Replit Deck
sanqiufong/slides-from-anything
Single-file horizontal-swipe HTML deck in the style of Replit Slides's landing-page template gallery.
Find out how a dashboard, KPI report, or metrics slide is lying to you — before you repeat its story in a bigger room.
Install Metric Gaslighting Detector
$ npx skills add mohitagw15856/pm-claude-skills --skill metric-gaslighting-detector -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mohitagw15856/pm-claude-skills metric-gaslighting-detector --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/metric-gaslighting-detector .claude/skills/metric-gaslighting-detector && 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 "metric-gaslighting-detector" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/metric-gaslighting-detector into .claude/skills/metric-gaslighting-detector/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metric-gaslighting-detector", 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/metric-gaslighting-detectorType 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 metric-gaslighting-detector -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mohitagw15856/pm-claude-skills metric-gaslighting-detector --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/metric-gaslighting-detector .agents/skills/metric-gaslighting-detector && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "metric-gaslighting-detector" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/metric-gaslighting-detector into .agents/skills/metric-gaslighting-detector/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metric-gaslighting-detector", 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 metric-gaslighting-detector -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mohitagw15856/pm-claude-skills metric-gaslighting-detector --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/metric-gaslighting-detector .cursor/skills/metric-gaslighting-detector && 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 "metric-gaslighting-detector" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/metric-gaslighting-detector into .cursor/skills/metric-gaslighting-detector/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metric-gaslighting-detector", 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/metric-gaslighting-detector--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 metric-gaslighting-detector -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mohitagw15856/pm-claude-skills metric-gaslighting-detector --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/metric-gaslighting-detector .gemini/skills/metric-gaslighting-detector && 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 "metric-gaslighting-detector" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/metric-gaslighting-detector into .gemini/skills/metric-gaslighting-detector/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metric-gaslighting-detector", 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 metric-gaslighting-detectorInstalls 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 metric-gaslighting-detector -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/metric-gaslighting-detector .github/skills/metric-gaslighting-detector && 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 "metric-gaslighting-detector" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/metric-gaslighting-detector into .github/skills/metric-gaslighting-detector/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metric-gaslighting-detector", 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 metric-gaslighting-detector -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 metric-gaslighting-detector --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/metric-gaslighting-detector .opencode/skills/metric-gaslighting-detector && 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 "metric-gaslighting-detector" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/metric-gaslighting-detector into .opencode/skills/metric-gaslighting-detector/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "metric-gaslighting-detector", 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
metric-gaslighting-detector- GitHub stars
- 1.4k
- Token cost
- ~1.1k tokens
- SKILL.md length
- 560 words
- Files
- 1
- Skills in repo
- 1,348
- Repo updated
- First seen
- Licence
- MIT
At a glance
Find out how a dashboard, KPI report, or metrics slide is lying to you — before you repeat its story in a bigger room.
- Works in 11 steps: Denominator games — the base changed… → Survivorship framing — measuring only… → Y-axis crimes — truncated baselines,… → …
- Numbers feel too tidy
- SKILL.md covers Required Inputs, The Eleven Distortions, Output Format and Quality Checks, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Metric Gaslighting Detector is an agent skill from mohitagw15856/pm-claude-skills. Find out how a dashboard, KPI report, or metrics slide is lying to you — before you repeat its story in a bigger room. Use when numbers feel too tidy, a narrative rests on one chart, or you inherited metrics you didn't define. Produces a deception audit: every metric graded for the eleven classic distortions (denominator games, survivorship, y-axis crimes, cherry-picked windows…), the story the data would tell under honest framing, and the three questions to ask the metric's owner.
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 Business, Finance & HR, covering OKRs and executive reporting and Slides and decks. 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
- Numbers feel too tidy
- A narrative rests on one chart
- You inherited metrics you didnt define
Example prompts
- “/metric-gaslighting-detector”
Workflow steps
11 steps, taken from the first numbered list in SKILL.md.
