AI Cost Optimization

This dotfiles framework ships an opinionated AI-cost layer designed to keep token spend predictable and low while still using the smartest model for orchestration. Two ideas drive it:

1. Delegate the grunt work. Have the expensive smart model orchestrate, and a cheap fast model do the file reads, edits, and verification. The smart model sees one tool call and the final git diff instead of every intermediate read.
2. Account every call. Every invocation through dot ai <provider> appends a JSONL entry so you can see spend across all providers in one report, not just per-tool dashboards.

Quick reference

dot ai delegate "rename every UserService method that starts with get to fetch"
dot ai cost                # all-time overview
dot ai cost --since 7      # last 7 days
dot ai cost --fails        # only failures + breakdown by failure type

Inside Claude Code: /vibe, /vibe-report, /vibeon, /vibeoff, /vibestatus, /vibe-model-pick, /vibe-model-clear.

The delegator pattern

The pattern comes from pcx-wave/vibe-skill. Mistral Vibe is the default delegate but the same wrapper accepts any model Vibe knows about (DeepSeek V4 Flash, Gemini Flash, etc.).

Cost comparison (May 2026 list prices, blended 85 in / 15 out typical of coding tasks):

Task	Claude Sonnet 4.6 ($3 / $15)	Mistral Medium 3.5 ($1.50 / $7.50)	DeepSeek V4 Flash ($0.14 / $0.28)
1-file tweak (800 tok)	~$0.004	~$0.002	~$0.0001
6-read task (4,800 tok)	~$0.023	~$0.012	~$0.0008
Multi-file refactor (12,000 tok)	~$0.058	~$0.029	~$0.002

Real-world stats from 254 vibe-skill runs over 10 days (May 2026):

	Amount
Actually paid (Mistral Pro prorated + DeepSeek pay-as-you-go)	$10.35
Same workload pay-as-you-go via Mistral API	$46.61
Same workload on Claude Sonnet 4.6	$179.91
Saved vs Claude	$169.56 (17.4× cheaper)

Claude itself contributes ~500-1500 tokens per delegation as orchestration overhead. Even with that overhead the savings dominate for anything beyond a one-line edit.

Pieces deployed by this repo

Component	Source path	Deployed to	Role
vibe skill	defaults/dot_claude/skills/vibe/	~/.claude/skills/vibe/	Claude Code slash commands (/vibe, /vibe-report, etc.)
Delegator binary	defaults/dot_claude/skills/vibe/tools/executable_vibe-delegate	~/.claude/skills/vibe/tools/vibe-delegate	Runs the cheap-model task in a pseudo-TTY, parses streaming JSON, syntax-checks changes, logs the run
Reporter	defaults/dot_claude/skills/vibe/tools/executable_delegate-report	~/.claude/skills/vibe/tools/delegate-report	Reads the JSONL log, prints overview / by-model / by-project / failure tables
CLI shim	scripts/dot/commands/ai.sh	bin/dot ai delegate / bin/dot ai cost	Same delegator + reporter, callable from the terminal without Claude Code
Unified log hook	_ai_log_run in ai.sh	runs inside run_ai_with_context	Appends one JSONL line per dot ai <provider> invocation
Log file	runtime-managed	~/.local/share/delegate-runs.jsonl	One line per run; dot ai cost reads it

State files

File	Owner	Purpose
~/.local/share/delegate-runs.jsonl	runtime	One JSONL entry per AI invocation (vibe + every other provider)
~/.local/share/vibe-auto.flag	/vibeon / /vibeoff	When present, Claude auto-delegates coding tasks to Vibe
~/.local/share/vibe-model.flag	/vibe-model-pick	Override the Vibe model for the next runs; cleared by /vibe-model-clear
~/.vibe/config.toml	user	Vibe's own provider / model configuration

Reading the report

DELEGATE REPORT  2026-05-17 → 2026-05-24
  Runs          : 27  (ok: 25, failed: 2, timeout: 0)
  Success rate  :  92%
  Avg duration  : 18.4s
  Tokens total  : 4,231,082
  Delegate cost : $1.4711
  Claude equiv  : $14.8294
  Saved         : $13.3583  (90% cheaper than Claude)

Claude equiv is what the same workload would have cost on Claude Sonnet 4.6 ($3 / $15 per M tokens, blended at the same in/out ratio). The savings line is the difference. Failure types are broken out per model so you can see which delegate is most reliable for your repo.

Provider coverage

Every provider exposed via dot ai <provider> is logged best-effort. For providers that don't surface token counts in their CLI output, the report still tracks: timestamp, project, exit code, duration, prompt word count. Token / cost fields stay zero for those providers — the report tolerates the gap and aggregates by model regardless.

Providers tracked today:

Provider	Binary	Logged	Tokens surfaced?
Claude Code	claude	yes	no (CLI doesn't expose)
Codex	codex	yes	no
Copilot CLI	copilot	yes	no
Gemini CLI	gemini	yes	no
Goose	goose	yes	no
Kimi CLI	kimi	yes	no
Aider	aider	yes	no
OpenCode	opencode	yes	no
Autohand	autohand	yes	no
Mistral Vibe	vibe	yes	yes (via delegator)
Qwen	qwen	yes	no
ZAI	zai	yes	no
Shell-GPT	sgpt	yes	no
Ollama (local)	ollama	yes	n/a (no cost)
Kiro CLI	kiro-cli	yes	no

Future work

Not implemented yet, ordered roughly by likely impact:

1. Provider-level budget guard. dot ai budget --set 50/month would warn at 80% and refuse new requests at 100% (overridable). Needs per-provider cost estimation hooks beyond what each CLI surfaces today.
2. Prompt response cache. Many coding-helper queries are deterministic ("syntax for X in Y"). A local cache keyed on prompt hash + provider could short-circuit repeat queries.
3. Per-task-class model routing. dot ai delegate --class refactor would pick the cheapest model that meets the quality bar for the task class. Today the user picks the model.
4. Rate-limit awareness. Track API rate limits from response headers, queue requests, surface a dot ai cost --limits view that shows time-to-reset for every provider with an active limit.