Performance

Skill adelaidasofia/claude-performance/skills/performance

Use this skill when the user says /performance, /digest, asks for a weekly Claude performance report, or wants to review how their Claude Code sessions have been going. Reads JSONL session files from ~/.claude/projects/, computes six effectiveness metrics (activity distribution, one-shot edit rate, subagent turn count, model mix, project allocation, hookify firings), fires diagnostic rules when thresholds breach, and writes behavioral rules into ~/.claude/CLAUDE.md so future sessions adapt. Closes the measurement loop for self-improving AI workflows.From its SKILL.md

Install

npx -y skills add adelaidasofia/claude-performance --skill performance

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

3 stars3 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

5.0 KB, as published. Nobody here has run it

Performance Digest

Measurement layer for Claude Code. Turns session telemetry into prescriptive behavioral rules that Claude reads on the next session start.

A static rule is a wish. A measured rule is a system.

What it does

Every seven days, reads all Claude Code session files from the last week and computes:

Activity distribution: Coding, Exploration, Debugging, Delegation, Planning, Conversation
One-shot edit rate: percentage of file edits that landed without a retry cycle
Agent spawn analysis: how many subagents fired and how many turns each took
Model mix: Opus vs. Sonnet vs. Haiku across all turns
Project allocation: which codebases consumed the most attention
Hookify firings: which behavioral guardrails actually triggered

Then runs six diagnostic rules. When a rule fires, one of two things happens:

Behavioral prescriptions (verbose agents, model routing, low one-shot rate, exploration overhead) are written directly to ~/.claude/CLAUDE.md as permanent rules Claude reads on future session starts.
Investigation prescriptions (recurring errors, hookify repeats) are appended to a Claude To-dos list for the user to review.

Next week the digest re-measures. If the number moved, the rule worked. If it did not, the rule fires again with updated numbers.

Setup

Expected vault layout (follows ai-brain-starter conventions):

<vault-root>/
  ⚙️ Meta/
    Performance/            (reports land here)
    Claude To-dos.md        (prescriptions go here)
    scripts/
      claude_performance_digest.py

Copy scripts/claude_performance_digest.py into your vault at the matching path. The script self-locates via __file__ and expects to sit at <vault>/⚙️ Meta/scripts/.

Optional: edit the PROJECT_LABELS dict at the top of the script to map project directory substrings to clean display labels.

Optional: tune the THRESHOLDS dict. Defaults are calibrated for daily power users.

Usage

Run manually:

python3 "<vault>/⚙️ Meta/scripts/claude_performance_digest.py"

Or schedule weekly. Examples:

Cron (Monday 1am UTC, adjust offset for your timezone):

0 1 * * 1 /usr/bin/python3 "/path/to/vault/⚙️ Meta/scripts/claude_performance_digest.py"

Or via the scheduled-tasks Claude Code plugin, if installed.

Flags

--days N: lookback window (default 7)
--dry-run: print report to stdout, do not write files
--no-report: skip the markdown report, apply prescriptions only

What the output looks like

A dated markdown file at ⚙️ Meta/Performance/weekly-YYYY-MM-DD.md:

# Performance Digest: 2026-04-09 to 2026-04-16

**767 sessions** across 3 projects. 20,822 assistant turns. 773 files edited.

## Activity Distribution
| Category     | Turns | %  |
| Coding       | 1392  | 7% |
| Exploration  | 3062  | 15%|
| Debugging    | 2719  | 13%|
| Delegation   | 324   | 2% |
| Planning     | 2292  | 11%|
| Conversation | 13033 | 52%|

## One-Shot Edit Rate
**83%** (773 files edited, 129 required retries) - on target

## Agent Spawns
**324 agents spawned**. Average turns per agent: **22.0**

## Diagnostics
- **VERBOSE AGENTS**: Avg agent turns is 22.0 (target: <5). Review agent
  prompts: add file paths, expected output format, and clear scope.

## Trending
*Baseline week. No prior data for comparison.*

And a behavioral rule written into ~/.claude/CLAUDE.md:

- [VERBOSE AGENTS fix](performance_verbose_agents.md) | Agent briefings must
  include: specific file paths, expected output format, and scope boundary.
  Target: <8 turns per agent. Current avg: 22.0. (updated 2026-04-16)

Why this exists

Self-improvement by memory alone has a failure mode: a rule gets written, Claude reads it at session start, and under the wrong context the behavior recurs anyway. Without measurement, you cannot tell whether a correction actually worked. You can only tell that you wrote the rule.

This skill closes the loop. Rules come with a number attached. Baseline, target, check-in. Next week the measurement tells you whether the rule is alive, needs revising, or can retire.

Integration

If you use the /weekly skill from claude-insights, the weekly review auto-surfaces the most recent performance digest in its report. The two skills compose: /weekly tells you what happened in your life, /performance tells you what happened in your AI workflow.