metricslisted

# metrics — quantify a project's token/cost profile Surfaces the numbers an audit should give you, framed around cost. A multi-stack project (website + game server + client + tools) has **no single number**, so everything is broken down per component. ```bash python -m skills.metrics.cli <project> python -m skills.metrics.cli <project> --porthos reports/<proj>/audit-report.json --json ``` ## What it reports - **LOC** by language and by top-level **component** (with bars). - **Duplicate-function groups** (stdlib AST, free). - **Directive health** + **always-on context cost**: instruction tokens × turns — e.g. a 2.3k-token CLAUDE.md ≈ **70k tokens/session** just re-sending rules. - **Local-routing posture**: backends present → cheap work at 0 cloud tokens. - **Skill-search tokens avoided** by `find_skills` (catalog × ~150 tok). - **The audit's own cost**: `analysis_llm_tokens = 0` — the scans are deterministic Python; only synthesis by the orchestrating model costs tokens. - **Deep audit** summary (health / dead code / secrets) if a Porthos `audit-report.json` is reachable (`.botte/` or `--porthos`). ## Why this framing The headline an audit should produce: *"analysis cost 0 tokens; your always-on instructions cost ~70k/session; local routing can move cheap work to 0 cloud tokens."* That's the number that justifies the toolkit. Exposed via [[llm_mcp]] as the `metrics` tool. Related: [[infra_advisor]] (auto audit), [[directives_audit]], [[skill_finder]], [[bootstrap