Aisafetyhot
wuyoscar/AISafetyHot-Hub
Query AI Safety HOT news, research papers, incidents, hot topics, and daily/weekly/monthly reports through its public read-only MCP service.
Figure out the best card or payment route for a purchase (or your everyday spending) to maximize cashback/points — without overspending or drowning in complexity.
Install Rewards Optimizer
$ npx skills add mohitagw15856/pm-claude-skills --skill rewards-optimizer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mohitagw15856/pm-claude-skills rewards-optimizer --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/rewards-optimizer .claude/skills/rewards-optimizer && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "rewards-optimizer" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/rewards-optimizer into .claude/skills/rewards-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rewards-optimizer", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/rewards-optimizerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mohitagw15856/pm-claude-skills --skill rewards-optimizer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mohitagw15856/pm-claude-skills rewards-optimizer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/rewards-optimizer .agents/skills/rewards-optimizer && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "rewards-optimizer" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/rewards-optimizer into .agents/skills/rewards-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rewards-optimizer", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mohitagw15856/pm-claude-skills --skill rewards-optimizer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mohitagw15856/pm-claude-skills rewards-optimizer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/rewards-optimizer .cursor/skills/rewards-optimizer && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "rewards-optimizer" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/rewards-optimizer into .cursor/skills/rewards-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rewards-optimizer", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mohitagw15856/pm-claude-skills.git --path skills/rewards-optimizer--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mohitagw15856/pm-claude-skills --skill rewards-optimizer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mohitagw15856/pm-claude-skills rewards-optimizer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/rewards-optimizer .gemini/skills/rewards-optimizer && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "rewards-optimizer" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/rewards-optimizer into .gemini/skills/rewards-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rewards-optimizer", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mohitagw15856/pm-claude-skills rewards-optimizerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mohitagw15856/pm-claude-skills --skill rewards-optimizer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/rewards-optimizer .github/skills/rewards-optimizer && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "rewards-optimizer" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/rewards-optimizer into .github/skills/rewards-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rewards-optimizer", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mohitagw15856/pm-claude-skills --skill rewards-optimizer -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mohitagw15856/pm-claude-skills rewards-optimizer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/rewards-optimizer .opencode/skills/rewards-optimizer && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "rewards-optimizer" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/rewards-optimizer into .opencode/skills/rewards-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rewards-optimizer", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
rewards-optimizer- GitHub stars
- 1.4k
- Token cost
- ~1.1k tokens
- SKILL.md length
- 539 words
- Files
- 1
- Skills in repo
- 1,348
- Repo updated
- First seen
- Licence
- MIT
At a glance
Figure out the best card or payment route for a purchase (or your everyday spending) to maximize cashback/points — without overspending or drowning in complexity.
- Works in 5 steps: Match the card to the category. Use… → Keep the everyday map simple. A… → Redeem smartly. Points aren't all worth… → …
- Asked which card should I use for [purchase]
- SKILL.md covers What This Skill Produces, Required Inputs, Framework: Value First, Never… and Output Format, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Rewards Optimizer is an agent skill from mohitagw15856/pm-claude-skills. Figure out the best card or payment route for a purchase (or your everyday spending) to maximize cashback/points — without overspending or drowning in complexity. Use when asked which card should I use for [purchase], maximize my credit card rewards, best card for [category], or optimize my points. Produces the best-value route for the spend from the cards/programs you actually have, a simple everyday cheat-sheet by category, redemption tips, and honest guardrails (pay in full, don't chase points into debt or…
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering, covering LLM guardrails. The repository describes itself as: 1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in… The licence is MIT.
When your agent uses it
- Asked which card should I use for [purchase]
- Maximize my credit card rewards
- Best card for [category]
- Optimize my points
Example prompts
- “/rewards-optimizer”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Match the card to the category. Use whichever card earns the highest rate for that specific spend — bonus categories are where the value is.
- Keep the everyday map simple. A two-or-three-card routine most people can actually remember beats a 10-card optimization nobody follows.
- Redeem smartly. Points aren't all worth the same — flag high-value redemptions and watch for devaluation; sometimes plain cashback wins.
- Judge fees honestly. An annual fee only pays off if your spending in its categories clears the fee in rewards — do that math.
- Guardrail hard. Rewards are worthless if you carry a balance or overspend to earn them — pay in full, don't chase. Say this plainly.
What it can do on your machine
Read from SKILL.md and the folder at commit 1cbf1f0. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Rewards Optimizer loads about 1.1k tokens when it runs. Until then it costs about 141 tokens; SKILL.md has 539 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from mohitagw15856/pm-claude-skills at commit 1cbf1f0, republished under its MIT licence (© mohitagw15856). 539 words, ~1,078 tokens.
