Score and prioritize AI use cases for your own job. An agent skill from sruthir28/enterprise-ai-skills.
$ npx skills add sruthir28/enterprise-ai-skills --skill ai-use-case-scorer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install sruthir28/enterprise-ai-skills ai-use-case-scorer --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/sruthir28/enterprise-ai-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/ai-use-case-scorer .claude/skills/ai-use-case-scorer && 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 "ai-use-case-scorer" agent skill from https://github.com/sruthir28/enterprise-ai-skills/tree/main/ai-use-case-scorer into .claude/skills/ai-use-case-scorer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-use-case-scorer", 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/sruthir28/enterprise-ai-skills/tree/main/ai-use-case-scorerType 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 sruthir28/enterprise-ai-skills --skill ai-use-case-scorer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install sruthir28/enterprise-ai-skills ai-use-case-scorer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sruthir28/enterprise-ai-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/ai-use-case-scorer .agents/skills/ai-use-case-scorer && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ai-use-case-scorer" agent skill from https://github.com/sruthir28/enterprise-ai-skills/tree/main/ai-use-case-scorer into .agents/skills/ai-use-case-scorer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-use-case-scorer", 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 sruthir28/enterprise-ai-skills --skill ai-use-case-scorer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install sruthir28/enterprise-ai-skills ai-use-case-scorer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sruthir28/enterprise-ai-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/ai-use-case-scorer .cursor/skills/ai-use-case-scorer && 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 "ai-use-case-scorer" agent skill from https://github.com/sruthir28/enterprise-ai-skills/tree/main/ai-use-case-scorer into .cursor/skills/ai-use-case-scorer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-use-case-scorer", 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/sruthir28/enterprise-ai-skills.git --path ai-use-case-scorer--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 sruthir28/enterprise-ai-skills --skill ai-use-case-scorer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install sruthir28/enterprise-ai-skills ai-use-case-scorer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sruthir28/enterprise-ai-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/ai-use-case-scorer .gemini/skills/ai-use-case-scorer && 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 "ai-use-case-scorer" agent skill from https://github.com/sruthir28/enterprise-ai-skills/tree/main/ai-use-case-scorer into .gemini/skills/ai-use-case-scorer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-use-case-scorer", 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 sruthir28/enterprise-ai-skills ai-use-case-scorerInstalls 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 sruthir28/enterprise-ai-skills --skill ai-use-case-scorer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/sruthir28/enterprise-ai-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/ai-use-case-scorer .github/skills/ai-use-case-scorer && 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 "ai-use-case-scorer" agent skill from https://github.com/sruthir28/enterprise-ai-skills/tree/main/ai-use-case-scorer into .github/skills/ai-use-case-scorer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-use-case-scorer", 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 sruthir28/enterprise-ai-skills --skill ai-use-case-scorer -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install sruthir28/enterprise-ai-skills ai-use-case-scorer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sruthir28/enterprise-ai-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/ai-use-case-scorer .opencode/skills/ai-use-case-scorer && 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 "ai-use-case-scorer" agent skill from https://github.com/sruthir28/enterprise-ai-skills/tree/main/ai-use-case-scorer into .opencode/skills/ai-use-case-scorer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-use-case-scorer", 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.
ai-use-case-scorerScore and prioritize AI use cases for your own job. An agent skill from sruthir28/enterprise-ai-skills.
AI Use Case Scorer is an agent skill from sruthir28/enterprise-ai-skills. Score and prioritize AI use cases for your own job. Given a list of candidate use cases (or a description of your workflow), evaluates each on Value × Feasibility × Safety and tiers them — Do Now / Do This Quarter / Park / Avoid. Use when you've heard "we should use AI more" and need to figure out what to actually build first. Built for the individual IC, not org-wide rollout.
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: Open-source AI skills for enterprise professionals. McKinsey consulting frameworks, PM workflows, and practical tools. Currently for Claude, expanding to other LLMs. The licence is MIT.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit ae8fe60. It shows what the files ask for, not the result of running them.
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.
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.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
AI Use Case Scorer loads about 1.5k tokens when it runs. Until then it costs about 100 tokens; SKILL.md has 824 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.
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.
The full file from sruthir28/enterprise-ai-skills at commit ae8fe60, republished under its MIT licence (© sruthir28). 824 words, ~1,524 tokens.
