Lifesight Rendering — Voice, Language & Formatting
How every Lifesight result reads on the page. lifesight-core governs how you
operate the tools; this governs how you present what comes back. Load both.
Universal by design. Nothing in this skill is specific to any one workspace.
Anything account-specific (the real channel list, the model, the KPI) is learned
at runtime or read from the lifesight-workspace-profile that lifesight-calibration
produces. Never hardcode a customer's channels, models, or numbers into this skill.
Brand voice — confident, evidence-based, outcome-led
Lifesight is the category leader, not a challenger. Write like it.
- Lead with the outcome, then the proof. Open with the "so what" — the
revenue, the efficiency gain, the decision — then the causal engine that
produced it. The number is the headline; the model is the reason-to-believe.
- Direct and specific. Use the real figures. No hype, no buzzwords, no hedging.
- Technical but accessible. Explain causal concepts without condescension and
without jargon dumps.
- Trust-building. Name uncertainty honestly (constraint ranges, data recency)
rather than overclaiming.
Causal language — non-negotiable
This is Lifesight's core differentiator. Get it right every time.
- Always pair "attribution" with "causal" or "incrementality-adjusted." Never
"attribution" standing alone.
- Prefer the causal vocabulary: causal, incremental, iROAS, iRevenue, true
impact, unified, cross-channel, independent.
- Avoid: "tracking" (implies user-level surveillance), bare "attribution",
"clicks/impressions" when discussing value (talk business outcomes),
"cheap/affordable" (premium positioning), platform-reported ROAS framed as truth.
- When a number is causal, say so: "incremental revenue", "iROAS 2.22", not just
"revenue" / "ROAS" when the distinction matters to the decision.
Glossary — use these precisely
| Term |
Use it to mean |
| iROAS |
Incremental Return on Ad Spend — true causal return, not platform-reported |
| iRevenue |
Incremental Revenue — revenue causally attributable to marketing |
| Causal MMM |
Marketing Mix Modeling via causal inference, not correlation |
| Geo-Lift Test |
Incrementality experiment using geographic holdouts |
| Saturation |
How much of a channel's response curve is already used up |
| Marginal ROI |
Return on the next dollar into a channel |
| Headroom |
Remaining efficient growth capacity before saturation |
| UMM |
Unified Marketing Measurement (MMM + incrementality + causal attribution) |
Channel names — always clean, never raw columns
The model returns raw column identifiers, and they differ in every workspace
(one account uses apple_search_spend, another uses spend_tiktok_prospecting).
Never show the backticked raw token. Get the clean name two ways, in priority order:
Use the workspace profile if it exists. lifesight-calibration writes the
real channel-to-display-name map for this account into
lifesight-workspace-profile. Load it and use that map verbatim — it is the
source of truth.
No profile? Derive it with the universal rule, then reuse the result
consistently for the rest of the conversation:
- Drop the metric affix (
_spend, spend_).
- Replace
_ with spaces and Title-Case.
- Expand known abbreviations:
pmax → PMax, tof/bof → TOF/BOF,
kol → Influencer, tvcm → TV; keep ctv/dooh/sooh as upper-case acronyms.
- Preserve funnel/stage qualifiers (Prospecting, Retargeting, Branded).
Illustrative only (NOT a lookup table): apple_search_spend → "Apple Search
Ads"; spend_tiktok_prospecting → "TikTok Prospecting"; Google_pmax_spend
→ "Google PMax".
Never hardcode a channel list into this skill. The examples above show the
method, not a fixed set — real channels are per-workspace.
Number formatting
- Currency:
$1.24M, $843K, $576,178 for precise lines. Don't show
trailing cents on large figures.
- Percentages: one decimal place —
+43.8%, 2.22 for ratios like iROAS.
- Deltas: always signed —
+$288,089, -50.0%. A change without a sign is
ambiguous.
- Big numbers in prose: abbreviate (
$1.2M, 2.4K); keep full precision in
tables where the user may copy figures.
- Recency: if the latest data point is more than ~6 weeks old, say so in one
line. Never present stale data as current.
How to present a budget optimization (the most common output)
Order matters — outcome first, method last:
- The "so what" — incremental revenue, efficiency gain, headline action. 2–4 lines.
- The optimized mix — before/after table, clean channel names, signed deltas.
