fable-cost-reduction-mdc

name

fable-cost-reduction-mdc

description

Use when reducing Claude Code token or quota cost, especially on a high-usage default model like Claude Fable 5. Covers the VERIFIED levers (RTK tool-output minifier, prompt-cache discipline, subagent delegation, low effort) and debunks the NON-levers (1M context has no price premium; MCP schemas are already deferred). Trigger on: save Fable cost, reduce token usage, Claude Code quota, cut usage limits, make Claude Code cheaper, why my plan burns fast.

Fable / Claude Code Cost Reduction

Verified 2026-07-04 against Anthropic's own docs (see Sources). Scope: reduce token and Max-plan quota burn, with a focus on Claude Fable 5 as a worked example of a high-usage default session model (claude-fable-5[1m]). The reasoning applies to any default model choice on a fixed weekly quota plan.

Example baseline this was written against

• Default model: claude-fable-5[1m] (Fable 5, 1M context) on every session.
• effortLevel: low already set globally. The "cap thinking to low" lever is DONE.
• autoCompactThreshold: 0.85.
• Dozens of plugins enabled, several user-scope MCP servers.

NON-levers (do NOT waste time on these; they were already solved by Anthropic)

1. 1M context is NOT more expensive. You are billed for tokens actually SENT, not window size. "A 900k-token request is billed at the same per-token rate as a 9k-token request." Defaulting to [1m] costs nothing extra unless you fill it. Switching to 200K saves $0 on its own.
2. Plugin/MCP tool schemas no longer load every turn. Anthropic now DEFERS tool definitions: only tool NAMES enter context until a tool is actually invoked (~85% overhead cut). Pruning a large plugin list saves far less than it once would. Still worth disabling truly-unused ones via /mcp, but it is a minor lever now.

