# Stakeholder Readout

> Structures a stakeholder-ready analysis writeup with TL;DR, evidence, decision, and next steps. Use when the user asks for a readout, analysis writeup, insight doc, exec summary, "share this with the team", "make this stakeholder-friendly", or "summarize the findings."

- Skill: `vermapragya/stakeholder-readout` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add vermapragya/stakeholder-readout`
- Raw SKILL.md: https://api.skillmd.com/api/skills/vermapragya/stakeholder-readout/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Product & Planning
- Author: vermapragya (https://skillmd.com/u/vermapragya)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/vermapragya/stakeholder-readout

---


# Stakeholder Readout

## When to use this skill

Use whenever an analysis output needs to be communicated to a non-DS audience (PM, eng, exec, sales). Triggers:

- "Write a readout for…"
- "Summarize the findings"
- "Make this stakeholder-friendly"
- "Exec summary of…"
- "Share this with the team"

Pair with any analysis-producing skill (`ab-test-analysis`, `cohort-analysis`, `survival-analysis`, etc.). This skill is the **packaging layer**.

## Required inputs

| Input | Why it matters |
|---|---|
| Question being answered | The decision this informs |
| Audience | PM / Exec / Eng / Mixed — affects depth |
| Key finding | The 1-2 sentence headline |
| Evidence (data / charts) | Numbers backing the finding |
| Confidence level | How sure are we? |
| Recommended decision | What you'd do if it were your call |

## The readout structure

Every readout has exactly five sections, in this order:

1. **TL;DR** — One sentence, one decision recommendation
2. **Context** — What question + why now
3. **Findings** — 2-5 key facts with evidence
4. **Decision** — What to do, by whom, by when
5. **Caveats & next steps** — What we don't know

## Workflow

1. **Write the TL;DR first.** If you can't summarize in one sentence, you don't understand it yet. The TL;DR must contain:
   - The answer to the question
   - The recommended action
   - Confidence indicator ("strong evidence" / "directional" / "preliminary")

2. **List 2-5 findings**, each with:
   - The fact (one sentence)
   - The data behind it (number + comparison + context)
   - Why it matters (decision relevance)

3. **State the decision explicitly.** Not "this suggests we might want to consider…" — but "Ship the change" / "Hold and investigate" / "No action needed."

4. **List caveats**, sorted by how much they should change the decision. If a caveat would change the recommendation, surface it at the top.

5. **End with next steps** — concrete, owned, time-bound.

6. **Run the conclusions audit before publishing.** Every readout passes the three checks below (see "Conclusions audit") — claims↔evidence traceability, causation language, and cherry-picking. A readout that fails any check doesn't ship until fixed.

## Output format

```markdown
# <Analysis Title>

**Author:** <name>  
**Audience:** <PM / Exec / Eng / Mixed>  
**Date:** <YYYY-MM-DD>  
**Status:** <Final | Draft for review | Preliminary>

---

## TL;DR
<One sentence. Includes finding + recommendation + confidence.>

**Recommendation:** <Specific action, e.g., "Ship the new onboarding flow to 100%">  
**Confidence:** <Strong | Moderate | Directional / preliminary>

---

## Context
- **Question:** <The decision this analysis informs>
- **Why now:** <The trigger — leadership ask, opportunity sized, problem detected>
- **What we did:** <Method in one paragraph — no jargon, name the technique>

---

## Findings

### Finding 1: <one-sentence headline>
<2-3 sentences expanding the fact, with the specific number and a comparison>

> Evidence: chart, table, or query result

### Finding 2: <one-sentence headline>
<...>

### Finding 3: <one-sentence headline>
<...>

---

## Decision

**Recommended:** <Specific action>

**Owner:** <Name(s)>

**Timeline:** <When>

**Why this and not alternatives:**
- Considered: <alternative 1> — rejected because <reason>
- Considered: <alternative 2> — rejected because <reason>

---

## Caveats & next steps

### What we don't know
- <Caveat 1, ordered by how much it could change the decision>
- <Caveat 2>

### Next steps
1. **<Action>** — <owner> — <by when>
2. **<Action>** — <owner> — <by when>
3. **<Action>** — <owner> — <by when>

---

## Appendix
<Optional: methodology details, charts, secondary findings — only for those who want the depth>
```

## Conclusions audit

Run this on the finished draft, before it ships. Audit the narrative as a skeptical reviewer would — the goal is that no claim in the readout can be embarrassed by someone reading the appendix.

### Check 1: Every claim is supported by evidence

Walk the narrative claim by claim. For each declarative statement, ask: **which number, chart, or test in this readout backs it?**

- Every claim in the TL;DR, findings, and decision must trace to specific evidence *in the document* (or its appendix) — not to "we know" or "it's well understood."
- The strength of the language must match the strength of the evidence:

| Evidence | Allowed language |
|---|---|
| Significant, pre-registered result | "X increased Y by 8%" |
| Directional but not significant | "X appears to increase Y (not yet conclusive)" |
| Single segment / small N | "In <segment>, we observed…" (never generalize to all users) |
| No supporting data in the doc | Delete the claim or add the evidence |

- Watch for **smuggled claims**: causal or quantitative statements hiding in transitions ("because users were confused, retention fell") — that "because" needs evidence too.

