agentleFS
Sign inStart free
sasly2048sasly2048/cc-atlas/skills/insights/SKILL.md

insights

Skill1 starsChanged 4 months agoMITView on GitHub

Answer questions about the user's own Claude Code usage history — sessions, hours, streaks, error rate, burnout risk, cost/cache savings, most-used tools, and git commit activity — using the locally installed cc-atlas CLI. Use whenever the user asks about their Claude Code usage, productivity, burnout, streaks, cost, or activity history. Entirely local, no network calls.

14 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

4 rules. 0 are common, 1 is distinctive, and 3 are very specific to this project.

  • 0

    Common

    Most of the 8 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Run cc-atlas sync first. It's safe and fast to re-run — incremental, only re-parsing transcript files that changed since the last sync.

    line 15
  2. Very specific:

    pattern-matching, not a language model: If it replies "I didn't recognize that one," fall back to cc-atlas export --format json and compute …

    line 21
  3. Distinctive:

    Don't try to drive interactive prompts through a tool call.

    line 36
  4. Very specific:

    If cc-atlas sync finds no session data yet, say that plainly rather than presenting a zero as a real answer.

    line 42

“Common” is measured: kept by at least 6 in 10 of the 8 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

cc-atlas usage insights

cc-atlas is a bundled CLI that reads the user's local ~/.claude/projects session transcripts (and any git repos they've configured) into a local SQLite database and computes usage analytics. Nothing leaves the machine — no API calls, no telemetry.

Workflow

  1. Run cc-atlas sync first. It's safe and fast to re-run — incremental, only re-parsing transcript files that changed since the last sync.
  2. For a specific question, prefer cc-atlas ask "<question>". It understands a fixed vocabulary — hours, sessions, error rate, streak, burnout, most-used tool, cost, commits — optionally scoped to a project name and a period (today / this week / this month / all time). It is pattern-matching, not a language model. If it replies "I didn't recognize that one," fall back to cc-atlas export --format json and compute the answer yourself from the returned summary rather than guessing.
  3. For a one-line snapshot (streak, hours today, burnout risk), use cc-atlas status --json.
  4. For a fuller written report, use cc-atlas report <day|week|month> --format markdown.

What this can't answer directly

Cross-project comparison, session replay, team activity, anomaly detection, and goal tracking are interactive-only menu screens — they need a real terminal to select options. If the user wants one of those, tell them to run cc-atlas directly in their own terminal to open the menu. Don't try to drive interactive prompts through a tool call.

Be honest about the numbers

  • Dollar figures use an illustrative blended rate, not Anthropic's actual per-model pricing — say so if you report a cost.
  • If cc-atlas sync finds no session data yet, say that plainly rather than presenting a zero as a real answer.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free