Download SKILL.mdSave it as
.claude/skills/rewards-optimizer/SKILL.md (or your agent's skills folder).- name
- rewards-optimizer
- description
- Figure out the best card or payment route for a purchase (or your everyday spending) to maximize cashback/points — without overspending or drowning in complexity. Use when asked which card should I use for [purchase], maximize my credit card rewards, best card for [category], or optimize my points. Produces the best-value route for the spend from the cards/programs you actually have, a simple everyday cheat-sheet by category, redemption tips, and honest guardrails (pay in full, don't chase points into debt or clutter). Not financial advice.
Rewards Optimizer
Reward programs are designed to be confusing so most value goes unclaimed. This cuts through it: given the cards and programs you actually have, it tells you the best one to use for a specific purchase or builds a simple by-category cheat-sheet for everyday spending — while keeping the golden rule front and center: rewards are only worth it if you pay in full and don't spend more to earn them.
What This Skill Produces
- The best route for this spend — which of your cards/programs earns most for the specific purchase or category
- An everyday cheat-sheet — a simple "use card X for groceries, Y for dining, Z for everything else" map
- Redemption tips — how to get the most value when cashing in (transfer partners, statement credit vs travel, avoiding devaluation)
- Guardrails — pay-in-full always, don't chase sign-ups into debt, keep it simple enough to actually follow
- A "worth it?" check — when an annual fee or a new card does or doesn't pay off for your spending
Required Inputs
Ask for these if not provided:
- Your cards/programs — what you have (issuers, categories, any annual fees)
- The question — a specific purchase/category, or optimizing everyday spending
- Your spending shape — rough monthly by category (groceries, dining, travel, gas, bills)
- Redemption goal — cashback, travel, or points flexibility
- Complexity tolerance — max value vs. keep-it-simple
Framework: Value First, Never Into Debt
- Match the card to the category. Use whichever card earns the highest rate for that specific spend — bonus categories are where the value is.
- Keep the everyday map simple. A two-or-three-card routine most people can actually remember beats a 10-card optimization nobody follows.
- Redeem smartly. Points aren't all worth the same — flag high-value redemptions and watch for devaluation; sometimes plain cashback wins.
- Judge fees honestly. An annual fee only pays off if your spending in its categories clears the fee in rewards — do that math.
- Guardrail hard. Rewards are worthless if you carry a balance or overspend to earn them — pay in full, don't chase. Say this plainly.
Show full SKILL.md (202 more words)Show less
Output Format
Rewards: [specific spend / everyday] · cards: [yours]
For this purchase: use [card] — earns [rate/value] because [category bonus].
Everyday cheat-sheet
| Category | Best card | Why |
|---|---|---|
| Groceries | [card] | [rate] |
| Dining | [card] | [rate] |
| Everything else | [card] | [base rate] |
Redeem for max value: [best redemption path + watch-outs]. Fee check: [card] fee pays off if you spend ~[x] in [category].
Not financial advice. Only worth it if you pay the balance in full every month and don't spend more to earn rewards.
Quality Checks
- Recommends the highest-earning card for the actual category
- Everyday cheat-sheet is simple enough to follow
- Includes redemption-value guidance, not just earning
- Does honest annual-fee math
- Leads with pay-in-full / don't-overspend guardrails
- Uses only the cards/programs the person has
Anti-Patterns
- Optimizing into complexity nobody will follow.
- Ignoring the pay-in-full rule — interest erases all rewards.
- Encouraging spend to hit bonuses.
- Treating all points as equal value.
- Recommending a fee card without the break-even math.
Example Trigger Phrases
- "Which card should I use for booking a flight?"
- "Help me maximize my cashback across my cards."
- "Best card for groceries and dining from what I have?"
- "Is this card's annual fee worth it for my spending?"
- "Set me up a simple system for which card to use where."
© mohitagw15856, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/rewards-optimizer of mohitagw15856/pm-claude-skills.
Open the folder on GitHubat commit 1cbf1f0
Compare with similar skills
Rewards Optimizer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Rewards Optimizer this skillmohitagw15856/pm-claude-skills | 1.4k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Aisafetyhotwuyoscar/AISafetyHot-Hub | 708 | — | ~1.4k | Automated safety check: Pass | Custom licence | |
| ObliteratusRedWoodOG/Hermes-Desktop | 177 | 5 repos | ~3.8k | Automated safety check: Pass | MIT | |
| Lemonade Router Builderamd/skills | 408 | — | ~4k | Automated safety check: Pass | MIT | |
| Execution Guardrailsmrtooher/fable-mode | 873 | — | ~1k | Automated safety check: Pass | None | |
| Writing Eval Scenariosopen-bias/open-bias | 143 | — | ~1.5k | Automated safety check: Pass | Apache-2.0 |
Similar skills
Obliteratus
RedWoodOG/Hermes-Desktop
Remove refusal behaviors from open-weight LLMs using OBLITERATUS — mechanistic interpretability techniques (diff-in-means, SVD, whitened SVD, LEACE, SAE decomposition, etc.) to excise guardrails…
Lemonade Router Builder
amd/skills
Turns a natural-language description of routing intent into a valid Lemonade collection.router policy JSON.