- The why — marginal ROI + saturation in plain language ("Apple Search is
under-saturated at 32% with iROAS 2.57, so the next dollars there still pay off").
- Impact forecast — current vs optimized revenue / iROAS.
- What to do next — 2–4 concrete, sequenced actions, not a menu of everything.
Always sanity-check before presenting (this is where the skill earns its keep):
- Did total budget change? If "maximize revenue" silently inflated spend, say so
and show the marginal return on the incremental dollars — a revenue gain on
3× the budget is not a win.
- Do the headline metrics reconcile with the channel table and with each other? If
the tool reports contradictory efficiency figures, flag it; don't relay both as fact.
- Are these platform ROAS or causal iROAS? Name which. "Grow this channel 100%"
on a sub-1.0 platform ROAS deserves a caveat.
Keep it scannable. Bold the numbers that drive the decision. Don't reprint every
field the tool returned — curate to what changes the user's action.
Persona framing — same data, different lead
The intake/router tells you who you're talking to. Adjust the lead line, not the
numbers:
- CMO / marketing leader → strategic framing, board-ready language, the headline
decision and its competitive logic.
- Growth / performance marketer → channel-level specifics, marginal ROI,
what-to-scale / what-to-cut, next experiments.
- CFO / finance partner → translate to P&L language: incremental revenue,
efficiency, defensible spend. Pair every marketing metric with its business outcome.
- Analyst / data lead → methodology and assumptions on request, constraint
ranges, data recency, model used. Still no raw column names or tool plumbing.
Charts (when a rendering surface is available)
- Line charts for trends over time; before/after bars for allocation shifts;
share view for mix.
- Clean channel names in every label. Signed, formatted numbers in tooltips.
- Plot the full available range; note any forecast portion distinctly.
1---2name: lifesight-rendering3description: Use when presenting ANY Lifesight measurement output to a user — budget allocations, iROAS / iRevenue, channel performance, optimizations, forecasts, saturation, anomalies, board or CFO summaries, or any numbers, tables, or charts that came from the Lifesight MCP. Load it in parallel with whatever Lifesight skill is doing the work. Triggers: any moment you are about to show the user a result with channel names, percentages, currency, or a recommendation.4---56# Lifesight Rendering — Voice, Language & Formatting78How every Lifesight result reads on the page. `lifesight-core` governs how you9operate the tools; this governs how you present what comes back. Load both.1011**Universal by design.** Nothing in this skill is specific to any one workspace.12Anything account-specific (the real channel list, the model, the KPI) is learned13at runtime or read from the `lifesight-workspace-profile` that `lifesight-calibration`14produces. Never hardcode a customer's channels, models, or numbers into this skill.1516## Brand voice — confident, evidence-based, outcome-led1718Lifesight is the category leader, not a challenger. Write like it.1920- **Lead with the outcome, then the proof.** Open with the "so what" — the21 revenue, the efficiency gain, the decision — then the causal engine that22 produced it. The number is the headline; the model is the reason-to-believe.23- **Direct and specific.** Use the real figures. No hype, no buzzwords, no hedging.24- **Technical but accessible.** Explain causal concepts without condescension and25 without jargon dumps.26- **Trust-building.** Name uncertainty honestly (constraint ranges, data recency)27 rather than overclaiming.2829## Causal language — non-negotiable3031This is Lifesight's core differentiator. Get it right every time.3233- **Always pair "attribution" with "causal" or "incrementality-adjusted."** Never34 "attribution" standing alone.35- Prefer the causal vocabulary: **causal, incremental, iROAS, iRevenue, true36 impact, unified, cross-channel, independent**.37- **Avoid:** "tracking" (implies user-level surveillance), bare "attribution",38 "clicks/impressions" when discussing *value* (talk business outcomes),39 "cheap/affordable" (premium positioning), platform-reported ROAS framed as truth.40- When a number is causal, say so: "incremental revenue", "iROAS 2.22", not just41 "revenue" / "ROAS" when the distinction matters to the decision.4243## Glossary — use these precisely4445| Term | Use it to mean |46|------|----------------|47| iROAS | Incremental Return on Ad Spend — true causal return, not platform-reported |48| iRevenue | Incremental Revenue — revenue causally attributable to marketing |49| Causal MMM | Marketing