### Check 2: Causation language matches the study design

Causal verbs — *caused, drove, increased, reduced, led to, because of* — are earned by design, not by effect size.

| Design | Language allowed |
|---|---|
| Randomized experiment (clean) | "The change **increased** conversion by 8%" |
| Quasi-experiment (DiD, matching, IV) | "The change is **associated with** +8%; causal under <stated assumptions>" |
| Observational / correlational | "Users who did X converted more — **selection effects likely**; we cannot say X causes conversion" |
| Pre/post with no control | "Conversion rose after launch — **other factors changed too**; not attributable" |

- Scrub the TL;DR hardest: it's the most-quoted sentence and the most likely place an "is associated with" silently becomes "drove."
- If the recommendation requires a causal claim the design can't support, say so explicitly and route to `ab-test-design` or `causal-inference` as a next step.

### Check 3: No cherry-picking

The narrative must survive contact with everything you looked at, not just what made the slide.

- **Metrics:** were any metrics checked but omitted because they were flat or negative? Report them — one line each is enough ("Guardrails: latency, churn, support tickets — all flat").
- **Time windows:** does the conclusion hold on the natural window (full quarter, all weeks), or only the window shown? If the window was chosen after seeing data, disclose it.
- **Segments:** is the headline a whole-population effect, or did one segment carry it? Report the segment composition; never present a subgroup win as a global win.
- **Multiple comparisons:** if 20 segments/metrics were tested, ~1 will look significant by chance. State how many things were tested; treat unplanned subgroup findings as hypotheses, not conclusions.
- **Outliers & exclusions:** any rows/users excluded? State the rule, the count, and whether the conclusion holds with them included.

**The two-question gut check:**
1. "If a skeptic saw *everything* I looked at, would they accept this narrative?"
2. "Did I decide the story before or after I saw this evidence?" — if before, the omitted evidence gets extra scrutiny.

### Audit output

Append a short audit trail to the readout (or appendix) so reviewers can verify the audit ran:

```markdown
## Conclusions audit
- Claims↔evidence: all N claims traced to evidence (claim 3 softened: directional, not significant)
- Causation language: observational design — all causal verbs replaced with "associated with"
- Cherry-picking: 6 metrics examined, 2 flat (reported in appendix); no post-hoc window changes; headline effect holds with outliers included
```

## Validation checks

- [ ] TL;DR is ONE sentence
- [ ] TL;DR includes a specific recommendation
- [ ] Each finding has a number AND a comparison (vs prior period, vs benchmark, vs alternative)
- [ ] Decision is unambiguous (not "could be valuable to explore")
- [ ] Owner and timeline named for every next step
- [ ] Caveats include the worst-case "this could be wrong because…"
- [ ] Length appropriate for audience (exec = 1 page; team = up to 3 pages)
- [ ] No statistical jargon without translation (p-value → "very strong evidence")
- [ ] **Conclusions audit ran**: every claim traced to evidence in the doc
- [ ] **Causation language** matches the study design (causal verbs only for experiments)
- [ ] **No cherry-picking**: flat/negative metrics reported; windows and exclusions disclosed; subgroup wins not presented as global

## Edge cases & failure modes

- **No clear recommendation.** If the data doesn't support a decision, the recommendation is "do X to get a clearer answer" — not silence. Common phrasings: "Run a follow-up experiment to disambiguate," "Defer for 4 weeks pending more data."

- **Findings contradict the asker's hypothesis.** Lead with the contradiction, don't bury it. Stakeholders trust analyses that confirm their priors AND ones that don't — they don't trust analyses that hedge.

- **Insufficient sample size / inconclusive.** Mark TL;DR as "Inconclusive — recommend X to get a definitive answer." Don't pretend uncertainty is certainty.

- **Stakeholder asks for a specific framing.** Push back if the framing distorts the finding. The job is accurate, not flattering.

- **Multiple audiences with different needs.** Default to the highest-stakes audience (exec). Optional: write 2 versions — 1-page exec, 3-page team.

## Writing style rules

| Don't | Do |
|---|---|
| "It seems like…" | "Conversion rose 8%." |
| "Could potentially be valuable…" | "Ship this." |
| "p < 0.05" | "Strong evidence (well below the noise threshold)." |
| "Statistically significant" | "Real, not noise." |
| Verbose throat-clearing | Get to the point in the first sentence. |
| Charts without titles | Every chart has a title that states the takeaway. |
| Numbers without comparison | "$1.2M, up 18% vs last quarter." |

## Templates by analysis type

See `templates/` directory in the parent repo for:
- `ab-test-readout.md`
- `cohort-readout.md`
- `model-readout.md`
- `insight-doc.md`

## Related skills

- `ab-test-analysis` — produces the analysis; this skill packages it
- `cohort-analysis`, `funnel-analysis` — same
- `metric-definition` — provides the precise definitions readouts reference
- Any modeling skill — wrap its output in this structure