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ImCa0/just-laws
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Audit whether the organisation's AI spend actually paid — measured against baselines, not vendor math or vibes.
MITAuto-check passed
Install AI Roi Audit
$ npx skills add mohitagw15856/pm-claude-skills --skill ai-roi-audit -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mohitagw15856/pm-claude-skills ai-roi-audit --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/ai-roi-audit .claude/skills/ai-roi-audit && 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-roi-audit" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/ai-roi-audit into .claude/skills/ai-roi-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-roi-audit", 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/ai-roi-auditType 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 ai-roi-audit -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mohitagw15856/pm-claude-skills ai-roi-audit --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/ai-roi-audit .agents/skills/ai-roi-audit && 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-roi-audit" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/ai-roi-audit into .agents/skills/ai-roi-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-roi-audit", 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 ai-roi-audit -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mohitagw15856/pm-claude-skills ai-roi-audit --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/ai-roi-audit .cursor/skills/ai-roi-audit && 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-roi-audit" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/ai-roi-audit into .cursor/skills/ai-roi-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-roi-audit", 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/ai-roi-audit--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 ai-roi-audit -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mohitagw15856/pm-claude-skills ai-roi-audit --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/ai-roi-audit .gemini/skills/ai-roi-audit && 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-roi-audit" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/ai-roi-audit into .gemini/skills/ai-roi-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-roi-audit", 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 ai-roi-auditInstalls 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 ai-roi-audit -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/ai-roi-audit .github/skills/ai-roi-audit && 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-roi-audit" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/ai-roi-audit into .github/skills/ai-roi-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-roi-audit", 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 ai-roi-audit -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 ai-roi-audit --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/ai-roi-audit .opencode/skills/ai-roi-audit && 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-roi-audit" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/ai-roi-audit into .opencode/skills/ai-roi-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-roi-audit", 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
ai-roi-audit- GitHub stars
- 1.4k
- Token cost
- ~1.4k tokens
- SKILL.md length
- 725 words
- Files
- 1
- Skills in repo
- 1,348
- Repo updated
- First seen
- Licence
- MIT
At a glance
Audit whether the organisation's AI spend actually paid — measured against baselines, not vendor math or vibes.
- Works in 6 steps: Reconstruct the promise. Per tool: what… → Score with the strongest method the… → Count the hidden costs. Verification… → …
- A CFO asks what the AI tools returned
- SKILL.md covers What This Skill Produces, Required Inputs, Audit Method and Output Format, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
AI Roi Audit is an agent skill from mohitagw15856/pm-claude-skills. Audit whether the organisation's AI spend actually paid — measured against baselines, not vendor math or vibes. Use when a CFO asks what the AI tools returned, when renewing AI contracts, when consolidating overlapping AI subscriptions, or to build the measurement plan before the next spend. Produces an ROI audit with per-tool verdicts (keep/consolidate/cut), the honest-measurement method behind each number, and a baseline plan for whatever can't be scored yet. To forecast ROI before an investment use…
Its SKILL.md is about 1.4k 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: 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
- A CFO asks what the AI tools returned
- Renewing AI contracts
- Consolidating overlapping AI subscriptions
- Build the measurement plan before the next spend
Example prompts
- “/ai-roi-audit”
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Reconstruct the promise. Per tool: what outcome justified the purchase — time saved, quality improved, headcount avoided, revenue created?…
- Score with the strongest method the evidence allows, in descending order of credibility
- Count the hidden costs. Verification time (humans checking AI output), rework from AI errors that shipped, licence sprawl (seats bought >…
- Convert honestly. Time saved → money only via a stated loaded rate and a stated assumption about what the time became (more output?…
- Verdict per tool. Keep (positive with tier ≤2 evidence) · Consolidate (positive but duplicative — name the overlap) · Renegotiate…
- Leave the audit better than you found it. Every "unknown" verdict gets a baseline plan: the metric, how it's instrumented, and the review…
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
AI Roi Audit loads about 1.4k tokens when it runs. Until then it costs about 144 tokens; SKILL.md has 725 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). 725 words, ~1,435 tokens.
