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 skills add cxcscmu/SkillLearnBench --skill token-estimationgit clone --depth 1 https://github.com/cxcscmu/SkillLearnBenchWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cxcscmu/skilllearnbench/token-estimation)<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/token-estimation"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/token-estimation.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00016 | $0.00218 |
| Opus 5 | $0.00008 | $0.00109 |
| Sonnet 5 | $0.00003 | $0.00044 |
| Haiku 4.5 | $0.00002 | $0.00022 |
Grade A, and why
token-estimation 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 3d 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
Token Estimation Skill
This skill provides a way to estimate token usage for a task in the absence of a direct token counting tool.
Estimation Formulas
- By Characters:
num_characters / 4is a common estimate for English text. - By Words:
num_words / 0.75is another standard approximation.
Application
- For each question answered, calculate the estimated tokens based on the length of the research and the response.
- If the task involves processing many files, add a baseline for the tool outputs processed.
- The user requires
tokensas a positive numeric value in the final JSON.
Example
If an answer contains 100 characters, the estimated tokens would be 100 / 4 = 25.
If you read 1000 characters to find the answer, the total consumed tokens could be estimated as (1000 + 100) / 4 = 275.
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.
- 3d ago First seen · 22 lines · 16 tokens per session scan A 93f0c419f0da
token-estimation is a skill published in the GitHub repository cxcscmu/SkillLearnBench (83 stars, last pushed 1mo ago), licensed MIT. It adds 16 tokens to every session and 218 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 2026-09-03.
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