functional-discovery

Discover overlapping community agents and skills from public registries and local installations.

12|2|Updated Jan 27, 2026

Search Tags:#community #verification #discovery #deduplication #installation #registry-search

Ready to run

npx skills add https://github.com/jikig-ai/soleur --skill functional-discovery

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: functional-discovery
Source: https://github.com/jikig-ai/soleur/tree/main/.openhands/skills/functional-discovery
Command: npx skills add https://github.com/jikig-ai/soleur --skill functional-discovery

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill prevents wasted effort by finding community agents and skills that functionally overlap with a planned feature so teams do not rebuild existing solutions.

Core Features & Use Cases

Parallel registry queries: Searches multiple public registries with timeout and error handling to gather candidate artifacts.
Trust filtering and deduplication: Applies a tiered trust model and deduplicates results across sources, preferring higher-trust artifacts.
Safe installation workflow: Checks for already-installed artifacts, validates frontmatter and size, adds provenance metadata, and requires explicit user approval before writing local files.

Quick Start

Run the functional discovery agent during planning with a concise feature description like "build an email-scheduling skill" to locate verified community tools that match.

Frequently Asked Questions about functional-discovery

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

FAQPage Schema

How do I find existing community skills before building a new feature?▼

To find existing community skills, use the functional discovery agent during planning to query public registries and local installations for overlapping functionality, filtering duplicates to prevent redundant development.

How does duplicate agent detection work across public registries?▼

Duplicate agent detection works by querying multiple public registries in parallel with timeout handling, then deduplicating the results across sources while applying a tiered trust model that prefers higher-trust artifacts.

Can I safely install verified community tools without breaking my local environment?▼

Yes, safe installation is supported by checking for already-installed artifacts, validating frontmatter and file size, adding provenance metadata, and requiring explicit user approval before writing any local files.

What is the best way to avoid rebuilding existing solutions during planning workflows?▼

The best way to avoid rebuilding existing solutions is running functional discovery with a concise feature description to locate verified community tools that match your planned functionality before starting development.

Does trust-tier filtering actually prevent the use of unreliable community agents?▼

Trust-tier filtering prevents unreliable community agents by applying a tiered trust model during deduplication, preferring higher-trust artifacts across queried registries to ensure only verified tools are suggested.

What happens when registry queries time out during community tool discovery?▼

When registry queries time out during community tool discovery, the Skill handles errors gracefully to ensure the workflow continues, gathering available candidate artifacts and deduplicating successful responses.