grimdevmodel-quirks
Solid(grim:dev:model-quirks): (Model Quirks): Apply model-specific prompt mitigations inline (unlabeled) into AGENTS.md, skills, and prompts, and record every applied change in the reverse-index ledger at docs/model-quirks-ledger.yaml so it can be verified, pruned, or undone when models rotate.
Install
Quality Score: 83/100
Skill Content
Details
- Author
- MindGoblinStudios
- Repository
- MindGoblinStudios/grim-tome
- Created
- 2 weeks ago
- Last Updated
- yesterday
- Language
- JavaScript
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
promptcarta
Model-aware expert prompt generator and critic. Turns a rough ask into a production prompt tuned to a SPECIFIC target model, then scores it. 9-step pipeline: resolve target model, score input, extract 11 intent dimensions, gate on success criteria, max 3 clarifying questions, pick an architecture, decompose into parallel sub-agents and assign the best-fit skill to each, apply the model-specific transform, scan for dead constructs, re-score. Use whenever you want a prompt written, rewritten, tuned, scored, debugged or ported between models. Trigger on "write a prompt for", "improve this prompt", "prompt for GPT-5 / Gemini / Kimi / GLM", "system prompt for", "why is this prompt failing", "port this prompt to", "score this prompt", "promptcarta", "/promptcarta", "tune this for <model>". HARD RULE: every model fact comes from references/models/*.md and its last_verified date. Never state model behaviour from memory. NOT for authoring skills (skill-creator), routing a request to the right skill (a routing/orchestr
system-prompts
Write system prompts, tool docs, and agent definitions. Project tag conventions + RFC 2119 keywords + dense compression. Use when authoring or editing any prompt the model reads.
prompt-versioning-hygiene
This skill should be used when the user mentions "prompt engineering", "prompt versioning", "prompt management", "system prompt", "prompt template", "manage prompts", or "prompts scattered in code". It provides a methodology for treating prompts as versioned, reviewable, testable code rather than magic strings buried in application logic.