mcp2agy-fix

mcp2agy-fix is a skill for Claude Code, Codex from uziii2208/mcp2agy. It costs 89 tokens per session (1,560 once invoked), scanned A, original, MIT.

A security-fix helper that creates small, testable code changes for confirmed vulnerabilities. It also turns each proof-of-concept demonstration into a regression test, which checks that the flaw stays fixed.

In plain words
What is it for?
It applies fixes for several vulnerability categories, checks all affected call sites, reviews the patch for unintended effects, and produces a unified diff and regression tests.
Why use it?
It reduces the risk of incomplete patches, missed vulnerable code paths, or fixes that introduce a new timing-related bug.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/uziii2208/mcp2agy/fix
Any agent
npx skills add uziii2208/mcp2agy --skill fix
Clone the repo
git clone --depth 1 https://github.com/uziii2208/mcp2agy

Made for: Claude Code, Codex.

Per session 89 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,560 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00089 $0.01560
Opus 5 $0.00044 $0.00780
Sonnet 5 $0.00018 $0.00312
Haiku 4.5 $0.00009 $0.00156

Measured 2d ago against content hash b535193b089c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mcp2agy-fix 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 2d 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/plugins/mcp2agy/skills/fix/SKILL.md · 146 lines

How it starts

The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/fix — Security Code Remediation & Subagent (v3.0.0)

0. Prime Directive & Remediation Principles

The Fixer produces patches that are minimal, correct, and provably effective:

  1. Multi-Site Completeness: Patch EVERY vulnerable call site in the project, not just the one hit by the PoC.
  2. Atomicity Check: Ensure the fix does NOT introduce a new TOCTOU race condition (e.g. check-then-act os.path.exists before open instead of O_CREAT | O_EXCL).
  3. No Scope Creep: Change ONLY what is required to remediate the vulnerability. Do not refactor unrelated code.
  4. PoC-as-Regression-Test: Convert the Verifier's PoC into a permanent automated unit test that passes with the patch and fails without it.

Operating Modes:

  1. Subagent Mode (Delegated by Orchestrator):
    • Consumes verified_findings.yaml from mcp2agy_workspace/auditor_zone/results/<run_id>/.
    • Generates minimal diff at mcp2agy_workspace/auditor_zone/results/<run_id>/fixes.diff.
    • Generates regression test harnesses in mcp2agy_workspace/auditor_zone/results/<run_id>/regression_tests/.
    • Responds to the Orchestrator with patch metrics.
  2. Standalone Mode (CLI /fix <finding_yaml>):
    • Generates patch and test harness for individual finding.

⚠️ CRITICAL: MCP Tool Usage Policy

NEVER call call_mcp_tool() or any MCP server tools directly when running as a subagent. MCP tools (e.g., generate_fix, check_fix_completeness, list_fix_templates) are lazy-loaded and require interactive user approval. When a subagent calls an MCP tool, it blocks indefinitely.

Instead, generate fixes using native tools:

  • view_file — Read verified findings, source code, and evidence
  • replace_file_content — Apply minimal code patches
  • write_to_file — Generate regression test harnesses and diff files
  • grep_search — Find all call sites for multi-site completeness
  • run_command — Run tests and verify fixes

If the Orchestrator has pre-gathered MCP tool data, it will be provided in your invocation prompt.

Read the full file on GitHub · 146 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. 2d ago First seen · 146 lines · 89 tokens per session scan A b535193b089c

Subscribe to this mod's changes

mcp2agy-fix is a skill published in the GitHub repository uziii2208/mcp2agy (1 stars, last pushed 3d ago), licensed MIT. It adds 89 tokens to every session and 1,560 once invoked, about $0.0004 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 skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

chat-perf

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens