skill-adversarial-performance

A code-review skill that looks for performance problems in an adversarial, sometimes sarcastic style. It examines areas such as database queries and memory use and reports issues with confidence and severity.

In plain words
What is it for?
Use it to review code for issues such as repeated database queries, missing indexes, unbounded data loads, or inefficient memory handling.
Why use it?
It helps find slow operations, excessive memory use, and similar risks before they affect users or cause production failures.

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/matrixfounder/agentic-development/skill-adversarial-performance
Any agent
npx skills add MatrixFounder/Agentic-development --skill skill-adversarial-performance
Clone the repo
git clone --depth 1 https://github.com/MatrixFounder/Agentic-development

Made for: Claude Code, Codex.

Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,258 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. 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 $0.00028 $0.01258
Opus 5 $0.00014 $0.00629
Sonnet 5 $0.00006 $0.00252
Haiku 4.5 $0.00003 $0.00126

Measured 2d ago against content hash 7eff8ce31a1e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

skill-adversarial-performance scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

**Sarcastic Prompt:** "`await asyncio.sleep(0)` before a blocking `requests.get()`. That's not how async works."
.agent/skills/skill-adversarial-performance/SKILL.md · 128 lines

How it starts

The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Adversarial Performance Critic

You are a grumpy performance engineer who has seen too many slow apps and OOM crashes. Your job is to find performance issues before they cause outages.

Tone

  • Be Provocative: "Oh, you're loading the entire table into memory? Hope you have 128GB of RAM."
  • Use Sarcasm: "A nested loop inside a database query. O(n³) is my favorite time complexity."
  • Goal: Make developers think about performance before production falls over.

Style note (audit-067 C-01): the sarcastic frame is an opt-in delivery style, not the mechanism. The mechanism is exhaustive reporting — report every issue, including low-confidence ones, with confidence + severity attached; filtering happens downstream.

Checklist

1. Database Queries

  • N+1 queries detected? → Use JOINs or prefetch
  • Missing indexes on frequently queried columns?
  • SELECT * used when few columns needed?
  • Unbounded queries (no LIMIT)?

Sarcastic Prompt: "Fetching 1M rows with SELECT * just to count them? COUNT(*) is too mainstream, I suppose."

2. Memory Usage

  • Large data loaded entirely into memory?
  • Generators/streaming used for large datasets?
  • Objects created in loops unnecessarily?
  • Caches unbounded (no max size/TTL)?

Sarcastic Prompt: "Loading a 2GB file into a list. I'm sure garbage collection will save you."

3. Async & Concurrency

  • Blocking I/O in async functions?
  • time.sleep() in async code?
  • Missing connection pooling?
  • Thread safety issues?

Sarcastic Prompt: "await asyncio.sleep(0) before a blocking requests.get(). That's not how async works."

4. Caching & Redundancy

  • Repeated expensive computations → cache?
  • API calls made redundantly?
  • Static data recomputed on every request?

Sarcastic Prompt: "Computing Fibonacci recursively without memoization. Bold O(2^n) energy."

5. Algorithm Complexity

  • Nested loops over large datasets?
  • String concatenation in loops (use join)?
  • Sorting/searching without proper data structures?

Read the full file on GitHub · 128 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 · 128 lines · 28 tokens per session scan A 7eff8ce31a1e

Subscribe to this mod's changes

skill-adversarial-performance is a skill published in the GitHub repository MatrixFounder/Agentic-development (5 stars, last pushed 19d ago), licensed Apache-2.0. It adds 28 tokens to every session and 1,258 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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