Prevent common coding mistakes with battle-tested agent skills
A skill pack for agents built only from real project mistakes, not theoretical best practices.
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Why it matters
Equip AI coding agents with defensive reasoning skills learned from real project failures to avoid typical mistakes like premature coding, scope blindness, and inadequate verification before making changes.
Outcomes
What it gets done
Force agents to understand task scope and gather facts before writing code
Maintain decision journals in changelogs explaining what changed and why
Verify system feedback clarity so users understand outcomes and errors
Challenge hidden assumptions in product and UX design decisions
Install
Add it to your toolbox
Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/hronicasync-nodumbmode | bash After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.
Reports
Agent outcome reports
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Overview
Nodumbmode
nodumbmode is a small set of agent skills - task-scoping discipline, changelog-as-decision-log, user feedback clarity, and UX assumption-checking - where each skill exists only because a real project failure prompted it. Use it before non-trivial code changes, when a project needs a decision-log changelog, when reviewing user-facing feedback, or during product/UX design discussions.
What it does
nodumbmode is a collection of skills for AI agents, each one created only after a specific, concrete failure in a real project - no skill here is added for a theoretical best practice. The pack contains four skills: nodumb, a common-sense manifest and rule set against typical agent mistakes (understand the task, check its scope, and gather facts before writing code), meant for use before non-trivial code changes, mass edits, or a second debugging attempt, producing a short output of what is known, where the risk is, what to do next, and how to verify the result; changelog-discipline, which keeps a changelog as a decision log recording what changed, why, what it was before, and what alternatives were rejected; system-feedback, which checks whether it is clear to the user what happened after an action and what to do if something fails; and ask-nodumb, a design consultant for product and UX tasks that helps surface a hidden assumption and separate the product vision, the model, and the technology.
When to use - and when NOT to
Use nodumb before starting non-trivial code work, a broad edit across a codebase, or a second attempt at debugging something that failed once already. Use changelog-discipline whenever a project needs a running record of decisions rather than just a list of changes. Use system-feedback when building or reviewing user-facing flows where error states and post-action clarity matter. Use ask-nodumb during product or UX design discussions where an unstated assumption might be driving the design.
Inputs and outputs
npx skills@latest add hronicasync/nodumbmode
This requires Node.js; the CLI asks whether to install globally or into the current project, detects installed agents, and lets you choose which ones to install into - Claude Code, Codex, Cursor, Windsurf, Continue, and dozens more are supported the same way. For a non-interactive install (CI or a script), name everything explicitly:
npx skills@latest add hronicasync/nodumbmode -g -y -a claude-code -a codex --skill '*'
Skills are written once to ~/.agents/skills/, with symlinks placed into each agent's own directory, so an update reaches every linked agent at once without duplicating files. Updating specific skills:
npx skills@latest update nodumb ask-nodumb changelog-discipline system-feedback
Running skills update with no names updates every installed skill, including ones from other sources, which is why this pack's update command names its skills explicitly.
Integrations
Works with any agent harness supported by the skills CLI, including Claude Code, Codex, Cursor, Windsurf, and Continue. SKILL.md in each skill's folder holds the core rules; the references/ folder holds examples and further detail.
Who it's for
Developers who want an agent's working habits (task scoping, changelog discipline, clear user feedback, questioning hidden assumptions) shaped by a record of real failures rather than generic advice.
FAQ
Common questions
Discussion
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