Download SKILL.mdSave it as
.claude/skills/ai-roi-audit/SKILL.md (or your agent's skills folder).- name
- ai-roi-audit
- description
- Audit whether the organisation's AI spend actually paid — measured against baselines, not vendor math or vibes. Use when a CFO asks what the AI tools returned, when renewing AI contracts, when consolidating overlapping AI subscriptions, or to build the measurement plan before the next spend. Produces an ROI audit with per-tool verdicts (keep/consolidate/cut), the honest-measurement method behind each number, and a baseline plan for whatever can't be scored yet. To forecast ROI before an investment use roi-estimator; this skill measures what already happened.
AI ROI Audit Skill
Every org now spends real money on AI tools, and most justify it with adoption counts ("80% weekly active!") — which measure enthusiasm, not return. This skill audits what the spend returned, using methods that survive a sceptical CFO: baselines, counterfactuals, and quality deltas, with "we can't know yet" said out loud where it's true.
What This Skill Produces
- A per-tool verdict table: keep / consolidate / renegotiate / cut, each with its evidence
- The measurement behind each number — method, baseline, confidence — so the audit is checkable
- A hidden-cost ledger (the part vendor ROI decks omit)
- A baseline plan for every "unknown", so next year's audit has data
Required Inputs
Ask for (if not already provided):
- The AI tool inventory with costs: subscriptions, API spend, seats — and utilisation if known
- What each tool was bought to do (the promised outcome, from the original business case if it exists)
- Available evidence: usage data, before/after metrics, time studies, quality data, anecdotes (labelled as anecdotes)
- The decision at stake: renewal? consolidation? budget defence? (calibrates depth)
Audit Method
- Reconstruct the promise. Per tool: what outcome justified the purchase — time saved, quality improved, headcount avoided, revenue created? A tool without a stated outcome gets audited against the best-fit guess, flagged as retrofitted.
- Score with the strongest method the evidence allows, in descending order of credibility:
- Natural experiment — teams/periods with vs without the tool, same work (best available in most orgs)
- Before/after with baseline — the metric before adoption vs after, seasonality noted
- Task-level time study — 10-20 real tasks timed with/without (cheap to run during the audit — do it rather than skip to tier 4)
- Structured self-report — users estimating time saved, discounted (self-reported AI savings run ~2× actuals; say so) Never present a tier-4 number with tier-1 confidence. Every figure carries its method and a confidence label.
- Count the hidden costs. Verification time (humans checking AI output), rework from AI errors that shipped, licence sprawl (seats bought > seats active), integration/prompt-maintenance time, and training time. These come off the gross benefit — an ROI audit that skips them is a vendor deck.
- Convert honestly. Time saved → money only via a stated loaded rate and a stated assumption about what the time became (more output? earlier finishes? — different values). "Saved 400 hours" that nobody redeployed is capacity, not cash; label which one you're claiming.
- Verdict per tool. Keep (positive with tier ≤2 evidence) · Consolidate (positive but duplicative — name the overlap) · Renegotiate (positive but mispriced vs utilisation) · Cut (negative or unmeasurable after a fair baseline attempt). Ties break toward the tool with a measurement plan.
- Leave the audit better than you found it. Every "unknown" verdict gets a baseline plan: the metric, how it's instrumented, and the review date. The first audit is mostly this; that's a finding, not a failure.
