mohanraj005-dot

context-till

Stingy end-of-turn cost and context controller. Audits every response for token waste and context-budget pressure, and nudges when avoidable spend or avoidable context growth happened. Invoked manually, or wired to end-of-turn via an orchestrator/router hook if you have one — silent when clean, vocal when waste detected. Trigger directly with "till check", "context-till audit", "what's the waste", "am I burning tokens", "till context", "how much budget is left", "why is context growing". The till is stingy and exact — it never adds prose where a tally will do.

entity-naming

Naming pipeline for Indian companies, LLPs, brands and outlets — brief intake, genre-diverse generation, authoritative RDAP domain clearance (.com/.in/.co.in/.net), a parallel MCA/trademark registry-proxy fan-out, a fixed scoring rubric, a ranked shortlist, and a shareable ranked finalist board. Use whenever someone needs to find, shortlist, clear, score or decide a name for a company, LLP, holding entity, brand, outlet, restaurant, cafe, gym or venture — including when they only say "I need a name for X", "help me name my company", "is this name available", "check if X.com is free", "shortlist some names", "our name is taken, find alternatives", "what should we call it", "MCA name availability", "is this trademark free", "brand name ideas", or paste candidate names asking which are clear. Also re-scores prior rounds. Do NOT use for naming code artifacts (variables, files, repos), for UK/Companies House naming, or for brand positioning with no name-selection component — that is emily.

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

remediation-planner

Solution finder that takes the risks risk-critic surfaced and answers each with a quick fix, a structural fix, the trade-off, a verification command, and one clear recommendation. Never identifies new risks — that is risk-critic's lane. Pairs with risk-critic and follows it automatically after a risk-critic findings block, or on explicit request ("how do we solve this", "give me options", "what's the fix", "how do we mitigate", "what would you do here").

sketcher

Turn room dimensions, a napkin brief, or "help me lay out this space" into an accurate, to-scale 2D floor plan (SVG) with real furniture, doors, windows, and clearance/code sanity checks. Use this whenever the user wants to design, sketch, plan, lay out, or visualize a physical space — a restaurant, cafe, kitchen, gym, coworking floor, office, shop, apartment, or any room — even if they don't say "floor plan": phrases like "how should I arrange", "where should the tables go", "draw my space", "plan the layout", "is this big enough", "will it fit", "design the interior", or giving raw dimensions of a room all trigger it. Also use to sanity-check an existing layout against accessibility and egress clearances (ADA/IBC or India NBC 2016). Produces a JSON plan + rendered SVG you can open in a browser. NOT for pixel-photoreal renders (it writes the prompt for an image AI to do that) and NOT for CAD/DWG output.