tddish
Skill0 starsChanged 3 months agoNo licenceView on GitHub
Develop under TDD discipline without any orchestration: find the suite, prove it green, plan the change as small behavioural steps, then run Red → Green → Refactor per step — the red predicted before it is run and watched to fail for the right reason, the green the minimum the test demands, the refactor bounded to the files that cycle touched. Use when the user says "tdd", "tddish", "use TDD", "test-driven", "test first", "write the test first", "red green refactor", "do this test-first", "start with a failing test", or asks for a change to be developed test-first. One agent, one worktree, no subagents, no state machine — for the projects where veri's `/tdd` is not installed or not worth its weight. When the request names a GitHub issue, it claims the issue with veri's label and ticks a veri-format plan ledger as steps land.
In this repository18 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- user-prompt/CLAUDE.mdCLAUDE.md
- afkSkill
- aws-sso-sessionsSkill
- delegateSkill
- dev-toolsSkill
- duckSkill
- handoffSkill
- housekeepingSkill
- house-styleSkill
- low-fuelSkill
- machine-health-scheduleSkill
- machine-healthSkill
- mergeSkill
- setup-git-guardrailSkill
- sync-configSkill
- tldrSkill
- wrap-upSkill
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

