Skill

agent-metrics

Query agent session metrics from hook-hero telemetry data. Use when the user asks about agent activity, efficiency, token spend, tool usage, session history, cost tracking, or productivity metrics. Examples: "how efficient was I this week", "show me my agent metrics", "which repo used the most tokens", "how much did I spend on Claude today".

npx claudepluginhub damahua/claude-code-hook-hero --plugin hook-hero

Tool Access

This skill is limited to using the following tools:

BashReadGrepGlob

Preview

Query and analyze agent session telemetry captured by the hook-hero plugin.

SKILL.md

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Last CommitMar 21, 2026

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Agent Metrics — Hook-Hero Telemetry

Query and analyze agent session telemetry captured by the hook-hero plugin.

Data Location

Session summaries: ~/.claude/hook-hero/sessions/{YYYY-MM-DD}/{session_id}.json Raw events: ~/.claude/hook-hero/events/{YYYY-MM-DD}/{session_id}.jsonl

How to Query

Quick stats for a date range

Use Glob to find session files, Read each one, aggregate in a Bash one-liner:

# Today's sessions
ls ~/.claude/hook-hero/sessions/$(date +%Y-%m-%d)/*.json 2>/dev/null | wc -l

Filter by repo or channel

grep -rl '"repo": "acme/my-app"' ~/.claude/hook-hero/sessions/
grep -rl '"channel": "claude-cli"' ~/.claude/hook-hero/sessions/

Analyze raw events for a session

cat ~/.claude/hook-hero/events/{date}/{session_id}.jsonl

Session Summary Fields

Each JSON file contains:

timing: start_time, end_time, duration_seconds
context: project_path, project_name, directory, cwd, repo, git_remote_url, git_branch, model
tools: total_calls, by_type (map), failures
tokens: input, output, total, cache_read, cache_write, estimated_cost_usd
git: commits_made, branches_touched, files_changed, insertions, deletions, prs_created
prompts: count
subagents: total_spawned, by_type (map), total_duration_ms
compactions: count
worktrees: created, removed
tasks: completed

Insights to Provide

When presenting metrics, highlight:

Total sessions, time, and cost for the period
Which repos consume the most effort/tokens
Channel comparison (claude-code vs claude-cli)
Most-used tools and failure rates
Git productivity (commits, PRs, lines changed per session)
Subagent usage patterns
Context compaction frequency (signals complex sessions)