Lite Constraints

Lite Constraints is an AI Engineering skill for Claude Code, published by acogood in diffmode_free.

161 stars0 forkson acogood/diffmode_freeAdded 2026/09/08+1% in starsRepository updated 2026/08/10

agentsaibootstrappedclaude-codeclaude-plugincodexdevtoolsfoundersgrowthgrowth-hackingmarketingmarketing-strategyopen-sourcesaasskillsstartupstartup-tools

Install in seconds

Install Lite Constraints

Copy Lite Constraints into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/acogood/diffmode_free/tree/main/plugin/skills/lite-constraints ~/.claude/skills/lite-constraints

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/acogood/diffmode_free.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: plugin/skills/lite-constraints/SKILL.md in acogood/diffmode_free
Installs to: ~/.claude/skills/lite-constraints
Collection: One of 13 skills cataloged from this repository
Category: AI Engineering — 3670 skills

What Lite Constraints does

Lite Constraints generates synthesis-constraints.json from per-run growth-factors.json and founder context. It is used after growth-factors mining and before synthesis to define white-space pairs, mandatory combinations, prohibited patterns, and category diversity rules.

Lite Constraints is cataloged under AI Engineering on DirSkills. Lite Constraints comes from a repository tagged agents, ai, bootstrapped, claude-code and claude-plugin.

Documentation

README

Excerpt

Lite Constraints (synthesis constraints, no Python)

You produce synthesis-constraints.json — the file the synthesis chain reads to force unconventional vector combinations and block conventional ones. In the paid pipeline this is generated by the proprietary Python constraints generator reading the proprietary intelligence layer (curated anchors + internal pair-scoring). Here you reason in-context over the per-run growth-factors.json + founder constraints to emit the same JSON shape. You drop the proprietary intelligence-layer scoring entirely — it was scaffolding for how the script picked pairs, not a field the synthesis prompts consume.

⚠️ Clean-room rule

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Lite Constraints

What else does acogood publish alongside Lite Constraints?
Lite Constraints is one of 13 skills that DirSkills catalogs from acogood/diffmode_free, the repository it ships in. Its siblings there include Acquisition Tactics Research, Audience JTBD Analysis and Competitor Gaps. Each one is a separate skill with its own page in this directory, installs the same way Lite Constraints does, and is maintained by acogood in that same repository. The rest of the collection is listed on the acogood/diffmode_free page.
How does Lite Constraints compare to other AI Engineering skills?
Lite Constraints ranks #3437 by stars among the 3670 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Lite Constraints against them. Open each page to compare what they document and how they install.