- Denominator games — the base changed ("of active users" quietly became "of weekly active")
- Survivorship framing — measuring only what remained (retention of cohorts that didn't churn early)
- Y-axis crimes — truncated baselines, dual axes, log scales without labels
- The cherry window — the date range that starts at the trough or ends before the drop
- Mix-shift laundering — the aggregate improved because composition changed, not performance
- Ratio without magnitude — "+40%!" concealing 5→7
- The vanity proxy — measuring what moves instead of what matters (signups for activation)
- Goodhart's ghost — the metric improved because it became a target, and the gamed behaviour is visible elsewhere
- Smoothing to silence — rolling averages wide enough to bury the event being asked about
- The missing counterfactual — "up 20% since launch" with no baseline trend (it was up 25% before)
- Significance theatre — differences within noise presented as movement ("ticked up to 4.6 from 4.5, n=41")
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
Metric Gaslighting Detector loads about 1.1k tokens when it runs. Until then it costs about 129 tokens; SKILL.md has 560 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). 560 words, ~1,101 tokens.
Download SKILL.mdSave it as
.claude/skills/metric-gaslighting-detector/SKILL.md (or your agent's skills folder).- name
- metric-gaslighting-detector
- description
- Find out how a dashboard, KPI report, or metrics slide is lying to you — before you repeat its story in a bigger room. Use when numbers feel too tidy, a narrative rests on one chart, or you inherited metrics you didn't define. Produces a deception audit: every metric graded for the eleven classic distortions (denominator games, survivorship, y-axis crimes, cherry-picked windows…), the story the data would tell under honest framing, and the three questions to ask the metric's owner.
Metric Gaslighting Detector
Dashboards rarely contain false numbers. They contain true numbers arranged to create false beliefs. This skill audits the arrangement — the eleven standard distortions through which honest data becomes dishonest narrative.
Required Inputs
- The metrics artifact — the dashboard description, KPI table, chart, or the numbers with their labels exactly as presented. Include axis ranges, time windows, and any annotations; the lie usually lives there.
- The claim being made with it (if any) — "churn is under control", "the launch worked". The audit tests the claim-data connection, not the data alone.
The Eleven Distortions
- Denominator games — the base changed ("of active users" quietly became "of weekly active")
- Survivorship framing — measuring only what remained (retention of cohorts that didn't churn early)
- Y-axis crimes — truncated baselines, dual axes, log scales without labels
- The cherry window — the date range that starts at the trough or ends before the drop
- Mix-shift laundering — the aggregate improved because composition changed, not performance
- Ratio without magnitude — "+40%!" concealing 5→7
- The vanity proxy — measuring what moves instead of what matters (signups for activation)
- Goodhart's ghost — the metric improved because it became a target, and the gamed behaviour is visible elsewhere
- Smoothing to silence — rolling averages wide enough to bury the event being asked about
- The missing counterfactual — "up 20% since launch" with no baseline trend (it was up 25% before)
- Significance theatre — differences within noise presented as movement ("ticked up to 4.6 from 4.5, n=41")
Output Format
- The audit table — metric | distortion(s) detected | severity (🔴 changes the conclusion / 🟡 shades it / 🟢 clean) | the honest version of that number's sentence.
- The honest retelling (≤150 words) — what this data says under fair framing. Sometimes the story survives; say so — the detector earns trust by clearing metrics too.
- Three questions for the owner — specific, answerable, non-accusatory ("what was the trend in the 8 weeks before launch?"), ordered by how much the answer would change the conclusion.
- The one chart to request — the single re-cut (full window, fixed denominator, split by segment) that would settle the biggest 🔴.
Show full SKILL.md (212 more words)Show less
Quality Checks
- Every 🔴 names the specific mechanism and what the conclusion becomes without it — "misleading" alone is not a finding
- At least one metric is graded 🟢 or the audit admits the artifact gave nothing to clear — all-guilty audits read as motivated
- The honest retelling uses only the numbers present — the detector doesn't smuggle in its own speculation
- Questions are answerable from data the owner plausibly has, and none contain an accusation
- Distortion names from the list are used consistently so repeated audits build a shared vocabulary
Anti-Patterns
- Do not accuse people of lying — the framing is "what belief does this arrangement create vs what the data supports"; most gaslighting dashboards are self-deception forwarded
- Do not grade a metric 🔴 for a distortion that doesn't change the decision at hand — severity is about consequences, not purity
- Do not demand data that doesn't exist as a gotcha — the three questions must be realistically answerable
- Do not rewrite the numbers — the honest retelling reframes; it never adjusts figures
- Do not skip auditing metrics that support conclusions you like — run the eleven on the favourable ones first
Example Trigger Phrases
- "These numbers feel too tidy."
