# Strategy Performance Review > Use this skill to review whether a strategic concept's bets actually played out — a positioning claim, a channel allocation, a content-strategy pillar mix, a GTM milestone, or a campaign's stated goals. Invoke when the user says "review our strategy performance", "did our positioning hold up", "how did the campaign perform against plan", "review the channel mix results", or "strategic performance review". Works from whatever performance data the owner pastes in — there is no analytics API integration. Do NOT use it to analyze how an individual content piece performed structurally or tonally — that is content-performance-review's job, a different plugin's skill at the content-piece altitude, not the strategy altitude. - Skill: `clever-cc-plugins/strategy-performance-review` (Agent Skill) - Install (CLI): `npx skillmds@latest add clever-cc-plugins/strategy-performance-review` - Raw SKILL.md: https://api.skillmd.com/api/skills/clever-cc-plugins/strategy-performance-review/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Marketing & Growth - Author: clever-cc-plugins (https://skillmd.com/u/clever-cc-plugins) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/clever-cc-plugins/strategy-performance-review --- # Strategic Performance Review Skill This skill closes the loop every other `cc-concept` skill's Step 7 (feedback) opens but never resolves: whether the strategic bet a concept document made actually played out once real-world results came in. It never regenerates a positioning document, channel plan, content strategy, GTM plan, or campaign concept itself — that stays the job of the skill that produced it. It names which bet held up and recommends the specific adjustment to feed into that skill's next run. This skill adapts `../_shared/skill-contract.md`'s 8-step sequence rather than following it literally — Steps 1–2 below do more work than the contract's generic description, because five structurally different artifact types (positioning, channel mix, content strategy, GTM plan, campaign concept) must be normalized into the same shape before any performance data is compared against them. ## Step 0: Recall learnings If `.claude/learnings.md` exists, read it silently. Apply relevant entries — in particular, prior review scope choices or promotion-target preferences. Do not announce this step. If the file is absent, continue normally. ## Step 1: Load context and identify scope Read the `## Context files` table in `CLAUDE.md`. List every registered concept-scope document you find: positioning, channel plan, content strategy, GTM plan, campaign brief — matching against each row's **Summary**, never its label or filename. If the owner already named which concept(s) to review, use that. Otherwise ask once: > "Which concept should I review — positioning, channel mix, content strategy, GTM > plan, a campaign brief, or more than one? I found: ." If nothing is registered, say so and stop — there is no baseline to check performance against: > "I don't see any concept documents registered yet. Run one of the concept-generation > skills first (e.g. `/positioning`, `/channel-advisor`) before > reviewing its performance." ## Step 2: Extract the bets For each document in scope, read it and extract its falsifiable bets in this uniform shape: ``` Bet: Expected signal: Source: ``` Apply per artifact type: - **Positioning document** → one bet: the target segment + differentiation claim resonates. - **Channel plan** → one bet per recommended channel: this allocation produces this outcome. - **Content strategy** → one bet per pillar: this pillar performs per its stated role in the mix. - **GTM plan** → one bet per milestone: this milestone is achievable on this timeline. - **Campaign concept** → one bet per stated goal. Present the full extracted list **before** moving to Step 3 — the owner can correct a misread bet before any data gets compared against it. ## Step 3: Gather performance data Ask for whatever the owner has against the extracted bets: > "What actually happened? Paste whatever data you have — channel results, campaign > KPIs vs. goals, pillar-level engagement, milestone status, or just your read on how > it went." If data only covers some of the extracted bets, proceed with what's available. Note which bets remain unevaluated — never fabricate a verdict for a bet with no data. ## Step 4: Verdict per bet For each bet with data, assign exactly one of: **Validated**, **Invalidated**, **Inconclusive** — with the evidence cited. For each bet without data: **Unevaluated**. **Never average verdicts across bets into one score.** A channel plan with three validated channels and one invalidated one gets four separate verdicts, not a 75%. For each Validated or Inconclusive bet, note "no change needed" or a minor refinement. For each Invalidated bet, recommend re-running the specific upstream skill that produced the document, naming the specific adjustment (e.g. "re-run `/channel-advisor` with budget shifted away from Channel X" — not a generic "reconsider this channel"). ## Step 5: Internal quality check Confirm every verdict traces to either the extracted bet (Step 2) or the pasted data (Step 3) — no verdict should introduce a claim that wasn't stated in either. Fix any gaps before proceeding. ## Step 6: Delimited output ``` ───────────────────────────────────────────────────────────────── Strategy performance review — ───────────────────────────────────────────────────────────────── Bet: Verdict: Validated | Invalidated | Inconclusive | Unevaluated Evidence: Recommendation: ` with | no change needed> [repeat per bet] ───────────────────────────────────────────────────────────────── ``` ## Register output Write the review to `context/strategy-performance-review.md` by convention. Apply the same collision-check logic as `positioning`'s Step 6: 1. Check if `context/strategy-performance-review.md` exists. 2. If it exists, generate a distinct filename by appending a `-N` suffix before `.md` (e.g. `context/strategy-performance-review-2.md`). Keep incrementing N until a filename that does NOT already exist is found. Never overwrite an existing review. 3. Write to the final, collision-checked filename. Confirm the file was created, then add a row to the `## Context files` table in `CLAUDE.md`: ```markdown | Strategy performance review | `context/strategy-performance-review.md` | Verdicts on which positioning/channel/content-strategy/GTM bets were validated by real-world results | ``` The Summary must be semantic and describe what the file covers. Do **not** hand-edit the **Key Config Files** table — the pre-commit hook owns that sync. ## Step 7: Feedback Store learnings tagged `[cc-concept:strategy-performance-review]` in `.claude/learnings.md`. Examples: ``` [cc-concept:strategy-performance-review] client always wants channel-level data even when campaign hit overall goal — 2026-07-19 [cc-concept:strategy-performance-review] positioning bets take 2+ quarters to show signal; flag short review windows as inconclusive — 2026-07-19 ``` If the session revealed a review-scope preference, a recurring evidence gap, or a project constraint that future reviews should apply, record it now.