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OpenSkills

Stop bloating your LLM context with unused instructions

Details

External ID
46716016
Source
HN
Company
—
Product
—
Website domain
—
Launched
Jan. 22, 2026
Cohort
—
Upvotes
9
Upvotes percentile
0.461133069828722
Tags
—
Fetched at
Sept. 7, 2026, 9:25 p.m.
Updated at
Sept. 7, 2026, 9:25 p.m.

Description

Hello HN,I’ve been building AI agents lately and ran into a common "Context Bloat" problem. When an agent has 20+ skills, stuffing every system prompt, reference doc, and tool definition into a single request quickly hits token limits and degrades model performance (the "lost in the middle" problem).To solve this, I built OpenSkills, an open-source SDK that implements a Progressive Disclosure Architecture for agent skills.The Core Concept: Instead of loading everything upfront, OpenSkills splits a skill into three layers:Layer 1 (Metadata): Light-weight tags and triggers (always loaded for discovery).Layer 2 (Instruction): The core SKILL.md prompt (loaded only when the skill is matched).Layer 3 (Resources): Heavy reference docs or scripts that are conditionally loaded based on the specific conversation context.Why this matters:Scalability: You can have hundreds of skills without overwhelming the LLM's context window.Markdown-First: Skills are defined in a simple SKILL.md format. It’s human-readable, git-friendly, and easy for the LLM to parse.Conditional Resources: For example, a "Finance Skill" only pulls in the tax-code.pdf reference if the query actually mentions tax compliance.Key Features:Python 3.10+ SDK.Automatic skill matching and invocation.Support for script execution (via [INVOKE:script_name] syntax).Multimodal support (Images via URL/base64).GitHub: [https://github.com/twwch/OpenSkills] PyPI: pip install openskills-sdk

Enrichment

Theme
AI agent frameworks and developer tools
Vertical
Horizontal
Function
Dev tools
Audience
Developer
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
optimize llm context with skill management
Manually corrected
False

Could you build this?

Yes It is a dynamic prompt management and tool-retrieval library that selects relevant agent instructions and tools on the fly based on vector similarity or rule-based matching.

Discussion

3 comments analyzed.

Concerns raised: State management across multi-step tasks with context recall, Lost in the middle problem - model forgetting earlier steps

Feature requests: Better handling of cross-step context dependencies in long workflows

Competitors

Other products that read as similar to this one — 132 launches clear the similarity bar, closest 8 shown.

Attention rank: #75 of 133 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 84 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a dev tools tool for Sales yet.