skill-creator
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an…
Activate for: performance analysis, campaign performance, marketing analytics, channel performance, what's working, what's not working, optimise campaign, improve results, weekly report, marketing report, ROI, cost per lead, CPL, ROAS, return on ad spend, email performance,
$ npx -y skills add panaversity/agentfactory-business-plugins --skill performance-analysis --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/performance-analysisContext preview
The summary Claude sees to decide when to auto-load this skill.
Activate for: performance analysis, campaign performance, marketing analytics, channel performance, what's working, what's not working, optimise campaign, improve results, weekly report, marketing report, ROI, cost per lead, CPL, ROAS, return on ad spend, email performance,
name: performance-analysis description: > Activate for: performance analysis, campaign performance, marketing analytics, channel performance, what's working, what's not working, optimise campaign, improve results, weekly report, marketing report, ROI, cost per lead, CPL, ROAS, return on ad spend, email performance, LinkedIn performance, A/B results, conversion rate, click rate, open rate, lead quality analysis. NOT for: automated weekly reporting (use marketing-performance-agent), revenue dashboards (use revenue-reporting-agent), pipeline analysis (use pipeline), campaign planning (use campaign-planning). context: fork
Accept via MCP connection or pasted data:
LAYER 1 -- ARE WE ON TRACK? Compare actuals vs. targets for primary KPI and secondary KPIs. Classify each metric: On track / At risk / Off track
LAYER 2 -- WHY? (root cause, not symptom) For each at-risk or off-track metric: diagnose the root cause. Example: low email CTR -> is it the subject line (low open rate would confirm), or the body content (high open, low click = body problem)? Do not recommend actions until root cause is confirmed.
LAYER 3 -- WHAT TO DO (specific, not generic) For each root cause: one specific change, with expected impact. "Rewrite Email 3" is not specific enough. "Rewrite Email 3 -- replace the three general patterns with one anonymised case study using the format: [Company type], [Problem], [Specific outcome]. Expected CTR improvement: +1-1.5%." is specific.
LAYER 4 -- WHAT NOT TO CHANGE Identify what is working and name it explicitly. Optimisation teams have a bias to change things that are working. Naming what to protect is as important as naming what to fix.
CAMPAIGN PERFORMANCE ANALYSIS -- Week [N] of [Total] Generated: [Date] | Campaign: [Name] ================================================================
HEADLINE NUMBERS -- THIS PERIOD [Metric]: [Actual] ([target]) -- [status] [% vs. target]
TOP [N] OPTIMISATION OPPORTUNITIES
[N]. [ISSUE NAME IN CAPS] Analysis: [What the data shows -- describe the pattern precisely] Diagnosis: [Root cause -- why this is happening] Change: [Exact change to make -- specific enough to action immediately] Owner: [Who does this] Deadline: [By when] Expected: [Quantified impact of making this change]
WHAT IS WORKING -- DO NOT CHANGE [Observation]: [Why it's working and what not to disrupt]
WEEK [N+1] ACTION PLAN [ ] [Action] -- [Owner] -- by [Date] ================================================================
| Metric | Poor | Average | Good | Best-in-class | | ------------------------- | ------ | ---------- | ---- | ------------- | | LinkedIn Sponsored CTR | <0.25% | 0.35-0.45% | 0.6% | >1% | | LinkedIn Thought Leader | <0.6% | 0.8-1.2% | 1.5% | >2% | | B2B email open rate | <20% | 28-35% | 40% | >50% | | B2B email CTR | <2% | 3.5-5% | 6% | >8% | | Landing page conversion | <5% | 10-20% | 25% | >35% | | Webinar to opp conversion | <10% | 15-20% | 25% | >30% | | MQL to SAL | <20% | 35-50% | 60% | >70% | | SAL to opp | <40% | 55-70% | 75% | >85% |
is meaningless; always compare to target, benchmark, or prior period
-- treating symptoms produces temporary improvement at best
testing whether the creative/copy/audience is the problem, not the channel
drive decisions, not to describe what happened
primary success indicators -- measure outcomes that predict revenue
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