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.
npx agentmods add commands/wesammustafa/opencode-primer/optimizegit clone --depth 1 https://github.com/wesammustafa/opencode-primerWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00010 | $0.00303 |
| Opus 5 | $0.00005 | $0.00151 |
| Sonnet 5 | $0.00002 | $0.00061 |
| Haiku 4.5 | $0.00001 | $0.00030 |
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.
What it actually says
Analyze the target for performance issues: $ARGUMENTS (or the current branch's changes if empty).
Cover these dimensions in this order:
- Algorithmic — wrong data structure, O(n²) where O(n) is possible, repeated work.
- I/O — N+1 queries, missing indexes, sync calls on hot paths, unbatched network requests.
- Memory — unbounded growth, leaks, large in-memory snapshots that could stream.
- Frontend (if applicable) — re-render cascades, large bundles, unmemoized expensive renders, blocking main-thread work.
- Micro-optimizations — only if (1)–(4) are clean and the call site is genuinely hot.
For each suggestion, output:
[Impact] <summary>
Where: <file:line>
Before: <snippet>
After: <snippet>
Why: <one sentence — what's faster and roughly by how much>
Impact tiers: High (>10× or removes the bottleneck) · Medium (2–10×) · Low (small constant factor).
Don't make the changes yet. End by asking which suggestions to apply.
Optional flag — pass --apply in arguments to skip the discussion and implement the High-impact suggestions directly.
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.
- yesterday First seen · 31 lines · 10 tokens per session scan A 208e2abf8646
optimize is a command published in the GitHub repository wesammustafa/opencode-primer (384 stars, last pushed 1mo ago), licensed MIT. It adds 10 tokens to every session and 303 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.
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fix
修复Bug并固化经验为skill/rule.
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ticket
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