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Agent Skill · 研究检索

codeprobe-performance(代码探针性能)

codeprobe-performance 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

codeprobe-performance 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为可写文件;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 48,867。

总安装 674周安装 27GitHub Stars 4下载 218核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:codeprobe-performance(代码探针性能)
来源仓库:https://github.com/nishilbhave/codeprobe
仓库路径:skills/codeprobe-performance
安装命令:
npx skills add https://github.com/nishilbhave/codeprobe --skill codeprobe-performance
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/nishilbhave/codeprobe --skill codeprobe-performance

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

codeprobe-performance 审计 N+1 查询、缺失索引与无界数据加载等性能瓶颈。适用于数据库访问层、API 接口与批量处理逻辑的效率优化。提供索引建议、分页策略与缓存提示,降低响应时间开销。安装前应核实是否允许读取 SQL 语句与 ORM 映射配置。

建议在测试环境先行验证优化效果,防止生产环境出现意外降级。

来源仓库内路径:skills/codeprobe-performance

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/nishilbhave/codeprobe --skill codeprobe-perfor…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要可写文件,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

codeprobe-performance 怎么安装?

在终端执行 npx skills add https://github.com/nishilbhave/codeprobe --skill codeprobe-performance。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

codeprobe-performance 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

codeprobe-performance 需要什么权限?

权限级别是可写文件。该 Skill 可能写入或修改本地文件,使用前需要确认目标目录和修改范围。

codeprobe-performance 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

codeprobe-performance 用的人多吗?

公开数据是累计安装 674 次,近一周安装 27 次,下载 218 次,GitHub 4 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

codeprobe-performance 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
codeprobe-performance

代码探针性能 · 本页

6744可写文件未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Standalone Mode

If invoked directly (not via the orchestrator), you must first:

  1. Read ../codeprobe/shared-preamble.md for the output contract, execution modes, and constraints.
  2. Load applicable reference files from ../codeprobe/references/ based on the project's tech stack.
  3. Default to full mode unless the user specifies otherwise.

Performance & Scalability Auditor

Domain Scope

This sub-skill detects performance and scalability issues across these categories:

  1. N+1 Queries — Lazy-loading relationships inside loops
  2. Missing Indexes — WHERE/ORDER BY on non-indexed columns
  3. Unbounded Queries — Model::all() without pagination/limit
  4. Memory — Loading entire files into memory, array accumulation in loops
  5. Caching — Repeated identical queries, missing TTL, stale cache after writes
  6. Algorithmic Efficiency — O(n^2) in hot paths, nested loops, sorting in loops
  7. Concurrency — Race conditions, non-idempotent queue jobs, shared mutable state
  8. Frontend Performance — Unnecessary re-renders, bundle size, missing lazy loading

What It Does NOT Flag

  • Premature optimization in non-hot-path code — proportional design matters. A utility function called once at startup doesn't need the same optimization as a request handler.
  • Development-only debug queries — queries in seeders, dev-only commands, or debug endpoints.
  • Batch processing scripts — scripts intentionally designed to process everything (migrations, data backfills) where unbounded queries may be appropriate.
  • O(n^2) on small bounded collections (<100 items) — nested loops on small known-size arrays are fine.
  • Frontend SSR/build-time code — server components and build scripts have different performance profiles than client-side code.

Detection Instructions

N+1 Queries

ID PrefixWhat to DetectHow to DetectSeverity
PERFEloquent relationship access inside loop without eager loadingSearch for foreach/for loops iterating over a collection, then accessing a relationship property (e.g., $order->items, $user->profile) inside the loop body. Check whether the query that produced the collection includes with() or load() for that relationship.Critical
PERFAny ORM lazy-loading inside iterationLook for patterns where a database query is implicitly triggered inside a loop: Django querysets accessed per-iteration, SQLAlchemy lazy loads, Prisma relation access in .map().Critical
PERFTemplate/view triggering queriesBlade templates, Jinja2 templates, or React components calling relationship properties that trigger queries during rendering.Major

Missing Indexes

ID PrefixWhat to DetectHow to DetectSeverity
PERFWHERE/ORDER BY on non-indexed columnsCross-reference query conditions (where(), orderBy(), WHERE, ORDER BY) with migration files or schema definitions to check for matching indexes.Major
PERFForeign keys without indexesCheck migration files for foreignId(), foreign(), references() without corresponding index definitions. Most ORMs add these automatically, but raw migrations may miss them.Minor
PERFComposite queries needing compound indexesMultiple where() conditions on different columns in the same query, or where() + orderBy() combinations that would benefit from a compound index.Minor

