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authorCraig Jennings <c@cjennings.net>2026-05-06 21:59:52 -0500
committerCraig Jennings <c@cjennings.net>2026-05-06 21:59:52 -0500
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downloadrulesets-5710b7865549b923467f5e4b1056e040273fc6aa.tar.gz
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chore(commands): mark user-invoked commands disable-model-invocation
Add disable-model-invocation: true to the user-triggered slash commands so the harness drops their descriptions from the model's preloaded skill listing while keeping /<name> routing intact. Skills meant for model recommendation (add-tests, debug, five-whys, frontend-design, humanizer, pairwise-tests, playwright-js, playwright-py, root-cause-trace) are unchanged.
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---
description: Craft prompts (commands, hooks, skill descriptions, sub-agent instructions, system prompts, one-shot requests to other LLMs) that do what they're meant to and resist common failure modes. Covers four moves that determine whether a prompt holds up: classify the prompt type (discipline-enforcing / guidance / collaborative / reference) to pick the right tone and techniques; apply the persuasion framework appropriate to that type (seven principles from Meincke et al. 2025, including which to avoid — notably Liking, which breeds sycophancy); match task fragility to degrees of freedom (high/medium/low); and spend the context window like a shared resource. Also contains a brief reference for classical techniques (few-shot, chain-of-thought, system prompts, templates). Use both in design mode (asking for help writing a new prompt from scratch) and critique mode (paste a draft, get it rewritten to resist common failure modes). Do NOT use for prose editing unrelated to LLM prompts (use a writing skill), for implementing application code that uses an LLM (different scope), or for content moderation / prompt-injection defense (adjacent but separate domain).
+disable-model-invocation: true
---
# Prompt Engineering