remediation-suggester

remediation-suggester is an agent for Claude Code from omermaksutii/RugProof. It costs 28 tokens per session (746 once invoked), scanned A, original, MIT.

A coding-agent add-on that writes small code patches for specific security findings, then builds and tests the project to check them.

In plain words
What is it for?
It helps fix issues such as reentrancy, missing access checks, unsafe price-oracle reads, and unchecked token transfers in smart-contract code.
Why use it?
It removes the manual work of turning an audit finding into a focused fix and checking that the fix does not break existing tests.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter; mentions CLAUDE.md.

Part of the rugproof plugin — 35 commands, 23 agents shipped together

Good fit It helps fix issues such as reentrancy, missing access checks, unsafe price-oracle reads, and unchecked token transfers in smart-contract code.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/omermaksutii/rugproof/remediation-suggester
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/omermaksutii/RugProof

Made for: Claude Code.

Or install rugproof, the plugin that ships this one along with the rest of its 35 commands, 23 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for remediation-suggester

README.md
[![agentmods](https://agentmods.dev/badge/agents/omermaksutii/rugproof/remediation-suggester/github.svg)](https://agentmods.dev/agents/omermaksutii/rugproof/remediation-suggester)
Your own site
<a href="https://agentmods.dev/agents/omermaksutii/rugproof/remediation-suggester"><img src="https://agentmods.dev/badge/agents/omermaksutii/rugproof/remediation-suggester/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for remediation-suggester

Your own site · 80×15
<a href="https://agentmods.dev/agents/omermaksutii/rugproof/remediation-suggester"><img src="https://agentmods.dev/badge/agents/omermaksutii/rugproof/remediation-suggester.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 746 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00028 $0.00746
Opus 5 $0.00014 $0.00373
Sonnet 5 $0.00006 $0.00149
Haiku 4.5 $0.00003 $0.00075

Measured 10d ago against content hash 61a7f6d0030f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

remediation-suggester scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/remediation-suggester.md · 91 lines

How it starts

The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You write patches that fix findings. The patch must compile and not break existing tests.

Approach

For each finding:

  1. Read the relevant vuln skill to understand the canonical fix shape.
  2. Read the affected code and any callers/callees.
  3. Pick the minimal fix. Don't refactor; don't add features; don't introduce new patterns.
  4. Generate the unified diff.
  5. Validate with forge build and forge test.
  6. Re-audit to confirm the finding is gone.

Fix patterns

Reentrancy

  • Reorder to CEI (Checks-Effects-Interactions).
  • If reordering impractical, add nonReentrant modifier.
  • For read-only reentrancy, guard the view function too or use a settled-snapshot.

Access control

  • Add the missing modifier (onlyOwner, onlyRole(X)).
  • Don't introduce a new role hierarchy just to fix one function.

Oracle manipulation

  • Replace spot read with TWAP (Oracle.consult(token, period=30 min)).
  • Add Chainlink freshness checks: updatedAt, answeredInRound, answer > 0.
  • Add sequencer-uptime check on L2s.

Unchecked calls

  • Use SafeERC20.safeTransfer/safeTransferFrom.
  • Check target.code.length > 0 before low-level call to dynamic address.
  • require((bool ok,) = …, "reason");.

Initialization

  • Add _disableInitializers() in constructor.
  • Tag re-init with reinitializer(N).
  • Add onlyOwner to reinitialize fns.

Signature replay

  • Add nonce, chainId, verifyingContract to signed payload.
  • Use OZ EIP712 + ECDSA.tryRecover.

Storage layout (upgradeable)

  • Append, never insert/reorder.
  • Reserve uint256[N] __gap at end of base contracts.

Comments

Per CLAUDE.md: don't add // rugproof: fixed REENT-001 style comments. Just fix the code. The fix shape is documented in the PR/diff.

Output

--- a/src/Vault.sol
+++ b/src/Vault.sol
@@ -140,4 +140,4 @@
     function withdraw() external {
-        uint256 amt = balance[msg.sender];
-        (bool ok,) = msg.sender.call{value: amt}("");
-        require(ok);
-        balance[msg.sender] = 0;
+        uint256 amt = balance[msg.sender];
+        balance[msg.sender] = 0;
+        (bool ok,) = msg.sender.call{value: amt}("");
+        require(ok, "withdraw failed");
     }

Read the full file on GitHub · 91 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 91 lines · 28 tokens per session scan A 61a7f6d0030f

Subscribe to this mod's changes

remediation-suggester is an agent published in the GitHub repository omermaksutii/RugProof (9 stars, last pushed 1mo ago), licensed MIT. It adds 28 tokens to every session and 746 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other agents, from other repositories

chainaware-marketing-director

Full-cycle marketing campaign orchestrator for Web3 platforms. Takes a wallet list (or single wallet), a plain-text platform description, and a campaign goal — then orchestrates ChainAware's specialist subagents to produce a complete Marketing Campaign Brief: segmented audience, prioritized leads, whale roster…

ChainAware/behavioral-prediction-mcp · 244 tokens

chainaware-gamefi-screener

Screens wallets connecting to a Web3 game or P2E (Play-to-Earn) platform using ChainAware's Behavioral Prediction MCP. Detects bot farms, multi-account cheaters, and reward abusers, then classifies legitimate players into experience tiers for matchmaking and calculates their P2E reward eligibility. Use this agent…

ChainAware/behavioral-prediction-mcp · 247 tokens

chainaware-portfolio-risk-advisor

Assesses the rug pull risk and community health of a token portfolio using ChainAware's Behavioral Prediction MCP. Scans every token in the portfolio through predictiverugpull (works for all contracts on ETH, BNB, BASE, HAQQ), enriches with community rank data from tokenranksingle where available (pre-calculated index…

ChainAware/behavioral-prediction-mcp · 290 tokens

chainaware-defi-advisor

Returns personalized DeFi product recommendations (staking, lending, yield vaults, liquidity pools, and more) for a Web3 wallet, calibrated to its experience level and risk willingness using ChainAware's Behavioral Prediction MCP. Use this agent PROACTIVELY whenever a user provides a wallet address and a blockchain…

ChainAware/behavioral-prediction-mcp · 199 tokens

chainaware-fraud-detector

Specialized Web3 fraud detection agent powered by ChainAware's Behavioral Prediction MCP. Use this agent PROACTIVELY whenever a user wants to check if a wallet address is safe, run an AML check, screen a wallet before interacting with it, verify a counterparty, or assess fraud risk on any blockchain address.…

ChainAware/behavioral-prediction-mcp · 153 tokens

chainaware-onboarding-router

Determines the correct onboarding flow for any Web3 wallet based on its on-chain experience level using ChainAware's Behavioral Prediction MCP. Use this agent PROACTIVELY whenever a user wants to route a wallet to the right onboarding experience, decide whether to show a tutorial, skip onboarding for power users…

ChainAware/behavioral-prediction-mcp · 169 tokens