
Chart & Statistics Integrity Gate — Catch Misleading Visuals & Unsound Claims
An adversarial gate that audits any chart, data summary, or statistic for misleading visuals and unsound inference, then returns one PASS/REVISE/FAIL verdict.
- Final pass before delivering a report figure or dashboard
- Catching misleading visuals in customer-facing data
- Integrity gate in an automated analytics or reporting pipeline
$12
· or 60 creditsSecure checkout via Stripe
Included in download
- Final pass before delivering a report figure or dashboard
- Catching misleading visuals in customer-facing data
- file_read automation included
- Ready for GPT
Sample input
Run the integrity gate on this figure before I put it in the board deck: "Revenue grew 40% — see the bar chart (y-axis starts at $4.2M, two bars: Q3 $4.4M, Q4 $4.6M). This proves our new pricing caused the jump."
Sample output
WEAKEST POINT: The "40% growth" headline is the load-bearing claim and it contradicts the data shown ($4.4M to $4.6M is ~4.5%, not 40%). The 40% appears to be an artifact of the truncated axis, not real growth.
ISSUES FOUND:
- Truncated axis: y-axis starts at $4.2M, exaggerating a 4.5% change into a visually large jump -> restart axis at $0 or label the true % change.
- Misstated statistic: "grew 40%" does not match $4.4M->$4.6M -> correct to ~4.5%.
- Correlation as causation: "proves our new pricing caused the jump" -> downgrade to "coincided with"; one quarter cannot prove causation.
- Missing context: no prior-quarter trend, no confidence interval, no mention of seasonality or other drivers.
MISSING CONTEXT: Baseline trend before Q3, sample/time window, and competing explanations for the change.
TOUGHEST QUESTIONS:
- Is the headline 40% the axis illusion or a real figure? (data shown says ~4.5%)
- What else changed in Q4 besides pricing? (not answered)
- How does Q3->Q4 compare to prior year-over-year quarters? (not answered)
DECISION: FAIL — fix the axis, correct the growth figure, and remove the causation claim before this goes in the deck.
An adversarial gate that audits any chart, data summary, or statistic for misleading visuals and unsound inference, then returns one PASS/REVISE/FAIL verdict.
$12
· or 60 creditsSecure checkout via Stripe
Included in download
- Final pass before delivering a report figure or dashboard
- Catching misleading visuals in customer-facing data
- file_read automation included
- Ready for GPT
- Instant install
Sample input
Run the integrity gate on this figure before I put it in the board deck: "Revenue grew 40% — see the bar chart (y-axis starts at $4.2M, two bars: Q3 $4.4M, Q4 $4.6M). This proves our new pricing caused the jump."
Sample output
WEAKEST POINT: The "40% growth" headline is the load-bearing claim and it contradicts the data shown ($4.4M to $4.6M is ~4.5%, not 40%). The 40% appears to be an artifact of the truncated axis, not real growth.
ISSUES FOUND:
- Truncated axis: y-axis starts at $4.2M, exaggerating a 4.5% change into a visually large jump -> restart axis at $0 or label the true % change.
- Misstated statistic: "grew 40%" does not match $4.4M->$4.6M -> correct to ~4.5%.
- Correlation as causation: "proves our new pricing caused the jump" -> downgrade to "coincided with"; one quarter cannot prove causation.
- Missing context: no prior-quarter trend, no confidence interval, no mention of seasonality or other drivers.
MISSING CONTEXT: Baseline trend before Q3, sample/time window, and competing explanations for the change.
TOUGHEST QUESTIONS:
- Is the headline 40% the axis illusion or a real figure? (data shown says ~4.5%)
- What else changed in Q4 besides pricing? (not answered)
- How does Q3->Q4 compare to prior year-over-year quarters? (not answered)
DECISION: FAIL — fix the axis, correct the growth figure, and remove the causation claim before this goes in the deck.
