Measure per-round token usage in godmode loops and log to a TSV file.
npx skills add https://github.com/arbazkhan971/godmode --skill tokens-arbazkhan971
Please help me install this Agent Skill. Skill: tokens Source: https://github.com/arbazkhan971/godmode/tree/main/skills/tokens Command: npx skills add https://github.com/arbazkhan971/godmode --skill tokens-arbazkhan971
Token-budget observability for godmode loops. Measures approximate input + output tokens consumed by each round of the Universal Protocol, appends one row per round to .godmode/token-log.tsv, and emits a terse session-end summary with per-skill breakdown and delta vs. prior sessions. Read-only to source. Inspired by rtk-ai/rtk's gain, discover, and session analytics. Fills the observability gap next to results.tsv (metric deltas) and failures.tsv (discard reasons) — tokens.tsv answers "what did this round COST in context?"
Invoke token-budget observability across your loop by running /godmode:tokens to start per-round token usage tracking.
High-intent search queries and answers about installing and using this skill.
Track token usage per round in automated loops by measuring approximate input and output tokens consumed during each iteration and appending the data to a persistent log file. This records per-round costs for later analysis and optimization.
Token budget observability measures approximate input and output tokens consumed by each round of multi-round orchestration, appends one row per round to a TSV file, and emits a session summary with per-skill breakdowns and deltas versus prior sessions.
Log per-session token metrics to a TSV file by appending one row per round to a persistent token-log file. The log captures per-round usage and computes a session-end summary with per-skill breakdowns and delta versus prior sessions.
Measuring token costs in Unix environments requires a minimal environment with standard Unix tools like awk, wc, date, and gzip. No external dependencies are needed, and the process uses a model-agnostic heuristic to estimate tokens.
Compare token costs across different sessions by computing the delta versus prior sessions. The observability process surfaces trends in token budgets and provides a per-session top-skill breakdown to help optimize future loops.
Measure token usage with a model-agnostic heuristic to estimate tokens independently of specific model APIs. This approach ensures consistent token cost tracking across different models within multi-round orchestration loops.
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