codeprobe-performance

A code review skill that looks for performance and scalability problems in backend, database, concurrency, and frontend code. Scalability means continuing to work acceptably as data, users, or requests increase.

In plain words
What is it for?
Use it to check for repeated database queries, missing indexes, unbounded reads, inefficient algorithms, caching gaps, concurrency bugs, and unnecessary frontend work.
Why use it?
It identifies work that may become slow, memory-heavy, or unreliable as the application grows.

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/nishilbhave/codeprobe/codeprobe-performance
Any agent
npx skills add nishilbhave/codeprobe --skill codeprobe-performance
Clone the repo
git clone --depth 1 https://github.com/nishilbhave/codeprobe

Made for: Claude Code, Codex.

Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,187 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 $0.00086 $0.02187
Opus 5 $0.00043 $0.01094
Sonnet 5 $0.00017 $0.00437
Haiku 4.5 $0.00009 $0.00219

Measured 2d ago against content hash 535c8507eb36, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

codeprobe-performance 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.

skills/codeprobe-performance/SKILL.md · 131 lines

How it starts

The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Standalone Mode

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

  1. Read ../codeprobe/shared-preamble.md (resolve relative to this SKILL.md's location — the sibling codeprobe skill directory — not the user's project) for the output contract, execution modes, and constraints.
  2. Load applicable reference files from ../codeprobe/references/ (same resolution) 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 Prefix What to Detect How to Detect Severity
PERF Eloquent relationship access inside loop without eager loading Search 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. Major
PERF Any ORM lazy-loading inside iteration Look 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(). Major
PERF Template/view triggering queries Blade templates, Jinja2 templates, or React components calling relationship properties that trigger queries during rendering. Major

Read the full file on GitHub · 131 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 · 131 lines · 86 tokens per session scan A 535c8507eb36

Subscribe to this mod's changes

codeprobe-performance is a skill published in the GitHub repository nishilbhave/codeprobe (5 stars, last pushed 1mo ago), licensed MIT. It adds 86 tokens to every session and 2,187 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.

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