- "Is this dashboard lying to me?"
- "Audit this KPI report before I present it."
- "I inherited these metrics: can I trust them?"
© 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/metric-gaslighting-detector of mohitagw15856/pm-claude-skills.
Open the folder on GitHubat commit 1cbf1f0
Compare with similar skills
Metric Gaslighting Detector 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 |
|---|---|---|---|---|---|---|
| Metric Gaslighting Detector this skillmohitagw15856/pm-claude-skills | 1.4k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Replit Decksanqiufong/slides-from-anything | 132 | 1 repos | ~2.9k | Automated safety check: Pass | Apache-2.0 | |
| Presentation Designcbrock84/headcount | 2k | — | ~1.2k | Automated safety check: Pass | MIT | |
| Pitch Deckagentii-ai/agentii-investment-intelligence | 207 | — | ~2k | Automated safety check: Pass | Apache-2.0 | |
| Board Meeting Prepw95/awesome-claude-corporate-skills | 244 | — | ~3.2k | Automated safety check: Pass | MIT | |
| Job Intent TrackerAli-Marandi/Web-Scraper-Framework | 107 | — | ~819 | Automated safety check: Pass | None |
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Categories
Questions about Metric Gaslighting Detector
What does Metric Gaslighting Detector do?
Find out how a dashboard, KPI report, or metrics slide is lying to you — before you repeat its story in a bigger room. Metric Gaslighting Detector is an agent skill from mohitagw15856/pm-claude-skills. Find out how a dashboard, KPI report, or metrics slide is lying to you — before you repeat its story in a bigger room.
When should I use Metric Gaslighting Detector?
Metric Gaslighting Detector fits situations like: numbers feel too tidy; A narrative rests on one chart; you inherited metrics you didnt define.
How do I install Metric Gaslighting Detector in Claude Code?
Run `npx skills add mohitagw15856/pm-claude-skills --skill metric-gaslighting-detector -a claude-code`. Or copy the skill folder (skills/metric-gaslighting-detector in mohitagw15856/pm-claude-skills) into .claude/skills/metric-gaslighting-detector in your project. Claude Code loads it when a task matches its description.
How do I install Metric Gaslighting Detector in Codex?
Run `npx skills add mohitagw15856/pm-claude-skills --skill metric-gaslighting-detector -a codex`. Or copy the skill folder (skills/metric-gaslighting-detector in mohitagw15856/pm-claude-skills) into .agents/skills/metric-gaslighting-detector in your project. Codex loads it when a task matches its description.
Can I use Metric Gaslighting Detector 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 metric-gaslighting-detector -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/metric-gaslighting-detector, .gemini/skills/metric-gaslighting-detector, .github/skills/metric-gaslighting-detector and .opencode/skills/metric-gaslighting-detector in your project.
What does Metric Gaslighting Detector need to run?
SKILL.md names no scripts, command-line tools or credentials: Metric Gaslighting Detector is instructions for the agent only.
Does Metric Gaslighting Detector 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 Metric Gaslighting Detector 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 Metric Gaslighting Detector use?
Metric Gaslighting Detector 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 Metric Gaslighting Detector use?
About 1.1k tokens (SKILL.md is roughly 4.4k 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 Metric Gaslighting Detector?
Skills that share tags, products or a category with Metric Gaslighting Detector: Replit Deck (sanqiufong/slides-from-anything, 132 stars), Presentation Design (cbrock84/headcount, 2k stars), Pitch Deck (agentii-ai/agentii-investment-intelligence, 207 stars) and Board Meeting Prep (w95/awesome-claude-corporate-skills, 244 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Metric Gaslighting Detector?
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.