Real levers, ranked

1. Subagent delegation (biggest structural lever). Subagents bill as THEIR OWN model. Any heavy read / search / multi-step task pushed from a premium-model session to a cheaper-tier subagent costs that cheaper tier's quota, not the premium one. If you keep a model delegation ladder documented anywhere in your own config, this is the lever it's protecting -- the win is in actually USING it, aggressively, during premium-model work.
2. RTK (Rust Token Killer) — MEDIUM RISK, adopt conservatively only. Real, open-source (github.com/rtk-ai/rtk, Apache 2.0, 5.5 months old, 68K stars, 113 contributors, no Nick Saraev/Maker School link confirmed). Runs as a PreToolUse hook that compresses verbose tool output (git status, cargo/npm test, grep, find) BEFORE the model sees it. Self-reported 60-90% reduction (unaudited by any third party). Confirmed, currently-open bugs that produce a SILENTLY WRONG result at exit code 0 (deep-dived 2026-07-04):
   • --ultra-compact flag (the one Claude Code integration guides recommend) has a confirmed silent-data-loss bug on grep (issue #2620) — matches vanish, no error shown.
   • rtk find with flags beyond -name/-iname/-type/-maxdepth silently broadens the query instead of erroring (#2821, filed the same day this was researched).
   • rtk git log silently injects --no-merges unless --merges is passed explicitly, hiding merge commits with zero indication (#1853).
   • rtk diff always exits 0 even when files differ, breaking &&/if conditionals (#2446).
   • Hard caps (20 errors/warnings, 20 list items, 50 inventory) mean anything past the cap is invisible unless the agent notices a tee hint and explicitly re-reads the full file — nothing forces that follow-up.
   • No true "lossless-only" mode exists yet (feature request #1313, open, unresolved). If adopted: exclude rtk find, rtk diff, rtk git log, and --ultra-compact globally via [hooks] exclude_commands in RTK's own config; keep tee.mode = "failures" (default) for full-output recovery; treat as safe only for routine noise (status/lint/test summaries), never for security-critical full-repo greps or pre-merge diff review. Claude Code natively supports the underlying mechanism: PreToolUse can rewrite a Bash command, and PostToolUse updatedToolOutput can rewrite a completed tool's result. Both documented. Can be gated to terminal+Fable-only via env/model-detecting hook (see below).
3. Prompt-cache discipline. Cache READ = 0.1x base input price (90% off). Cache WRITE = 1.25x (5-min TTL) or 2x (1-hour TTL); breaks even after 1 read (5-min) or 2 (1-hour). Min cacheable block 1,024 tokens. Invalidation hierarchy: Tools -> System -> Messages.
   • Editing CLAUDE.md / AGENTS.md / memory mid-session invalidates System+Messages cache -> next turn re-pays FULL price. Batch config edits into a Sonnet session, or do them at session end, not mid-Fable-work.
   • Dynamic content in the system prompt (a timestamp, changing hook text) silently kills the cache every call.
   • Compaction resets history and forces new cache writes for the summarized prefix.
4. Mind the 5-minute cache TTL. Idle gaps > 5 min expire the cache, so resuming re-pays full input price for the whole prefix. This IS the "compact/resume is slow and expensive" symptom. Work in bursts; compact sooner rather than sitting on a huge live context.
5. Trim per-turn hook output under Fable — MINOR win, not major (corrected 2026-07-04). UserPromptSubmit-injected text lands AFTER the cached prefix breakpoint (wrapped as a system-reminder alongside the prompt), so it does NOT invalidate the existing cache — it only adds a small amount of uncached tail per turn. Worth trimming, but it is not the "big cache win" it first looked like. Cache invalidation is driven by Tools/System/Messages changes (item 3 below), not by hook injection size.
6. Prefer CLI over MCP (gh, aws, gcloud) where possible — zero per-tool listing cost.
7. Block huge reads via PreToolUse hook — LOWER RISK, evidence-backed (added 2026-07-04). Claude Code's Read tool has a documented ~2,000-line/~25K-token cap but does NOT reliably self-enforce it (confirmed bug, issue #6910: a 20,010-line file was attempted whole and errored instead of auto-truncating). Worse: Anthropic's own tracker (issue #28783) confirms a SILENT partial-read failure mode — a file can land in an "ambiguous preview" tier where Claude reads only part of it with NO signal that content is missing, and proceeds as if it read everything (instructions/guardrails in the unread tail silently vanish). A PreToolUse hook that gates on file size/line count (warn ~500 lines, deny/redirect above ~2000, forcing Grep + offset/limit instead of a blind full read) is a genuine MITIGATION for this bug, not just a cost lever — it forces an explicit decision point instead of a silent partial read. Reference implementation exists: smart-read in corca-ai/claude-plugins (CWF_READ_WARN_LINES=500, CWF_READ_DENY_LINES=2000, env-configurable). Anthropic declined to build this in natively (issue #22699, "not planned"), so it stays a community/custom hook. Residual risk: if the follow-up targeted search misses the right term, content is still missed — just with an explicit prompt to search rather than a silent gap.
8. Logs → SQLite — BUILT 2026-07-05, gated model+terminal only. hooks/logs_to_sqlite.py fires on Read for files that look like logs (.log extension or common names like app.log/error.log) once they exceed 1000 lines. Parses each line with a generic timestamp + level + message pattern, but ALWAYS keeps the full line verbatim in a raw column too, so an unrecognized log format still ends up fully queryable (just without structured ts/level columns) instead of silently dropping content the way a single-format-only parser would. Cached by file path + size + mtime (an unchanged file is never re-parsed). Denies the raw Read and points at the SQLite db path with example queries. Residual risk carried into the denial message itself: a bad/overly narrow SQL query can silently return zero rows and look like a clean "no errors" answer — the message tells the agent to SELECT COUNT(*) first. Runs ahead of block-huge-reads.py in the same Read hook list; non-log files fall through to that hook untouched. Narrower in scope than a general drop-in converter (only worth it if you're actually reading large logs regularly), but that's a usage-frequency judgment call for you to make, not a technical blocker.
9. Semantic compression of context files (global, NOT model-gateable since files load for all models). Rewrite CLAUDE.md / AGENTS.md / memory for max info density. Helps the first-turn cache write on every model. If your own global context file is near whatever size ceiling you've set for it, this is worth doing globally, separately from any single-model-only work.
10. Advisor-pattern approximation (added 2026-07-07). Anthropic ships a real beta API feature ("advisor tool," advisor-tool-2026-03-01 header) pairing a cheap executor model with a smarter advisor consulted mid-task; their own SWE-bench Pro numbers: ~92% of solo-premium-model quality at ~63% of the price. It is API-only (direct Messages API calls): Claude Code's session/subagent system has no equivalent, so it can't be wired into the app itself. Approximate the same effect with dispatch discipline, no new hooks/infra: instead of one large single-shot Sonnet 5 subagent, break a long/ambiguous task into staged Agent-tool dispatches. Dispatch Sonnet 5 for one bounded chunk, review the checkpoint yourself (the Fable session), send a short course-correction as the next chunk's prompt, repeat. Bulk of tokens still land at Sonnet's rate; Fable's judgment only spends tokens at each checkpoint, not on every step. Only worth the extra round-trips on tasks long/ambiguous enough that mid-task redirection actually changes the outcome, not on a well-scoped single-shot subagent task.
11. Reverse direction: Sonnet session, Fable advisor (added 2026-07-07). Works the other way too, and is actually the closer match to Anthropic's real advisor-tool pattern (a cheap model drives, a smarter model is consulted rarely). Running a Sonnet 5 session as the default driver, dispatch a single Fable 5 subagent via the Agent tool at one key decision point (start of an ambiguous task, a fork in the road, before an architecturally significant choice), then keep executing yourself with that guidance. Bills as one Fable subagent call, not a whole Fable session. Not automatic: ask for it explicitly, or expect it flagged when a task looks significant enough to warrant it.