Show full SKILL.md (259 more words)Show less
Output Format
AI ROI Audit: [org/team] — [period]
Total AI spend: [sum] · Verdict summary: [n keep / n consolidate / n renegotiate / n cut / n unknown]
| Tool | Annual cost | Promised outcome | Measured return | Method (tier) | Confidence | Verdict |
|---|
Hidden-cost ledger: [verification, rework, sprawl, maintenance — quantified where possible, listed where not]
The math shown: [for each material number: baseline, method, conversion assumptions]
Baseline plan for the unknowns: [tool → metric → instrumentation → review date]
One-paragraph CFO summary: [net position, the two decisions to make, and what will be measurable by next audit]
Quality Checks
- Every figure carries its measurement method and confidence — no naked numbers
- Self-reported savings are discounted and labelled as self-reported
- Hidden costs appear as line items, not a caveat sentence
- Time→money conversions state the loaded rate and the capacity-vs-cash claim
- Every "unknown" has a baseline plan with a date — the audit compounds
Anti-Patterns
- Do not use adoption or engagement as return — usage is a cost signal until an outcome moves
- Do not accept vendor ROI calculators as evidence — reconstruct from your own data or score it unknown
- Do not average across tools into one triumphant number — the verdict is per-tool or it decides nothing
- Do not claim headcount avoidance without the counterfactual hiring plan that was actually cancelled
- Do not punish honest "unknowns" by cutting them reflexively — cut requires a failed measurement attempt, not a missing one
Example Trigger Phrases
- "What did our AI tools actually return?"
- "Should we renew these AI contracts?"
- "We pay for three overlapping AI subscriptions: which do we keep?"
- "Build the measurement plan before the next AI spend."
© 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/ai-roi-audit of mohitagw15856/pm-claude-skills.
Open the folder on GitHubat commit 1cbf1f0
Compare with similar skills
AI Roi Audit 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 Roi Audit this skillmohitagw15856/pm-claude-skills | 1.4k | — | ~1.4k | Automated safety check: Pass | MIT | |
| MarkitdownImCa0/just-laws | 781 | 14 repos | ~3.2k | Automated safety check: Notes | MIT | |
| Technical Analysttradermonty/claude-trading-skills | 3k | 4 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Creating Financial ModelsChen-zexi/open-ptc-agent | 729 | 3 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Managing Google Workspacetaylorwilsdon/google_workspace_mcp | 3.3k | — | ~2.9k | Automated safety check: Pass | MIT | |
| Job Application Managerreactive-resume/reactive-resume | 44k | — | ~13k | Automated safety check: Pass | MIT |
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Questions about AI Roi Audit
What does AI Roi Audit do?
Audit whether the organisation's AI spend actually paid — measured against baselines, not vendor math or vibes. AI Roi Audit is an agent skill from mohitagw15856/pm-claude-skills. Audit whether the organisation's AI spend actually paid — measured against baselines, not vendor math or vibes.
When should I use AI Roi Audit?
AI Roi Audit fits situations like: A CFO asks what the AI tools returned; renewing AI contracts; consolidating overlapping AI subscriptions; build the measurement plan before the next spend.
How do I install AI Roi Audit in Claude Code?
Run `npx skills add mohitagw15856/pm-claude-skills --skill ai-roi-audit -a claude-code`. Or copy the skill folder (skills/ai-roi-audit in mohitagw15856/pm-claude-skills) into .claude/skills/ai-roi-audit in your project. Claude Code loads it when a task matches its description.
How do I install AI Roi Audit in Codex?
Run `npx skills add mohitagw15856/pm-claude-skills --skill ai-roi-audit -a codex`. Or copy the skill folder (skills/ai-roi-audit in mohitagw15856/pm-claude-skills) into .agents/skills/ai-roi-audit in your project. Codex loads it when a task matches its description.
Can I use AI Roi Audit 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 ai-roi-audit -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-roi-audit, .gemini/skills/ai-roi-audit, .github/skills/ai-roi-audit and .opencode/skills/ai-roi-audit in your project.
What does AI Roi Audit need to run?
SKILL.md names no scripts, command-line tools or credentials: AI Roi Audit is instructions for the agent only.
Does AI Roi Audit 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 AI Roi Audit 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 AI Roi Audit use?
AI Roi Audit 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 AI Roi Audit use?
About 1.4k tokens (SKILL.md is roughly 5.7k 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 AI Roi Audit?
Skills that share tags, products or a category with AI Roi Audit: Markitdown (ImCa0/just-laws, 781 stars), Technical Analyst (tradermonty/claude-trading-skills, 3k stars), Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars) and Managing Google Workspace (taylorwilsdon/google_workspace_mcp, 3.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains AI Roi Audit?
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.