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revenuecat-forecasting

Use this skill whenever the user asks for a forecast, projection, extrapolation, or run-rate (MRR, ARR, revenue, or subscribers N months out; revenue to the end of the month or year), or asks what ad spend or acquisition is needed to hit a growth target. Load it before pulling charts for the projection.

Quality

85%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

81%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

An operationally strong playbook: exact MCP call patterns, formulas, per-duration due/rate rules, and a sequenced workflow with real validation checkpoints and guardrails against known wrong methods. The main improvement opportunities are consolidating the repeated anti-pattern warnings and providing one complete runnable script template.

Suggestions

Consolidate the blended-churn / second-model warning, which is restated in the churn line, short horizons, steps, and wrong-example sections, into a single authoritative guardrail statement.

Provide one complete executable script template in the Correct block that wires the Status, Retention/Cohort, and MRR Movement pulls into the step loop, instead of schematic fragments.

Show the inflow run-rate derivation (the MRR Movement pull and how new/resub/expansion become inflow[m]) with the same concrete get-chart-data example given for Subscription Status.

DimensionReasoningScore

Conciseness

The body is dense and directive with no explanation of concepts Claude already knows, but the anti-pattern warning about blended churn / second-method projections ("never as a second method that sets the headline number") is repeated across at least four sections and could be consolidated.

4 / 5

Actionability

Highly concrete guidance — a full get-chart-data call with exact parameters (segment=expiration_month, selectors, limit_num_segments), the churn formula, and a per-duration due/rate table — but the Correct script blocks are schematic (e.g., "due_annual_next = 28316.52", "inflow_run_rate") rather than a copy-paste runnable template wired to the chart pulls.

4 / 5

Workflow Clarity

The MRR Steps are clearly sequenced (pull stocks, pull due, pull rates, pull inflows, compute in one script, present) with explicit validation checkpoints ("If month-1 modeled churn ≠ observed, print the gap as a diagnostic only", "Every rate literal in code must appear in a prior tool output") and an error-recovery path ("If you cannot pull due at all, ask for the renewal schedule"), plus a routing section that dispatches each ask type to the right workflow.

5 / 5

Progressive Disclosure

A clear routing overview ("Pick the section that matches the ask") and well-organized sections, with all content appropriately inline for a single-task skill with no bundle files; however at ~172 lines with no reference layering, the wrong-example gallery and duration table could partially live in a reference file.

4 / 5

Total

17

/

20

Passed

Description

83%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description with an explicit trigger clause, concrete metric-level keywords, and clear what/when coverage. Its main gaps are a missing common synonym ("predict") and no platform scoping, which slightly raise conflict risk with generic forecasting skills.

Suggestions

Add "predict" (and similar natural phrasings like "how much revenue will we make") to the trigger list in the description.

Scope the description to RevenueCat (e.g., "for RevenueCat projects") so generic forecasting asks outside the platform do not trigger this skill over others.

Mention the scenario (low/base/high) forecast capability so the description covers all three ask types the body handles.

DimensionReasoningScore

Specificity

The description names several concrete capability areas — "forecast, projection, extrapolation, or run-rate (MRR, ARR, revenue, or subscribers N months out)" plus "what ad spend or acquisition is needed to hit a growth target" — but stops short of comprehensively enumerating the distinct forecast modes (rest-of-period run-rates, scenario forecasts) that the body covers.

4 / 5

Completeness

It explicitly answers both what (produces forecasts/projections/run-rates for MRR, ARR, revenue, subscribers; solves for spend to hit targets) and when ("Use this skill whenever the user asks for a forecast, projection, extrapolation, or run-rate...") with concrete trigger phrases and load-timing guidance ("Load it before pulling charts for the projection").

5 / 5

Trigger Term Quality

Strong natural keywords users would actually say ("forecast", "projection", "run-rate", "MRR", "ARR", "N months out", "ad spend", "growth target"), but common synonyms such as "predict" or phrasings like "how many subscribers will we have" are missing.

4 / 5

Distinctiveness Conflict Risk

The forecasting triggers form a clear niche distinct from a sibling charts skill, but the description never scopes itself to RevenueCat, so generic revenue-forecasting asks unrelated to the platform could trigger it over other analytics skills.

4 / 5

Total

17

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

RevenueCat/ai-toolkit

Path

revenuecat/skills/revenuecat-forecasting/SKILL.md

Reviewed

Table of Contents

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