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profile-detection

Scan repository markers to select language profiles for StatsClaw workflows.

89|17|Updated Mar 27, 2026
Search Tags:#workflow-automation#package-development#repository-scanning#profile-detection#language-profile#statsclaw#marker-matching
One-click install
npx skills add https://github.com/statsclaw/statsclaw --skill profile-detection
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: profile-detection
Source: https://github.com/statsclaw/statsclaw/tree/main/skills/profile-detection
Command: npx skills add https://github.com/statsclaw/statsclaw --skill profile-detection

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

StatsClaw requires the correct language profile to coordinate specialized AI agents for statistical package development workflows, but manually selecting and assigning profiles for each new target repository is time-consuming and prone to human error that disrupts workflow execution.

Core Features & Use Cases

  • Automatic Marker Scanning: Inspects the target repository root for language-specific file markers in a defined priority order to select the matching profile.
  • Disambiguation Handling: Resolves conflicts when multiple language markers are present by checking source file counts, README references, or prompting the user for input.
  • Profile Assignment: Writes the selected profile to the repository context file and run status file to ensure all downstream agents use the correct workflow conventions.
  • Use Case: When you point StatsClaw at a new Python statistical package repository, the skill automatically detects the pyproject.toml marker and loads the correct Python package profile without any manual configuration.

Quick Start

Allow the profile-detection skill to run automatically when you start a new StatsClaw session with a target repository to have the correct language profile applied immediately without manual input.

Frequently Asked Questions about profile-detection

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automatically detect the correct language profile for a new repository?▼

Automatic language profile detection scans the target repository root for language-specific file markers in a defined priority order. It selects the matching profile for supported ecosystems like R, Python, and Rust without manual configuration.

What happens if multiple language markers are found in a single repository?▼

When multiple language markers are present, disambiguation handling resolves conflicts by checking source file counts and README references, or by prompting the user for input to ensure the correct profile is selected.

How do I assign a package development workflow profile for a Python repository?▼

Assigning a package development profile involves detecting language-specific markers like pyproject.toml. The skill writes the selected profile to the repository context file to coordinate downstream AI agents.

Does StatsClaw workflow automation support statistical package development in Julia and Stata?▼

Yes, StatsClaw workflow automation supports statistical package development across multiple ecosystems, automatically detecting file markers for Julia, Stata, R, Python, Go, and other supported languages.

How does the system handle repositories with unrecognized language markers?▼

For repositories with unrecognized marker patterns, the profile detection skill implements fallback handling to manage errors and ensure workflow initialization continues without disrupting execution.

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