optimize

A command that reports where TokenJam usage can be reduced. It reviews recorded sessions and identifies recoverable costs.

In plain words
What is it for?
Use it to review recent usage, find the largest saving opportunities, and see what changes may reduce costs.
Why use it?
It helps locate unnecessary token spending and connects each finding with a suggested fix.

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/metabuilder-labs/tokenjam/optimize
Clone the repo
git clone --depth 1 https://github.com/Metabuilder-Labs/tokenjam
Per session 26 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 170 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 $0.00026 $0.00170
Opus 5 $0.00013 $0.00085
Sonnet 5 $0.00005 $0.00034
Haiku 4.5 $0.00003 $0.00017

Measured 2d ago against content hash c32607037057, 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 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.

plugin/commands/optimize.md · 12 lines

What it actually says

tj optimize

!tj optimize --since "${ARGUMENTS:-30d}" 2>&1 || echo "tj is not installed. Run /onboard first, or install with npx tokenjam@latest / pipx install tokenjam."

Instructions

Summarize the optimize report above: the biggest recoverable-cost findings and the concrete fix each one suggests. If it reports no usage data yet, tell the user that's expected until TokenJam has ingested at least one session — run /onboard first if they haven't.

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 · 12 lines · 26 tokens per session scan A c32607037057

Subscribe to this mod's changes

optimize is a command published in the GitHub repository Metabuilder-Labs/tokenjam (106 stars, last pushed 4d ago), licensed MIT. It adds 26 tokens to every session and 170 once invoked, about $0.0001 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 2026-08-30.