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Activity Calendar Chart

A year of effort, visible in one glance.

Turns a list of dated events into a calendar heatmap: days as cells, weeks as columns, intensity shown by shade, with annotations for streaks, gaps, and peaks — plus the tidy daily table behind it.

Activity Calendar Chart preview
Best for
Habit trackers, teams, and reporters who want a year of activity visible in one picture
Time needed
~15 min for a first draft
Level
Beginner-friendly

Install it in 3 steps

No sign-up. No CLI tools. Pick your AI, copy one line, paste it over.

Pro — all 471 skills

Prefer doing it yourself? Buy the skill ($4.99), download the ZIP from your checkout confirmation, unzip it into the directory shown above, restart your AI session — same result. Already bought it? Your AI assistant can download it for you.

What’s inside

One SKILL.md (the playbook) + one starter template. A preview:

Activity Calendar Chart

When to use

  • You want to see a year of habits, commits, workouts, or sales as a single picture instead of a spreadsheet
  • You need a "year in review" visual that shows streaks, gaps, and seasonal patterns at a glance
  • Your team wants a shared view of activity — support tickets, deploys, posts shipped — across weeks and months
  • You are reporting progress to a client or manager and a heatmap says more than a table of daily counts
  • Your raw data is a list of dated events and you need it turned into something a reader can understand in five seconds

Workflow

  1. Define the unit (input: raw dated events → output: counting rule)
    Decide exactly what one cell means before charting anything: one day = one cell, and the value is a count (workouts done, tickets closed) or a yes/no (published or not). Write the rule down: "one cell = one day, shade = number of focused work sessions that day." Ambiguous counting produces a chart that looks precise and means nothing.
  2. Clean the dates (input: event list → output: tidy daily table)
    Normalize everything to a single daily table: one row per day in the range, zero-filled for days with no activity. Check for the classic traps — timezone shifts, duplicate entries, events dated in the future, and ranges that start mid-week. A heatmap with missing zeros lies: an empty day and an unrecorded day must be distinguishable or the gap pattern is meaningless.
  3. Choose the scale (input: daily table → output: color scale + legend)
    Pick a scale that matches the data: a sequential scale (light to dark) for counts, a binary scale for yes/no. Set the breakpoints from the actual distribution — if most days are 0–2 and a few are 20, a linear scale will wash everything out; use thresholds that separate the common range. The legend must state the unit: "darker = more sessions, max 8/day."
  4. Annotate the story (input: scaled chart → output: annotated chart)
    Add the annotations that turn a grid into a story: label the streaks, mark the gaps with a reason you actually know ("travel", "holiday"), and call out the peaks. Keep annotations short and place them outside the grid where they cannot obscure cells. Never annotate a gap with a reason you are guessing — an unexplained gap is honest; an invented explanation is fabrication.
  5. Check readability (input: annotated chart → output: publish-ready chart)
    Verify the chart at the size it will be read: month labels aligned, weekday labels legible, legend visible, color differences distinguishable without the legend. Check it in grayscale — if the scale collapses when color is removed, adjust the lightness steps. Confirm the total shown matches the source data (sum of cells = total events) before publishing.

Template preview

Activity Calendar Chart — Data & Chart Template

One dataset = one chart. Define the counting rule and clean the dates before shading a single cell.

Dataset: {what is being tracked}

Counting rule (one cell = one day, value = ?): {e.g. "number of focused work sessions that day"} Date range: {start} → {end} Timezone: {timezone used for all dates} Source of events: {where the event list came from}

Data cleaning checklist

[ ] One row per day in range, zero-filled for days with no activity [ ] Timezone shifts checked (no events landing on the wrong day) [ ] Duplicates removed [ ] Future-dated events removed or flagged

Pro — all 471 skills

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