.claude/skills/ai-use-case-scorer/SKILL.md (or your agent's skills folder).Turns "I should be using AI more" into "here are the 3 things I'm building this week, here's why, and here's what I'm explicitly NOT doing." Built for the individual IC trying to figure out where to deploy AI in their own work.
Most AI-use-case lists are theater — pages of "potential" use cases that never get built. This skill compresses the call: of the use cases on your list, which 2–3 actually pay off this month, and which to ignore.
Built for the IC. If you're rolling AI out to a 50-person team, this is the wrong framework — that's change management, not personal scoring.
Each use case scored on three axes (1–5 scale).
| Score | Time saved | Quality lift | Strategic fit |
|---|---|---|---|
| 5 | >5 hrs/wk | Visibly better output | Hits a top-3 personal goal |
| 3 | 1–5 hrs/wk | Modest improvement | Adjacent to a goal |
| 1 | <1 hr/wk | Marginal | Not connected to goals |
Value score = round(avg of three sub-scores)
| Score | Tool maturity | Your skill / time |
|---|---|---|
| 5 | Mature off-the-shelf skill or tool exists | Ship in one sitting |
| 3 | Tools exist but need glue | A weekend project |
| 1 | Requires custom dev / new infra | Multi-week build |
Feasibility score = round(avg of two sub-scores)
| Score | Quality risk | Data risk | Trust risk |
|---|---|---|---|
| 5 | Errors easy to catch | No sensitive data | Team comfortable with AI |
| 3 | Errors land in internal docs | Some PII / internal data | Mixed signals from team |
| 1 | Errors land in customer / exec face | Confidential / regulated | Active resistance |
Safety score = round(avg of three sub-scores)
Range: 1 (don't bother) to 125 (perfect).
| Use case | V | F | S | Score | Tier |
|---|---|---|---|---|---|
| Auto-draft weekly update | 4 | 5 | 5 | 100 | Do Now |
| ... |
For each: 1-line description, 1-line why-now, 1-line first step (must be doable in <1 hour).
Often more useful than the Do Now list — tells you what you're explicitly NOT building, and when to revisit.
Brainstorm if needed. If user gives a workflow instead of a list, walk through their week — every recurring task, every painful task, every "I keep meaning to..." task. Aim for 8–12 candidates.
Score each on V/F/S. Use the rubric. Push back on 5s — they should be rare.
Compute scores + assign tiers.
Write the top 3 tightly. First step must be doable in under 1 hour. If it isn't, the score was wrong.
Flag the parked + avoided. With the trigger condition for revisiting.
Input "I'm a senior PM at a B2B SaaS company. I want to use AI more in my week. Things I do a lot: draft PRDs, write status updates, prep for stakeholder reviews, analyze user-research transcripts, write release notes."
Output
| Use case | V | F | S | Score | Tier |
|---|---|---|---|---|---|
| Auto-draft weekly status update | 4 | 5 | 5 | 100 | Do Now |
| Synthesize user-research transcripts | 5 | 4 | 4 | 80 | Do Now |
| Stakeholder review prep | 4 | 4 | 5 | 80 | Do Now |
| PRD first-draft generator | 4 | 4 | 4 | 64 | Do Now |
| Release notes from PRs | 3 | 5 | 4 | 60 | Do Now |
| Auto-classify inbound customer feedback | 4 | 3 | 4 | 48 | Do This Quarter |
| Replace user interviews with AI personas | 3 | 2 | 1 | 6 | Avoid |
meeting-prep-kit skill; ~1 hr saved per review. First step: run meeting-prep-kit on your next exec review.decision-memo-builder for buy/build/partner)scpr-framework)decision-memo-builder — turn the top Do-Now pick into a memo if you need leadership buy-inprioritization — for non-AI use cases use RICE / Impact-Effort insteadmckinsey-critic — run your top-3 picks through the critic to stress-test your "Do Now" choices© sruthir28, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in ai-use-case-scorer of sruthir28/enterprise-ai-skills.