Unbounded Queries

ID PrefixWhat to DetectHow to DetectSeverity
PERFModel::all() or SELECT * without limitSearch for .all(), ::all(), findAll(), SELECT * FROM without LIMIT, paginate(), take(), or limit().Major
PERFMissing cursor/chunk for large dataset processingOperations that get() or load entire collections when processing large datasets. Should use cursor(), chunk(), lazy(), or equivalent streaming approach.Major

Memory

ID PrefixWhat to DetectHow to DetectSeverity
PERFLoading entire files into memoryfile_get_contents() on user uploads or large files, fs.readFileSync() on variable-size files, Python open().read() without size limits.Major
PERFArray accumulation in loopsArrays that grow inside loops without bounds or cleanup — collecting results in memory that could be streamed or yielded.Minor
PERFLarge collections instead of generatorsReturning full arrays/lists where generators (yield), lazy collections, or iterators would be more memory-efficient for large datasets.Minor

Caching

ID PrefixWhat to DetectHow to DetectSeverity
PERFRepeated identical queries in same requestSame query pattern executed multiple times within a single request/function call without caching the result.Minor
PERFCache without TTLCache::put(), cache.set(), Redis SET without expiration. Data cached forever risks staleness.Minor
PERFCache not invalidated after writesWrite operations (create/update/delete) that don't clear or update related cache entries. Stale cache served after mutation.Major

Algorithmic Efficiency

ID PrefixWhat to DetectHow to DetectSeverity
PERFO(n^2) or worse in hot pathsNested loops iterating over the same or related collections. array_search/in_array/includes() inside loops (linear search in a loop = O(n^2)).Major
PERFSorting inside loopssort(), usort(), array_sort(), .sort() called inside a loop body.Major
PERFHashmap-replaceable linear searchin_array(), .includes(), .indexOf(), list.index() used repeatedly on the same array where building a Set/dict/hashmap first would be O(1) per lookup.Minor

Concurrency

ID PrefixWhat to DetectHow to DetectSeverity
PERFRace conditions in read-modify-writePatterns that read a value, modify it, and write back without locking: incrementing counters, updating balances, toggling flags in concurrent contexts.Critical
PERFQueue jobs without idempotencyQueue/job handlers that don't check for duplicate execution. Jobs that create resources without checking if already created. Missing unique constraints on job-created data.Major
PERFShared mutable state in async contextsGlobal/module-level mutable variables accessed in async handlers, request-scoped data stored in module scope.Major

Frontend Performance

ID PrefixWhat to DetectHow to DetectSeverity
PERFUnnecessary re-rendersMissing React.memo, useMemo, useCallback on expensive computations or components receiving new object/array references on every render. Objects/arrays created inline in JSX props.Minor
PERFLarge bundle importsimport _ from 'lodash' (imports entire library), import moment from 'moment' (large library where date-fns or dayjs suffice), import * as icons from 'icon-library'.Minor
PERFMissing lazy loadingNo React.lazy() / dynamic import() for route-level code splitting. Heavy components loaded eagerly on initial page load.Minor

Optional Script Integration

When scripts/complexity_scorer.py output is available (run by the orchestrator during /codeprobe audit), use it to identify high-complexity functions as performance hot-spot candidates. Functions rated "high" or "very_high" that also appear in hot paths (request handlers, loop bodies, frequently-called utilities) are strong signals for algorithmic efficiency findings.


ID Prefix & Fix Prompt Examples

All findings use the PERF- prefix, numbered sequentially: PERF-001, PERF-002, etc.

Fix Prompt Examples

  • "In OrderController@index (line 22), add ->with('items', 'customer') to the Order::query() call to fix the N+1 problem — currently loading 2 relations lazily inside the Blade loop at orders/index.blade.php:15."
  • "Replace Product::all() at line 30 of CatalogService.php with Product::query()->paginate(25) or Product::cursor() if processing all records. The current query loads all products into memory."
  • "In ReportGenerator@aggregate (lines 45-60), the nested loop iterating $orders inside $customers is O(n*m). Build a lookup hashmap before the outer loop: $ordersByCustomerId = collect($orders)->groupBy('customer_id')."
  • "Replace import _ from 'lodash' at line 3 of src/utils/helpers.ts with specific imports: import debounce from 'lodash/debounce' to reduce bundle size."

平台分布

Codex

37.73%
按下载量换算82

Claude

31.69%
按下载量换算69

Cursor

16.59%
按下载量换算36

Gemini CLI

10%
按下载量换算22

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

可写文件

该 Skill 可能写入或修改本地文件,使用前需要确认目标目录和修改范围。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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