About This Skill
# Chart & Statistics Integrity Gate A pre-publish quality gate that makes your agent a hostile reviewer of every chart, table, and statistic before a human sees it. ## What this skill does Most agents present data agreeably. They describe a chart, quote a number, and move on. A skeptical data reviewer does the opposite: they assume the visual is misleading and the statistic is overstated, then try to prove it. This skill installs that posture as a final pass. The agent stops being the analyst and becomes an adversarial reviewer of its own data presentation. The output is not a redrawn chart or a recomputed number. It is a structured verdict: the weakest visual or claim, every misleading element, every missing piece of context, and a clear decision — PASS, REVISE, or FAIL. ## When to use it Run the gate as the last step before delivering anything that shows or cites data: dashboards, report figures, chart descriptions, data summaries, KPIs, or any statistic that will be quoted or acted on. It is most valuable for confident, polished-looking visuals, because that is exactly where distortion hides. ## The five review passes 1. **Axis & scale check.** Flag truncated or non-zero baselines, dual axes, inconsistent intervals, and log scales presented as linear. 2. **Cherry-pick scan.** Catch suspicious date ranges, dropped outliers, missing denominators, and selective comparisons that flatter one side. 3. **Chart-type fit.** Check that the chosen visual matches the data (e.g., pie charts used for non-parts-of-whole, line charts implying continuity across categories). 4. **Statistical-soundness audit.** Surface correlation stated as causation, small-sample or no-error claims, misleading averages, and percentages without base rates. 5. **Hostile-question rehearsal.** Generate the three toughest questions a skeptical analyst would ask, and check whether the presentation already answers them. ## The verdict format A compact, consistent block: the weakest visual/claim, each issue found (with a suggested fix), missing context, the three toughest analyst questions, and a final decision — PASS, REVISE, or FAIL — with a one-line justification. ## Why it works It separates the analyst role from the reviewer role. The same model is far more critical when explicitly told to argue against its own figures and to score them on adversarial criteria rather than on whether the chart looks clean. The structured passes stop the review from collapsing back into approval. ## What it is not This is a reasoning-and-prompting skill, not a charting tool or a statistics engine. It cannot run calculations, render charts, or access data. It surfaces misleading presentation and unsound inference in the data the agent already holds — it does not certify that the underlying numbers are correct. Pair it with an evidence or claim-grounding skill when factual verification is also required.
Use Cases
- Final pass before delivering a report figure or dashboard
- Catching misleading visuals in customer-facing data
- Integrity gate in an automated analytics or reporting pipeline
Known Limitations
Does not run calculations, render charts, or access data. It reviews the chart and statistics described in the text the agent already holds; it cannot confirm the underlying numbers are correct. Pair with an evidence or claim-grounding skill for factual verification.
How to Install
mkdir -p ~/.claude/skills && curl -sL https://www.agensi.io/api/install/chart-statistics-integrity-gate-catch-misleading-visuals-unsound-claims -o /tmp/chart-statistics-integrity-gate-catch-misleading-visuals-unsound-claims.zip && unzip -o /tmp/chart-statistics-integrity-gate-catch-misleading-visuals-unsound-claims.zip -d ~/.claude/skills && rm /tmp/chart-statistics-integrity-gate-catch-misleading-visuals-unsound-claims.zipFree skills install directly. Paid skills require purchase - use the download button above after buying.
Reviews
No reviews yet - be the first to share your experience.
Only users who have downloaded or purchased this skill can leave a review.
Early access skill
Be the first to review this skill.
Only users who have downloaded or purchased this skill can leave a review.
Security Scanned
Passed automated security review
Permissions
File Scopes
This skill only reads its own SKILL.md instructions. It needs no write, network, shell, or environment access — it operates purely on text the agent already holds.
Model-agnostic. Works with any SKILL.md-compatible agent (Claude, GPT, Gemini, Llama, Mistral). No external dependencies — pure reasoning and prompting. Runs entirely on text the agent already holds, with no network or write access.
Creator
PubsProToolkit builds AI agent skills that bring regulated-industry rigor to written output. Created by a CMPP-certified medical writer with a PhD and 10+ years in pharma — covering clinical and scientific publishing, plus evidence-grounded QC for any agent.
Frequently Asked Questions
Learn More About AI Agent Skills
More Premium Skills
designing-hybrid-context-layers
Architects the right retrieval strategy for every query — teaching your agent when to use RAG, a knowledge graph, or a temporal index instead of defaulting to vector search for everything.
consumer-motivation-analyzer
Go beyond surface-level feedback to uncover the psychological drivers and hidden motivations behind buyer behavior.
Bounty Security Pattern Master Library — 399 Vulnerability Patterns
A premium library of 399 vulnerability patterns and DeFi attack vectors for AI-driven bug hunting and security audits.
keyword-research
Transform URLs or product lists into SEO keyword research packs with Google Ads data and intent-based clustering.