Execution Guardrails
mrtooher/fable-mode
Always-on operational guardrails, model-independent. An agent skill from mrtooher/fable-mode.
Writing Eval Scenarios
open-bias/open-bias
Guide for writing eval conversation JSONs and running them through policy engines
Wp Project Triage
gambitph/Stackable
A skill your agent uses when you need a deterministic inspection of a WordPress repository (plugin/theme/block theme/WP core/Gutenberg/full site) including tooling/tests/version hints, and a…
More from mohitagw15856/pm-claude-skills
All 1,348 skills in this repoCar Tco
mohitagw15856/pm-claude-skills
Compare the total cost of car ownership across buy-new, buy-used, lease, and keep-your-current-car — depreciation, insurance, maintenance ramp, and fuel over a real horizon, not just the monthly…
Cs Health Scorecard
mohitagw15856/pm-claude-skills
Build a customer health scorecard for a specific account. An agent skill from mohitagw15856/pm-claude-skills.
Exit Waterfall
mohitagw15856/pm-claude-skills
Compute who gets what at each exit price from a cap table — liquidation preferences, conversion points, and where the founders' share collapses.
Feature Prioritisation
mohitagw15856/pm-claude-skills
Apply prioritisation frameworks (RICE, MoSCoW, Kano, ICE, Opportunity Scoring) to rank features and backlog items.
Fire Number
mohitagw15856/pm-claude-skills
Compute a financial-independence (FIRE) target and years-to-reach with every assumption labeled as an assumption — plus a sensitivity table instead of a single false-precision answer.
Freelance Rate
mohitagw15856/pm-claude-skills
Derive a freelance day/hourly rate backwards from target income, honest billable utilization, overhead, and the self-employment tax premium — the arithmetic that proves a rate is not salary÷2000.
Related
Categories
Questions about Rewards Optimizer
What does Rewards Optimizer do?
Figure out the best card or payment route for a purchase (or your everyday spending) to maximize cashback/points — without overspending or drowning in complexity. Rewards Optimizer is an agent skill from mohitagw15856/pm-claude-skills. Figure out the best card or payment route for a purchase (or your everyday spending) to maximize cashback/points — without overspending or drowning in complexity.
When should I use Rewards Optimizer?
Rewards Optimizer fits situations like: asked which card should I use for [purchase]; maximize my credit card rewards; best card for [category]; optimize my points.
How do I install Rewards Optimizer in Claude Code?
Run `npx skills add mohitagw15856/pm-claude-skills --skill rewards-optimizer -a claude-code`. Or copy the skill folder (skills/rewards-optimizer in mohitagw15856/pm-claude-skills) into .claude/skills/rewards-optimizer in your project. Claude Code loads it when a task matches its description.
How do I install Rewards Optimizer in Codex?
Run `npx skills add mohitagw15856/pm-claude-skills --skill rewards-optimizer -a codex`. Or copy the skill folder (skills/rewards-optimizer in mohitagw15856/pm-claude-skills) into .agents/skills/rewards-optimizer in your project. Codex loads it when a task matches its description.
Can I use Rewards Optimizer in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mohitagw15856/pm-claude-skills --skill rewards-optimizer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/rewards-optimizer, .gemini/skills/rewards-optimizer, .github/skills/rewards-optimizer and .opencode/skills/rewards-optimizer in your project.
What does Rewards Optimizer need to run?
SKILL.md names no scripts, command-line tools or credentials: Rewards Optimizer is instructions for the agent only.
Does Rewards Optimizer access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Rewards Optimizer safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Rewards Optimizer use?
Rewards Optimizer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Rewards Optimizer use?
About 1.1k tokens (SKILL.md is roughly 4.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Rewards Optimizer?
Skills that share tags, products or a category with Rewards Optimizer: Aisafetyhot (wuyoscar/AISafetyHot-Hub, 708 stars), Obliteratus (RedWoodOG/Hermes-Desktop, 177 stars), Lemonade Router Builder (amd/skills, 408 stars) and Execution Guardrails (mrtooher/fable-mode, 873 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Rewards Optimizer?
mohitagw15856 (a GitHub user) maintains it in mohitagw15856/pm-claude-skills, which has 1,434 GitHub stars. The repository holds 1,348 skills in this directory. The repository was last updated on October 9, 2026.
Source: mohitagw15856/pm-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.