wallet trustworthy?”	get_credit_score	Add include_factors: true for detail
”Compare these wallets”	get_credit_scores_batch	Individual scores, no aggregation
”Give me one score for this multi-sig”	get_aggregate_score	Single combined score
”Tell me everything about this wallet”	get_financial_summary	Full report with assets, DeFi, events
”Full multi-chain credit report”	get_comprehensive_report	Per-chain breakdowns + percentiles
”Quick summary, no chain details”	get_summary_report	Lighter than comprehensive
”What’s happening on Ethereum specifically?”	get_chain_report	Single-chain deep dive
”Quick chain stats”	get_chain_summary	Single-chain aggregated metrics
”How much is this wallet worth?”	get_portfolio_value	Total USD across all chains
”What does this wallet hold on Base?”	get_chain_portfolio_value	Chain-specific USD value
”What’s the asset breakdown?”	get_portfolio_composition	Tokens, DeFi, stablecoins, debt
”What identity does this wallet have?”	get_identity_attestations	ENS, Gitcoin Passport, POAPs, etc.
”Is this a bot or a real person?”	get_sybil_score	Sybil detection with indicators
”Show me this wallet’s transaction network”	get_transaction_graph	Token transfer graph (nodes + edges)
“How many agents are registered?”	get_agent_count	Total in ERC-8004 registry
”List all agents”	list_agents	Paginated agent listing
”Find agents that do X”	search_agents	Search by name or description
”Look up agent #42”	get_agent	Single agent info by ID
”Rate this agent on-chain”	submit_agent_reputation	Submits credit/sybil/identity scores
”What’s this agent’s reputation?”	get_agent_reputation	Aggregated on-chain feedback
”Did my reputation submission go through?”	get_reputation_status	Track async submission

Escalation Patterns

Wallet assessment (most common):

1. Start with the credit score

   Call get_credit_score with include_factors: true — this answers 80% of questions.

2. Escalate if needed

   If the user wants the full picture, call get_financial_summary or get_comprehensive_report.

3. Add specific details on request

   Only call get_identity_attestations, get_portfolio_value, or get_sybil_score if the user needs those specific details — the financial summary already includes identity and asset data.

Deep dive on a wallet:

1. get_credit_score for the headline number
2. get_comprehensive_report for the full multi-chain breakdown
3. get_sybil_score if trust/humanity is in question
4. get_transaction_graph to visualize the wallet’s network

Agent reputation workflow:

1. search_agents or list_agents to find the agent
2. get_agent to confirm details
3. get_agent_reputation to read existing on-chain feedback
4. submit_agent_reputation to add new feedback (costs 10 CU, async)
5. get_reputation_status to track the on-chain submission

Authentication

All tools require a CRED_API_KEY to access the live Cred Protocol API. All responses include source: "live" indicating real on-chain data.

Generate your API key from the Cred Protocol Dashboard.

Understanding Credit Scores

Scores range from 300 to 1000 (like traditional credit scores):

Range	Label	Meaning
920-1000	Excellent	Top-tier on-chain reputation. Minimal risk.
840-919	Very Good	Strong history, diversified activity.
750-839	Good	Solid track record, moderate experience.
640-749	Fair	Limited history or some risk signals.
300-639	Low	New wallet, thin file, or negative events.

Score factors (available with include_factors: true):

• Borrowing History — Loan repayment track record across DeFi protocols
• Wallet Composition — Asset diversity and stablecoin ratio
• Wallet Health — Collateralization ratios and liquidation distance
• Interactions — Protocol breadth and ecosystem participation
• Trust — Identity attestations (ENS, Gitcoin Passport, POAPs)
• New Credit — Recent changes in borrowing behavior

Understanding Sybil Scores

The get_sybil_score tool returns a score from 0-100 with a risk level:

Risk Level	Score	Meaning
low	0-25	Likely a unique human with organic activity
medium	26-50	Some suspicious indicators, needs context
high	51-75	Multiple sybil indicators present
critical	76-100	Very likely a sybil/bot account

Key indicators to highlight:

• wallet_age_days — Older wallets are more trustworthy
• transaction_time_entropy — Higher entropy = more human-like timing
• identity_attestations — More attestations = harder to fake
• count_unique_counterparties — Diverse interactions suggest real usage

Reading Financial Summaries

Key fields in the financial summary report:

Field	Meaning
net_worth_usd	Total assets minus total debt
total_asset_usd / total_debt_usd	Gross positions
total_collateral_usd	Assets locked as collateral in DeFi
count_transactions	Total on-chain transactions (activity proxy)
count_active_loans	Current open DeFi loans
count_liquidations	Historical liquidation events (red flag if > 0)
global_percentiles	How this wallet compares to the population

Identity Attestations

Attestations are verified on-chain identity credentials:

Attestation	What It Proves
ENS Name	Owns an Ethereum Name Service domain
Basename	Owns a Base network name (username.base.eth)
Gitcoin Passport	Passed humanity verification (score >= 20)
POAPs	Attended real-world or virtual events
Worldcoin	Verified unique human via biometric proof
BrightID	Verified through social graph analysis

More attestations generally indicate a more established, trustworthy identity.

Transaction Graphs

The get_transaction_graph tool returns a tripartite graph:

• Nodes with group: "wallet" are Ethereum addresses
• Nodes with group: "token" are ERC-20 tokens (USDC, WETH, etc.)
• Edges with label: "SENT" go from wallet to token
• Edges with label: "RECEIVED" go from token to wallet

This is useful for visualizing money flow, identifying major counterparties, and spotting wash trading patterns.

Agentic Reputation (ERC-8004)

The agent tools interact with the ERC-8004 Identity and Reputation Registries on Base (chain ID 8453).

Identity Registry — where agents are registered as ERC-721 tokens:

• Each agent has an agent_id (token ID), owner address, and metadata (name, description, image)
• Use get_agent_count, list_agents, search_agents, get_agent to browse

Reputation Registry — where feedback about agents is stored on-chain:

• submit_agent_reputation computes credit score, sybil risk, and identity count for a given address, then writes the results on-chain as feedback for the specified agent
• get_agent_reputation reads the aggregated feedback summary
• Submissions are async — use get_reputation_status to track

You can combine agent tools with wallet tools: look up an agent’s owner via get_agent, then score the owner with get_credit_score to assess the human behind the agent.

Supported Chains

Data is aggregated across 10 EVM networks:

Chain	ID	Notes
Ethereum	1	Primary chain, richest data
Optimism	10	L2
BSC	56	Binance Smart Chain
Polygon	137	L2
Base	8453	Coinbase L2, ERC-8004 registry
Arbitrum	42161	L2
Celo	42220	Mobile-first chain
Avalanche	43114	—
Scroll	534352	zkEVM L2
Linea	59144	Consensys zkEVM L2

Input Format

All address-based tools accept either:

• Ethereum addresses: 0x742d35Cc6634C0532925a3b844Bc9e7595f32345 (42 characters, hex)
• ENS names: vitalik.eth, username.base.eth

Agent tools use integer agent_id values (starting at 1).

Best Practices

1. Don't over-call

   A single get_credit_score with include_factors: true answers most questions. Only escalate to get_comprehensive_report if the user needs the full breakdown.

2. Batch when possible

   Use get_credit_scores_batch instead of looping get_credit_score for multiple addresses.

3. Interpret, don't just relay

   Translate scores and data into actionable insights. “This wallet has an Excellent score of 945 with no liquidation history — it’s a strong candidate for undercollateralized lending.”

4. Flag red flags

   Highlight liquidations, high debt-to-asset ratios, low scores, missing identity attestations, or high sybil scores.

5. Respect the score range context

   A 750 is “Good” — don’t call it average. A 640 is “Fair” — don’t call it bad. Use the labels.

6. Combine tools for depth

   Credit score + sybil score + identity attestations gives a comprehensive trust picture. Agent lookup + owner credit score assesses the human behind an agent.

7. Track async operations

   After submit_agent_reputation, always inform the user the submission is async and provide the submission_id for tracking with get_reputation_status.