Open the folder on GitHubat commit ae8fe60
AI Use Case Scorer 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 |
|---|---|---|---|---|---|---|
| AI Use Case Scorer this skillsruthir28/enterprise-ai-skills | 148 | — | ~1.5k | Automated safety check: Pass | MIT | |
| Prioritizing Vulnerabilities With Cvss Scoringmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~1.9k | Automated safety check: Pass | Apache-2.0 | |
| Impediment Prioritizationgithub/awesome-copilot | 40k | 1 repos | ~2.3k | Automated safety check: Pass | MIT | |
| Prioritization Frameworksphuryn/pm-skills | 27k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Prioritize Assumptionsphuryn/pm-skills | 27k | — | ~571 | Automated safety check: Pass | MIT | |
| Claw Scoreopenclaw/openclaw | 392k | — | ~2.5k | Automated safety check: Pass | MIT |
mukul975/Anthropic-Cybersecurity-Skills
The Common Vulnerability Scoring System (CVSS) is the industry standard framework maintained by FIRST (Forum of Incident Response and Security Teams) for assessing vulnerability severity.
github/awesome-copilot
Ranks any list of impediments and their countermeasures using a value-stream scoring model (ROI, Cost to Implement, Ease of Deployment, Risk Factor) and a fixed prioritization formula.
phuryn/pm-skills
Reference guide to 9 prioritization frameworks with formulas, when-to-use guidance, and templates — RICE, ICE, Kano, MoSCoW, Opportunity Score, and more.
phuryn/pm-skills
Prioritize assumptions using an Impact × Risk matrix and suggest experiments for each.
openclaw/openclaw
Audit or refresh OpenClaw maturity scorecard docs from root taxonomy, maturity scores, and QA evidence artifacts without using maintainer discrawl data or committed inventory reports.
github/awesome-copilot
A skill your agent uses when a software engineer asks for help with job search tasks: parsing or analyzing a job description, tailoring a CV/resume, writing a cover letter, evaluating a job offer…
sruthir28/enterprise-ai-skills
McKinsey-style storyline framework for building presentation decks.
sruthir28/enterprise-ai-skills
Builds a 1-page decision memo (context → options → recommendation → risks → ask) enforcing McKinsey memo DNA — brutal brevity, SCP storyline clarity, decision-forcing output, evidence density.
sruthir28/enterprise-ai-skills
Multi-agent pipeline that builds a polished presentation deck from a single topic.
sruthir28/enterprise-ai-skills
McKinsey-style issue tree framework for breaking down complex problems into MECE (Mutually Exclusive, Collectively Exhaustive) components.
sruthir28/enterprise-ai-skills
Generate McKinsey-style consulting charts as native python-pptx objects (editable inside PowerPoint).
sruthir28/enterprise-ai-skills
SCPR (Situation-Complication-Problem-Recommendation) framework for structured problem solving and executive communication.
Score and prioritize AI use cases for your own job. An agent skill from sruthir28/enterprise-ai-skills. AI Use Case Scorer is an agent skill from sruthir28/enterprise-ai-skills. Score and prioritize AI use cases for your own job.
AI Use Case Scorer fits situations like: youve heard we should use AI more and need to figure out what to actually build first.
Run `npx skills add sruthir28/enterprise-ai-skills --skill ai-use-case-scorer -a claude-code`. Or copy the skill folder (ai-use-case-scorer in sruthir28/enterprise-ai-skills) into .claude/skills/ai-use-case-scorer in your project. Claude Code loads it when a task matches its description.
Run `npx skills add sruthir28/enterprise-ai-skills --skill ai-use-case-scorer -a codex`. Or copy the skill folder (ai-use-case-scorer in sruthir28/enterprise-ai-skills) into .agents/skills/ai-use-case-scorer in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sruthir28/enterprise-ai-skills --skill ai-use-case-scorer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-use-case-scorer, .gemini/skills/ai-use-case-scorer, .github/skills/ai-use-case-scorer and .opencode/skills/ai-use-case-scorer in your project.
SKILL.md names no scripts, command-line tools or credentials: AI Use Case Scorer is instructions for the agent only.
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.
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.
AI Use Case Scorer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.5k tokens (SKILL.md is roughly 6.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with AI Use Case Scorer: Prioritizing Vulnerabilities With Cvss Scoring (mukul975/Anthropic-Cybersecurity-Skills, 34k stars), Impediment Prioritization (github/awesome-copilot, 40k stars), Prioritization Frameworks (phuryn/pm-skills, 27k stars) and Prioritize Assumptions (phuryn/pm-skills, 27k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
sruthir28 (a GitHub user) maintains it in sruthir28/enterprise-ai-skills, which has 148 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on September 1, 2026.
Source: sruthir28/enterprise-ai-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.