Terminal + model gating — mechanics confirmed 2026-07-04 (harder than it first looked)

Terminal detection: CLAUDE_CODE_ENTRYPOINT is real (directly observed in a live session: a Claude Desktop app session read claude-desktop) but is NOT in Anthropic's official env-var docs — treat it as moderate-confidence, not a guaranteed-stable API across versions. The documented, official signal is the OTEL attribute app.entrypoint (cli, sdk-cli, sdk-ts, sdk-py, claude-vscode), which is a better-grounded reference point if OTEL is ever wired up. Cheap env-var check inside a hook is still the pragmatic move; just don't treat it as forever-stable.

Model detection is the hard part. NO PreToolUse or UserPromptSubmit hook payload includes the current model — only SessionStart's stdin JSON has a model field, and that value goes STALE the moment /model is used mid-session (confirmed from the official hooks reference). There is no $CLAUDE_MODEL env var. The only way to stay correct after a mid-session model switch is to re-parse the session transcript .jsonl (path given to every hook call as transcript_path) for the most recent model entry, every time the hook fires — not a cheap check, real parsing logic needed in each hook invocation.

Output rewriting, exact shapes (confirmed 2026-07-04):

• PreToolUse rewriting the Bash COMMAND before it runs: {"hookSpecificOutput":{"hookEventName":"PreToolUse","permissionDecision":"allow","updatedInput":{"command":"..."}}}
• PostToolUse rewriting the tool's OUTPUT before the model sees it (the right event for RTK-style compression): {"hookSpecificOutput":{"hookEventName":"PostToolUse","updatedToolOutput":"..."}} — confirmed as of Claude Code v2.1.121+, applies to all tools not just MCP.

Desktop app isn't monolithic: hooks in ~/.claude/settings.json fire in both terminal and the Desktop app's Code tab (confirmed official), but a still-open bug (GitHub #63360) means hooks do NOT fire in Cowork/Dispatch tabs due to a sandbox mismatch. Any terminal-gated hook naturally skips Cowork too, which is fine for this use case but worth knowing.

File compression (item 9) and cache discipline (item 3) are largely global and cannot be gated at all (files load identically regardless of surface or model).

What pairs well with this

• A low effortLevel default for routine work.
• A documented model delegation ladder (premium model -> mid-tier -> cheap-tier, with auto-escalation back up when a cheaper tier struggles) so lever #1 above actually gets used.

Sources

• Claude Code costs docs: code.claude.com/docs/en/costs (MCP deferral, PreToolUse cost example)
• Claude Code hooks: code.claude.com/docs/en/hooks
• Anthropic pricing, Long context section: platform.claude.com/docs/en/about-claude/pricing
• Prompt caching: platform.claude.com/docs/en/build-with-claude/prompt-caching
• RTK: github.com/rtk-ai/rtk