race-condition

A security checker for race conditions, where concurrent operations access the same shared data at nearly the same time. It focuses especially on time-of-check-to-time-of-use bugs, in which something changes between a check and the action that follows.

In plain words
What is it for?
Use it when reviewing file operations, account balances, quotas, counters, unique-name creation, or permission checks involving shared resources.
Why use it?
It helps prevent privilege escalation, double spending, lost updates, and corrupted data caused by operations that are not performed safely as one unit.

Skill for Claude CodeCodex

Part of the soundcheck plugin — 50 skills, 7 agents, 2 hooks shipped together

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/thejefflarson/soundcheck/race-condition
Any agent
npx skills add thejefflarson/soundcheck --skill race-condition
Clone the repo
git clone --depth 1 https://github.com/thejefflarson/soundcheck

Made for: Claude Code, Codex.

Or install soundcheck, the plugin that ships this one along with the rest of its 50 skills, 7 agents, 2 hooks.

Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 753 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 $0.00060 $0.00753
Opus 5 $0.00030 $0.00377
Sonnet 5 $0.00012 $0.00151
Haiku 4.5 $0.00006 $0.00075

Measured 3d ago against content hash 77070970d51c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

race-condition 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 3d 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.

.claude/skills/race-condition/SKILL.md · 62 lines

How it starts

The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Race Condition Security Check (CWE-362)

What this checks

Protects against time-of-check-to-time-of-use (TOCTOU) and other race conditions where concurrent access to shared state creates a window for attackers to manipulate data between a check and its corresponding action. Exploitation leads to privilege escalation, double-spend, and data corruption.

Vulnerable patterns

  • File existence checked before opening, deleting, or creating — the file can be swapped between the check and the operation.
  • Balance, quota, or counter read into memory, modified, then written back without locking or a transaction — concurrent updates lose writes or double-spend.
  • "Does this username exist? if not, create it" with no database-level uniqueness constraint — two concurrent callers both see "no" and both create.
  • Privilege or ownership checked in one call, then a separate later call performs the action on the same resource — the resource may have changed between calls.

Fix immediately

Flag the vulnerable code and explain the risk. Then suggest a fix that establishes these properties. Translate each property into the audited file's language, database driver, and filesystem API — use the platform's documented atomic primitives.

  1. No check-then-act sequence on shared state runs without atomicity. The check and the act collapse into a single atomic operation, or both sit inside a lock, transaction, or database-level guard. A read followed by a separate write is the exact bug — merge them into a conditional update that returns the affected row count.
  2. Balance, counter, and quota updates use atomic increments or compare-and-swap — never a read-modify-write sequence in application code. Under concurrency the read-modify-write loses every interleaved update; the database or atomic type is the correct place for the mutation.
  3. File operations that depend on existence use atomic primitives — exclusive-create flags, atomic rename, atomic link. A separate exists check followed by an open is TOCTOU-exploitable; the atomic flag short-circuits the window.
  4. Uniqueness constraints live in the database, not in application code. An "exists then create" pattern races two ways with itself; a uniqueness index plus an insert-and-catch-duplicate pattern is race-free by construction.

Read the full file on GitHub · 62 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. 3d ago First seen · 62 lines · 60 tokens per session scan A 77070970d51c

Subscribe to this mod's changes

race-condition is a skill published in the GitHub repository thejefflarson/soundcheck (20 stars, last pushed 1mo ago), licensed MIT. It adds 60 tokens to every session and 753 once invoked, about $0.0003 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 2026-08-30.

Related

Other skills, from other repositories

make-skill

Use this skill when sedimenting a session into a reusable workspace skill. Triggers when the user wants to turn the current conversation, workflow, or troubleshooting path into a SKILL.md. Phrases like 'turn this into a skill', 'remember how I did X', 'save this workflow', 'make a skill from this', and any /make-skill…

agentscope-ai/QwenPaw · 85 tokens

make-skill

用于把当前会话沉淀为可复用的 workspace skill。当用户希望把当前对话、工作流或排错路径写成 SKILL.md 时触发。触发表达包括「把这个变成 skill」「记住我是怎么做 X 的」「保存这个工作流」「make a skill from this」以及任何 /make-skill 调用。.

agentscope-ai/QwenPaw · 84 tokens

terraform-skill

Use when working with Terraform or OpenTofu - creating modules, writing tests (native test framework, Terratest), setting up CI/CD pipelines, reviewing configurations, choosing between testing approaches, debugging state issues, implementing security scanning (trivy, checkov), or making infrastructure-as-code…

agentscope-ai/QwenPaw · 62 tokens

docx

Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of "Word doc", "word document", ".docx", or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when…

agentscope-ai/QwenPaw · 168 tokens

docx

当用户需要创建、读取、编辑或处理 Word 文档(.docx)时,使用此技能。触发场景包括提到“Word 文档”、“.docx”,或要求生成带目录、标题、页码、信头等格式的专业文档;也包括提取或重组 .docx 内容、插入或替换图片、在 Word 文件中查找替换、处理修订或批注,以及将内容整理为正式 Word 文档。如果用户要求生成“报告”“备忘录”“信函”“模板”等 Word / .docx 交付物,也应使用此技能。不要用于 PDF、电子表格、Google Docs,或与文档生成无关的一般编程任务。.

agentscope-ai/QwenPaw · 161 tokens

multi_agent_collaboration

Use this skill when another agent's expertise or context is needed, or when the user explicitly asks to involve another agent. First list agents, then use qwenpaw agents chat for two-way communication with replies.

agentscope-ai/QwenPaw · 47 tokens