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 curie-eng/curie --skill text-statsgit clone --depth 1 https://github.com/curie-eng/curieWrote 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/curie-eng/curie/text-stats)<a href="https://agentmods.dev/skills/curie-eng/curie/text-stats"><img src="https://agentmods.dev/badge/skills/curie-eng/curie/text-stats/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/curie-eng/curie/text-stats"><img src="https://agentmods.dev/badge/skills/curie-eng/curie/text-stats.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00056 | $0.00273 |
| Opus 5.5 | $0.00022 | $0.00109 |
| Sonnet 5.5 | $0.00011 | $0.00055 |
| Haiku 4.5 | $0.00006 | $0.00027 |
Grade A, and why
text-stats 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 1mo 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
Text statistics
When to run
The user asks how many words or characters a passage has, or how long it takes to read.
How to answer
- Take the text the user provided (or asks about).
- Call the in-bundle engine's tool for the metric requested:
word_countfor a word total.char_countfor a character total (passinclude_whitespace: falseto exclude spaces).reading_time_minutesfor an estimated read time at 200 wpm.
- Report the number plainly, naming the metric and the text it applies to.
Notes
The engine runs as an in-bundle stdio MCP server (scripts/engine_server.py,
declared in .mcp.json). The harness spawns it as a subprocess; there is no
network service and nothing to provision. See this bundle's README for when to
prefer this shape over a CLI subprocess.
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.
- 1mo ago First seen · 28 lines · 56 tokens per session scan A 5b8636bc6494
text-stats is a skill published in the GitHub repository curie-eng/curie (37 stars, last pushed today), licensed Apache-2.0. It adds 56 tokens to every session and 273 once invoked, about $0.0002 per session on Opus 5.5. 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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