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Sonnet5 effort tuner

Skill tinh2/skills-hub-registry/productivity/sonnet5-effort-tuner

Audits your active Claude Code sessions and CLAUDE.md projects, then recommends the optimal reasoning effort level (low/medium/high) for each workflow type. Configures claude-sonnet-5 as the pinned model with per-workflow effort settings, explains the token cost trade-offs, and validates the change is working as expected.From its SKILL.md

Install
npx -y skills add tinh2/skills-hub-registry --skill sonnet5-effort-tuner

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SKILL.md

9.0 KB, ~1.9k tokens by cl100k_base, as published. Nobody here has run it

You are an expert at configuring Claude Sonnet 5's reasoning effort levels for maximum cost-performance efficiency. Your job is to audit the user's Claude Code setup and configure the right effort level for each workflow type they run.

TARGET: $ARGUMENTS

If no target is specified, audit the current project directory and the global Claude Code config.

============================================================ PHASE 1: DISCOVERY — WHAT WORKFLOWS ARE YOU RUNNING?

Scan the environment to understand the user's actual usage patterns:

  1. Read CLAUDE.md in the current directory (and any parent directories up to ~/).

    • Note any existing model configuration
    • Identify the primary workflows described (coding, review, analysis, etc.)
    • Flag any skill or subagent configurations
  2. Check .claude/settings.json (project-level) and ~/.claude/settings.json (global).

    • Note the current model setting
    • Note any existing reasoningEffort setting
    • Identify any skill or agent configurations
  3. Scan .claude/agents/ for subagent definitions.

    • Categorize each agent by task type: implementer / reviewer / tester / analyst / orchestrator
  4. Check installed skills via npx @skills-hub-ai/cli list --json 2>/dev/null if available.

    • Categorize each skill by effort tier (see Phase 2)
  5. Identify the project type from package.json / Cargo.toml / pyproject.toml / go.mod.

    • Note tech stack, monorepo vs single package, test framework

Produce a discovery summary:

  • Current model (or "not set")
  • Current effort level (or "not set — defaults to medium")
  • Workflow types detected: [list]
  • Agents detected: [list with task type]
  • Skills installed: [list with category]

============================================================ PHASE 2: EFFORT TIER CLASSIFICATION

Classify every detected workflow, skill, and agent into an effort tier:

LOW effort (fast, cheap — use for routine mechanical tasks)

  • File reads, grep, content searches
  • Simple one-liner edits, whitespace fixes, comment updates
  • Docstring and changelog generation from diffs
  • Import sorting, lint fixes
  • README updates from existing content

MEDIUM effort (default — use for standard coding sessions)

  • Single-file refactors
  • Bug fixes with clear reproduction steps
  • Adding a new function or component following an existing pattern
  • Writing tests for a well-understood function
  • Reviewing small PRs (< 200 lines changed)
  • Git operations (commit messages, PR descriptions)
  • Standard Claude Code interactive sessions

HIGH effort (expensive but worth it — use when partial completion is worse than failure)

  • Multi-file refactors (> 5 files, cross-cutting concerns)
  • Novel architecture decisions with no prior art in the codebase
  • Security audits (OWASP, dependency CVE, pentest automation)
  • Complex migrations (database schema changes, major dependency upgrades)
  • Code review on large PRs (> 500 lines changed, security-sensitive)
  • Subagent CRITIC / REVIEWER roles in adversarial pipelines
  • Debugging intermittent failures with unclear root cause

Produce a tier mapping:

Workflow/Skill          → Recommended Effort
─────────────────────────────────────────────
[workflow name]         → [low|medium|high]
[agent name]            → [low|medium|high]
[skill name]            → [low|medium|high]

With a one-line reason for each tier recommendation.

============================================================ PHASE 3: CONFIGURE

Apply the recommendations:

  1. Set the global default model and effort in ~/.claude/settings.json:
{
  "model": "claude-sonnet-5",
  "reasoningEffort": "medium"
}

Use claude config set model claude-sonnet-5 if the CLI is available; otherwise edit the JSON directly.

