agenthropic

Market Landscape & Selection Bias

The panel’s blind spot

The reports frame the market as “only tiny single-maintainer projects; no Grafana of Claude Code exists.” That framing is broken by popular, MIT-licensed, actively maintained tools the reports never mention:

Missed tool Stars What it is Why it still isn’t the answer
davila7/claude-code-templates 28.4k, MIT Real npx claude-code-templates --analytics live web dashboard; reads ~/.claude JSONL; zero-install; no Docker Flat subagent leaderboard, no DAG; no dollar cost; no persistence (in-memory TTL cache); no Telegram; binds 0.0.0.0
jarrodwatts/claude-hud 26.1k, MIT Literally “see which subagents are running” In-terminal statusline HUD; single-session; not a historical web cockpit
ccusage 16.8k, MIT The de-facto token/cost tool for Claude Code CLI report, not a cockpit — but it undercuts the report’s praise of cast as capturing cost “no one else does”

See projects/claude-code-templates.md for the full deep-dive on the most relevant of these.

Honest reading of the thesis

The market gap that justifies building

No tool in the surveyed set — including the popular ones the panel missed — delivers all of:

  1. Global, persistent, per-instance subagent orchestration DAG (not a session-scoped, render-time-derived tree).
  2. Dollar-cost attribution + delegation-savings, surfaced live.
  3. Telegram alert sink (→ @baev_bot_bot).
  4. Cross-machine / fleet aggregation.
  5. Persistence you own for historical/time-series analysis.

claude-code-templates is the honest baseline to differentiate against: it already nails self-hosted + zero-install + live token attribution. The OPCⁿ moat is precisely the DAG + dollar-cost + persistence + Telegram it lacks. Building agenthropic is justified — but the pitch is “the persistent DAG cockpit,” not “the first Claude Code dashboard.”

Implication for agenthropic