review-performance

A focused performance review for Cratis projects, covering event-sourced data, MongoDB queries, .NET code, and React rendering.

In plain words
What is it for?
Use it to inspect changed code for full-collection reads, unindexed queries, N+1 queries, oversized responses, unnecessary allocations, and excessive React renders.
Why use it?
It identifies inefficient data access, unnecessary memory use, repeated queries, and avoidable browser work.

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/cratis/ai/review-performance
Any agent
npx skills add Cratis/AI --skill review-performance
Clone the repo
git clone --depth 1 https://github.com/Cratis/AI

Made for: Claude Code, Codex.

Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 596 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 $0.00045 $0.00596
Opus 5 $0.00023 $0.00298
Sonnet 5 $0.00009 $0.00119
Haiku 4.5 $0.00005 $0.00060

Measured 2d ago against content hash 09b8a20a88cc, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

review-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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.ai/skills/review-performance/SKILL.md · 56 lines

How it starts

The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Perform a focused performance review of changed code.

Chronicle / Event Sourcing

  • Projections use AutoMap (on by default) — avoids manual mapping cost
  • Projections do NOT join on the read model (forces full re-read)
  • Reactors do NOT re-query the event log inside On() — use event data directly
  • No eager loading of entire event sequences without paging/filtering
  • New projections can replay all historical events without crashing
  • Events are small — no large blobs or base64-encoded content embedded

MongoDB / Read Models

  • Queries filter on indexed fields — no unintentional full-collection scans
  • Paged queries use .Skip() + .Take() — never load all rows
  • No N+1 pattern — single query returns all needed data
  • Read-model records do not embed large nested collections that are never fully iterated

ASP.NET Core / Commands & Queries

  • Query endpoints do not hydrate the full collection when only a count is needed
  • Command validators are synchronous and in-memory — no I/O in validation
  • No await Task.Run(() => syncWork) wrapping for naturally async work
  • Response payloads include only fields the client uses — no over-fetching

React / TypeScript

  • DataTable uses lazy + paginator for collections larger than ~20 rows
  • No inline object/array literals passed as props (causes identity change every render)
  • useEffect dependencies are correct — no missing deps, no over-broad deps
  • Large-collection components wrapped in React.memo or use stable references
  • No JSON.parse(JSON.stringify(x)) deep cloning

General .NET

  • No LINQ .ToList() before .Where() — filter before materialising
  • IEnumerable<T> not enumerated multiple times — materialise once if needed
  • Large object logging uses {@obj} only at Debug level

Risk classification

  • 🔴 High — measurable degradation at moderate load — must fix before merge
  • 🟡 Medium — could degrade under load or at scale
  • 🟢 Low — minor inefficiency or style issue

Read the full file on GitHub · 56 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 · 56 lines · 45 tokens per session scan A 09b8a20a88cc

Subscribe to this mod's changes

review-performance is a skill published in the GitHub repository Cratis/AI (2 stars, last pushed 5d ago), licensed MIT. It adds 45 tokens to every session and 596 once invoked, about $0.0002 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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