text-statistics
Skill2 starsChanged 5 months agoMITView on GitHub
Compute readability and structural statistics for a block of text: word count, sentence count, character count, average word length, and an approximate Flesch reading-ease score. Trigger when the user asks to analyze text, count words, measure readability, or get text statistics.
In this repository15 other files it gives its agents.
- change-impact-analysisSkill
- legacy-discoverySkill
- spec-governanceSkill
- task-decompositionSkill
- test-generationSkill
- topology-planningSkill
- ui-modernizationSkill
- jira-ticketSkill
- servicenow-ticketSkill
- speckit-constitutionSkill
- speckit-planSkill
- speckit-specifySkill
- speckit-tasksSkill
- my-skillSkill
- xquik-social-dataSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 55
Call the skill with a single text input.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Text Statistics Skill
Analyze a block of text and report structural and readability metrics.
How it works
- Tokenize the input into sentences and words.
- Count words, sentences, and characters.
- Estimate syllables per word to compute an approximate Flesch reading-ease score.
- Return all metrics as a structured object.
Usage
Call the skill with a single text input. The skill returns the metrics
described in the outputs section of the frontmatter.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.