A developer analyzed Claude Code's per-call token logs and found most cost came from context bloat, mis-inherited model assignments, and repeated file reads — not output verbosity. After four fixes, cost per call fell 40% and subagent spend dropped 77%. The audit and fixes are packaged as a local-only plugin, /scrooge.
A developer analyzed 60 sessions of Claude Code transcripts and built a free open-source profiler to identify token waste. Key findings: a 5,649-line progress doc was read 118 times, and 455 failed tool calls cost ~$201 in retry billing. Caching saved an estimated $15k in API costs.
A developer analyzed 60 sessions of Claude Code transcripts and built a free open-source profiler to identify token waste. Key findings: a 5,649-line progress doc was read 118 times, and 455 failed tool calls cost ~$201 in retry billing. Caching saved an estimated $15k in API costs.
A user priced six months of personal Claude Code transcripts at API rates and found only 20% of spend went to useful work, while 56% covered re-reading the conversation, since every call resends full context. The post offers mitigation settings and promises follow-up before/after numbers.
A user priced six months of personal Claude Code transcripts at API rates and found only 20% of spend went to useful work, while 56% covered re-reading the conversation, since every call resends full context. The post offers mitigation settings and promises follow-up before/after numbers.
A developer building an internal CRM with a multi-agent Claude Code setup tested three plugins aimed at reducing token costs. Analysis showed cache reads, not generated code, drove most token spend, since each turn resends growing context across agents. The post shares which cost-reduction approaches actually worked for practitioners running similar agent loops.
A developer building an internal CRM with a multi-agent Claude Code setup tested three plugins aimed at reducing token costs. Analysis showed cache reads, not generated code, drove most token spend, since each turn resends growing context across agents. The post shares which cost-reduction approaches actually worked for practitioners running similar agent loops.
jev-gate is a Claude Code plugin where a cheap decision model decides whether each task needs Haiku, Sonnet, or Opus, while Sonnet coordinates. It also includes an extractive compactor that replaces auto-compact with a digest plus recent tail without calling a summarizer. It targets Claude Code users wanting to cut token costs, though no savings are proven yet.
jev-gate is a Claude Code plugin where a cheap decision model decides whether each task needs Haiku, Sonnet, or Opus, while Sonnet coordinates. It also includes an extractive compactor that replaces auto-compact with a digest plus recent tail without calling a summarizer. It targets Claude Code users wanting to cut token costs, though no savings are proven yet.
Developers captured raw Claude Code API traffic via local proxy to analyze where tokens and cost go in multi-turn sessions. They identified five cost drivers, including MCP tool schemas consuming 15k-25k input tokens per turn and prompt cache misses that cut the 90% discount. They released an open-source tool, cost-xray, that attributes tokens and costs to individual sources for Claude Code and Codex.
Developers captured raw Claude Code API traffic via local proxy to analyze where tokens and cost go in multi-turn sessions. They identified five cost drivers, including MCP tool schemas consuming 15k-25k input tokens per turn and prompt cache misses that cut the 90% discount. They released an open-source tool, cost-xray, that attributes tokens and costs to individual sources for Claude Code and Codex.