Agent skill · Workflow & Productivity

ln-002-session-analyzer

Analyzes current or recent session for errors, inefficiencies, and improvement opportunities across skills, tools, hooks, and communication. Use after completing a task or periodically.

majiayu000github.com/majiayu000GitHub ↗
claude-codecan modify filesMIT
Install
npx skills add majiayu000/claude-skill-registry --skill ln-002-session-analyzer-levnikolaevich-claude-code-skills-3 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 11 KB
Bundled scripts: none
Allowed tools: BashReadGlobGrepAgentmcp__hex-line__read_filemcp__hex-line__grep_searchmcp__hex-line__outline
Path: skills/analysis/ln-002-session-analyzer-levnikolaevich-claude-code-skills-3/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

> **Paths:** File paths (`references/`, `../ln-*`) are relative to this skill directory. # Session Analyzer (Standalone Utility) **Type:** Standalone Utility **Category:** 0XX Shared Analyzes a session for errors, inefficiencies, and improvement opportunities. Produces actionable fixes for skills, tools, hooks, and communication style. **Scope:** Single-session deep analysis (10 dimensions). Broader than protocol self-audit, narrower than `/audit-sessions` batch. For skill self-audit: `references/meta_analysis_protocol.md` §7. For multi-day patterns: `/audit-sessions`. --- ## When to Use This Skill - After completing a task — find what went wrong and how to improve - Periodically — audit recent sessions for patterns - After a skill run — analyze how well the skill instructions worked - When debugging tool/hook issues — find root causes in session data --- ## Input `$ARGUMENTS`: - (empty) — analyze current session (conversation context) - `recent` — scan latest JSONL session per agent (Claude, Codex) - `{skill-name}` — focus analysis on that skill's execution within the session `hex-line` is an optional accelerator for large local session logs and repo files. If MCP is unavailable,

What's inside
Steps it walks through
  1. When to Use This Skill
  2. Input
  3. Dimensions
  4. Phase 1: Collect Session Data
  5. Current session (empty args)
  6. Recent sessions (recent arg)
  7. Extract raw data from JSONL session
  8. Extract token statistics from Claude JSONL
  9. Phase 2: Analyze by Dimensions
  10. D1: Tool Errors
  11. D2: Tool Waste
  12. D3: Process Issues
  13. D4: Script Extraction
  14. D5: Hook & Permission
Ships with 1 file
  • metadata.json
Commands it runs
echo "=== LATEST SESSIONS ==="
echo "## Claude"
echo "## Claude Active Sessions"
for f in "$HOME/.claude/sessions"/*.json; do
kill -0 "$PID" 2>/dev/null && echo "  ACTIVE: $(cat "$f")" || echo "  STALE: PID=$PID"
done
echo "## Codex"
echo "=== TOOL CALLS ==="
grep -oE '"name"\s*:\s*"[^"]*"' "$F" 2>/dev/null | sed 's/"name"\s*:\s*"//;s/"//' | sort | uniq -c | sort -rn | head -30
echo "=== ERRORS ==="
More from claude-skill-registry
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About this skill
What does the ln-002-session-analyzer skill do?

Analyzes current or recent session for errors, inefficiencies, and improvement opportunities across skills, tools, hooks, and communication. Use after completing a task or periodically.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill ln-002-session-analyzer-levnikolaevich-claude-code-skills-3 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going