optimize

A command that looks for performance problems in code and suggests ways to fix them. Performance problems are code choices that make an application slower or use more resources than necessary.

In plain words
What is it for?
Reviewing unstaged changes or a specified file or area, with issue locations, explanations, optimization examples, and prioritization by likely impact.
Why use it?
It gives a defined review process for finding costly code, explaining its impact, and weighing the likely benefit against the effort to change it.

Command

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 commands/rileyhilliard/agentrc/optimize
Clone the repo
git clone --depth 1 https://github.com/rileyhilliard/agentrc
Per session 7 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 216 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 $0.00007 $0.00216
Opus 5 $0.00003 $0.00108
Sonnet 5 $0.00001 $0.00043
Haiku 4.5 $0.00001 $0.00022

Measured yesterday against content hash 64e99f5829b1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

optimize 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 yesterday.

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.

.agentrc/commands/optimize.md · 37 lines

What it actually says

Use the Skill tool to invoke the optimizing-performance skill to analyze code for performance issues and suggest optimizations.

Arguments:

  • $ARGUMENTS: Optional file path or area to focus on (defaults to unstaged changes)

If $ARGUMENTS is empty:

  1. Run git diff to get unstaged changes
  2. Focus on optimizing the unstaged changes

If $ARGUMENTS is provided:

  • Use it as the focus area for optimization

When invoking the ce:optimizing-performance skill:

"Analyze code for performance issues and suggest optimizations.

Focus area: [unstaged changes from git diff OR $ARGUMENTS]

Provide:

  • Specific file:line references for each issue
  • Explanation of the performance impact
  • Code examples showing the optimization
  • Estimated improvement (if measurable)
  • Cost-benefit analysis for each proposed optimization

Prioritize high-impact optimizations over micro-optimizations."

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. yesterday First seen · 37 lines · 7 tokens per session scan A 64e99f5829b1

Subscribe to this mod's changes

optimize is a command published in the GitHub repository rileyhilliard/agentrc (3 stars, last pushed 6mo ago), licensed MIT. It adds 7 tokens to every session and 216 once invoked, about $0.0000 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.