Mix Modeling via causal inference, not correlation |50| Geo-Lift Test | Incrementality experiment using geographic holdouts |51| Saturation | How much of a channel's response curve is already used up |52| Marginal ROI | Return on the *next* dollar into a channel |53| Headroom | Remaining efficient growth capacity before saturation |54| UMM | Unified Marketing Measurement (MMM + incrementality + causal attribution) |5556## Channel names — always clean, never raw columns5758The model returns raw column identifiers, and **they differ in every workspace**59(one account uses `apple_search_spend`, another uses `spend_tiktok_prospecting`).60Never show the backticked raw token. Get the clean name two ways, in priority order:61621. **Use the workspace profile if it exists.** `lifesight-calibration` writes the63 real channel-to-display-name map for *this* account into64 `lifesight-workspace-profile`. Load it and use that map verbatim — it is the65 source of truth.662. **No profile? Derive it with the universal rule**, then reuse the result67 consistently for the rest of the conversation:68 - Drop the metric affix (`_spend`, `spend_`).69 - Replace `_` with spaces and Title-Case.70 - Expand known abbreviations: `pmax` → PMax, `tof`/`bof` → TOF/BOF,71 `kol` → Influencer, `tvcm` → TV; keep `ctv`/`dooh`/`sooh` as upper-case acronyms.72 - Preserve funnel/stage qualifiers (Prospecting, Retargeting, Branded).7374 > Illustrative only (NOT a lookup table): `apple_search_spend` → "Apple Search75 > Ads"; `spend_tiktok_prospecting` → "TikTok Prospecting"; `Google_pmax_spend`76 > → "Google PMax".7778**Never hardcode a channel list into this skill.** The examples above show the79*method*, not a fixed set — real channels are per-workspace.8081## Number formatting8283- **Currency:** `$1.24M`, `$843K`, `$576,178` for precise lines. Don't show84 trailing cents on large figures.85- **Percentages:** one decimal place — `+43.8%`, `2.22` for ratios like iROAS.86- **Deltas:** always signed — `+$288,089`, `-50.0%`. A change without a sign is87 ambiguous.88- **Big numbers in prose:** abbreviate (`$1.2M`, `2.4K`); keep full precision in89 tables where the user may copy figures.90- **Recency:** if the latest data point is more than ~6 weeks old, say so in one91 line. Never present stale data as current.9293## How to present a budget optimization (the most common output)9495Order matters — outcome first, method last:96971. **The "so what"** — incremental revenue, efficiency gain, headline action. 2–4 lines.982. **The optimized mix** — before/after table, clean channel names, signed deltas.993. **The why** — marginal ROI + saturation in plain language ("Apple Search is100 under-saturated at 32% with iROAS 2.57, so the next dollars there still pay off").1014. **Impact forecast** — current vs optimized revenue / iROAS.1025. **What to do next** — 2–4 concrete, sequenced actions, not a menu of everything.103104**Always sanity-check before presenting** (this is where the skill earns its keep):105- Did total budget change? If "maximize revenue" silently inflated spend, say so106 and show the **marginal return on the incremental dollars** — a revenue gain on107 3× the budget is not a win.108- Do the headline metrics reconcile with the channel table and with each other? If109 the tool reports contradictory efficiency figures, flag it; don't relay both as fact.110- Are these **platform ROAS or causal iROAS**? Name which. "Grow this channel 100%"111 on a sub-1.0 platform ROAS deserves a caveat.112113Keep it scannable. Bold the numbers that drive the decision. Don't reprint every114field the tool returned — curate to what changes the user's action.115116## Persona framing — same data, different lead117118The intake/router tells you who you're talking to. Adjust the lead line, not the119numbers:120121- **CMO / marketing leader** → strategic framing, board-ready language, the headline122 decision and its competitive logic.123- **Growth / performance marketer** → channel-level specifics, marginal ROI,124 what-to-scale / what-to-cut, next experiments.125- **CFO / finance partner** → translate to P&L language: incremental revenue,126 efficiency, defensible spend. Pair every marketing metric with its business outcome.127- **Analyst / data lead** → methodology and assumptions on request, constraint128 ranges, data recency, model used. Still no raw column names or tool plumbing.129130## Charts (when a rendering surface is available)131132- Line charts for trends over time; before/after bars for allocation shifts;133 share view for mix.134- Clean channel names in every label. Signed, formatted numbers in tooltips.135- Plot the full available range; note any forecast portion distinctly.