Melech Cost

Answer "what did this repo cost me, and which task burned it?" from local agent history. One script does all the work; the agent only runs it and relays the result.

/melech-cost                      # every worktree of this repo, top 8 cards
/melech-cost last 10              # 10 most recent sessions across all worktrees
/melech-cost <worktree>           # one worktree, its top 10 sessions
/melech-cost since 2026-09-01     # only sessions active since a date

Run

Set COST_SCRIPT to scripts/cost.py beside this file (Python 3.9+):

python3 "$COST_SCRIPT" --cwd "$PWD"                        # default view
python3 "$COST_SCRIPT" --cwd "$PWD" --latest 10            # latest 10 sessions across all worktrees
python3 "$COST_SCRIPT" --cwd "$PWD" --worktree feature-a   # focus one worktree
python3 "$COST_SCRIPT" --cwd "$PWD" --since 2026-09-01     # date filter
python3 "$COST_SCRIPT" --cwd "$PWD" --cards 20             # more cards

Relay stdout as-is. It is already Markdown: a repo header, one card per worktree, and a footnote. Do not recompute, round differently, re-sort, or add numbers the script did not print. End with the Full report: path so the user can open every worktree. Do not read the full report unless asked.

Card shape:

### `feature-a` · ~$321
26d ago · 22 sessions + 36 subagents · cursor, claude · mostly `gpt-5.6-sol` (79%)
~394.1M tokens read (98% cached) · ~717k written

| Age | Cost | Read / Write Tokens | Model | Agent | Session | Topic |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1.4d ago | **~$187** | ~250.0M / ~400k | `gpt-5.6-sol` | cursor (+20) | `c747b3dc` | Users locked out after the SSO change… |
| 2d ago | **~$51** | ~80.0M / ~150k | `claude-opus-5-5` | claude | `bf32eff9` | Fix mode keeps editing the wrong file… |

(removed) marks a worktree that no longer exists on disk but still has history. Subagent spend rolls into the session that spawned it.

How it works

Scope: this repo only, every worktree. git worktree list gives the main checkout and every live worktree, wherever it lives (Superset, Cursor, Codex, Claude Code, or a plain sibling folder). A folder that holds this repo's worktrees and no other repo's checkout also counts, so history from removed worktrees in that folder is included. The main checkout's parent folder (for example ~/code) never counts, so sibling repos stay out.

Sources and accuracy:

Agent	Where	Tokens
Claude Code	~/.claude/projects/**/*.jsonl	Exact: logged per message (input, cache write, cache read, output)
Codex	~/.codex/sessions/**, archived_sessions/**	Exact: last token_count total per session
Cursor CLI	~/.cursor/chats/*/<id>/store.db	Estimated: replays the stored ordered conversation
Cursor IDE	state.vscdb + ~/.cursor/projects/*/agent-transcripts	Estimated: replay calibrated against Cursor's own context counter

Pricing. Tokens × list price per model from references/prices.json (dated, per 1M tokens, sourced from Cursor's, Anthropic's, and OpenAI's pricing pages). The first matching rule wins. Unknown models, such as Auto, use a fallback rate, and the footnote says how much that affected. Results are API list-price value. On a subscription, part of it is covered by included usage.

Cursor replay. Cursor stores no billing counters locally, so each session is replayed call by call:

• Every model call re-reads the prior prompt at the cached rate.
• New context (your message and tool results since the last call) is billed at the cache-write or input rate.
• The model's reply is billed at the output rate.
• When the context passes the model's limit, a summary resets it.

The IDE store drops file-read and search results. The replay therefore scales each session to match Cursor's own "context tokens used" breakdown; sessions without that breakdown use the median of this run's sessions, or 2.4× if there are too few samples. Treat Cursor numbers as about ±30–40%. Hidden reasoning tokens and cache misses after idle gaps aren't visible, so they push the true number up.

What it costs to run

The script is plain local Python: no model tokens and no network. It takes about 10–40 seconds depending on history size. The only spend is the agent turn around it: about three model calls that add ~3k new tokens (this skill, the command, and the printed cards) plus ~1k output tokens, on top of re-reading whatever the chat already holds.

Where you run it	Opus 5.5 / GPT-5.6 Sol	Composer 2.5
Inside an existing chat (~50k context)	~$0.05–0.10	~$0.03
As the first message of a fresh chat	~$0.25 (writing the agent's own ~40k system prompt to cache)	~$0.05

More --cards means more output tokens: roughly +$0.01 per 3 extra cards on frontier models.

Boundaries

• Read-only. Cursor CLI stores are copied to a temp dir to read past SQLite locks, then deleted. The only file written is the full report in the system temp dir (or --report PATH).
• History is private. Never upload, publish, or paste it anywhere else without explicit instruction.
• Prices go stale. When a provider changes pricing, update prices.json and its as_of date instead of hand-adjusting printed numbers.
• Agents without a supported local store (for example SQLite-only or encrypted histories) are not counted. Say so if the user expects them.