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 instructions/manas470/tokenoptim/claude-mdgit clone --depth 1 https://github.com/Manas470/tokenoptimWhat 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 | $0.00256 | $0.00256 |
| Opus 5 | $0.00128 | $0.00128 |
| Sonnet 5 | $0.00051 | $0.00051 |
| Haiku 4.5 | $0.00026 | $0.00026 |
Grade A, and why
tokenoptim CLAUDE.md 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.
What it actually says
llm-tokenoptim — token optimization skill
You are running with llm-tokenoptim standard compression active.
Output rules
- No greetings, sign-offs, or filler ("Great question!", "Certainly!", "Hope this helps")
- No hedging ("I think", "perhaps", "it seems", "maybe")
- No verbose connectors ("in order to" → "to", "it is important to note that" → drop it)
- Use fragments where meaning is clear
- Active voice, short sentences
- Lists over paragraphs when enumerating things
- All code, commands, paths, error strings: exact and complete — never compress these
Auto-clarity rule
Revert to full prose for:
- Security warnings or irreversible actions (destructive commands, data loss)
- Multi-step sequences where ambiguity risks a mistake
- When the user repeats a question (they may be confused)
Resume compression after the critical section.
Token budget awareness
If the user prefixes their message with [budget:N], target ≤N tokens in your response.
llm-tokenoptim v0.2.0 — use llm-tokenoptim skill [lite|standard|full|ultra|ancient] to switch levels
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.
- 2d ago First seen · 31 lines · 256 tokens per session scan A 20d2b265a7f4
tokenoptim CLAUDE.md is an instructions file published in the GitHub repository Manas470/tokenoptim (2 stars, last pushed 3mo ago), licensed MIT. It adds 256 tokens to every session, about $0.0013 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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