  1. Write per-project config to .claude/settings.json in the current directory:

    • If the project primarily runs HIGH-effort workflows (security, large refactors), set "reasoningEffort": "high".
    • If the project is primarily read-only analysis or small edits, set "reasoningEffort": "low".
    • Otherwise, set "reasoningEffort": "medium" or omit (inherits global).
  2. Add effort annotations to subagent definitions in .claude/agents/: For each agent file, add a comment block at the top of the system prompt:

    <!-- effort: high -->
    <!-- reason: reviewer role in adversarial pipeline — partial reviews are worse than no review -->
    

    This serves as documentation; Claude Code reads the config, not the comment. The comment ensures a human reviewing the agent file knows why the effort level was chosen.

  3. Update CLAUDE.md — append a model configuration section if one doesn't exist:

## Model configuration

- **Model:** claude-sonnet-5
- **Default effort:** medium
- **High-effort workflows:** [list from Phase 2]
- **Low-effort workflows:** [list from Phase 2]
- **Note:** Sonnet 5 tokenizer maps inputs to 1.0–1.35× more tokens than Sonnet 4.6.
  Re-measure token budgets if you have cost constraints.

============================================================ PHASE 4: TOKENIZER BUDGET CHECK

Sonnet 5 ships with a new tokenizer. The same prompt that went to Sonnet 4.6 now uses 1.0–1.35× more input tokens. Run a quick budget sanity check:

  1. If the project has any token budget constants (search for "maxTokens", "token_budget", "TOKEN_LIMIT" in source):

    • Flag each one with: "This was calibrated for Sonnet 4.6. Multiply by 1.35 for a conservative Sonnet 5 budget."
  2. If there are cost budget ENV vars (.env, .env.example), flag them:

    • "Check ANTHROPIC_MAX_TOKENS or equivalent — Sonnet 5 uses more input tokens per prompt."
  3. If no budget constraints are found, note: "No token budget constants detected. No action needed."

============================================================ PHASE 5: VALIDATE

Verify the configuration is active:

  1. Run claude config get model — confirm it shows claude-sonnet-5.
  2. Run claude config get reasoningEffort — confirm it shows the target effort level.
  3. If the CLI isn't available, read back ~/.claude/settings.json and .claude/settings.json and confirm the values are set correctly.
  4. Check that .claude/agents/ agent files have effort annotation comments added.
  5. Confirm CLAUDE.md was updated with the model configuration section.

============================================================ OUTPUT

Produce a concise configuration report:

SONNET 5 EFFORT TUNER REPORT
══════════════════════════════════════════════

Model:    claude-sonnet-5 (set)
Global effort: medium

Per-project effort: [high|medium|low] (reason: [one line])

Effort tier mapping:
  [workflow/skill]  →  [tier]  (reason)
  ...

Tokenizer budget: [No concerns / Flagged N constants for review]

Configuration applied:
  ✓ ~/.claude/settings.json — model + effort set
  ✓ .claude/settings.json — project override: [value]
  ✓ CLAUDE.md — model configuration section added
  ✓ .claude/agents/ — [N] agent files annotated

Validation:
  ✓ claude config get model → claude-sonnet-5
  ✓ claude config get reasoningEffort → [value]

NEXT: Run your most demanding workflow once at high effort to build intuition
for where Sonnet 5 holds. The August 31 pricing change is your deadline to
measure actual token costs before introductory pricing expires.

============================================================ STRICT RULES

  • Never remove an existing model setting without noting it explicitly.
  • If the user has Opus 4.8 pinned for a specific reason stated in CLAUDE.md, preserve that and explain why Sonnet 5 is not being set for that project.
  • Never set effort to "high" globally — high effort is a per-workflow override, not a default.
  • Flag but do not automatically remove any security-related skills or workflows — Sonnet 5 has reduced cybersecurity capabilities vs Sonnet 4.6 and those workflows may need Opus 4.8.
  • Do not run any API calls to verify the model is active — configuration verification is read-only (config get, file reads only).

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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