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effort-optimizer

Optimize API costs by adjusting thinking effort per task type.

Skill by JimmyBlanquet

IndexedMIT
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/jimmyblanquet-effort-optimizer

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Optimize API costs by adjusting thinking effort per task type. Use with ralph-agent-teams or ralph-loop to reduce token usage on repetitive tasks while maximizing quality on critical tasks. Categorizes tasks (database, types, api, frontend, tests) and suggests effort levels (high/medium/low).

Use cases: frontend, backend, productivity, agent-building

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
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Install scripts
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Runs as
Python package

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/effort-optimizer

What's inside

Skill name
effort-optimizer
Description
Optimize API costs by adjusting thinking effort per task type. Use with ralph-agent-teams or ralph-loop to reduce token usage on repetitive tasks while maximizing quality on critical tasks. Categorizes tasks (database, types, api, frontend, tests) and suggests effort levels (high/medium/low).
License
MIT
Instructions
162 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Agent Skills spec issues

  • files: referenced but missing: scripts/categorize_task.py

Files (2)

  • SKILL.md
  • analyze_effort.py · scripts/

SKILL.md (first lines)

# Effort Optimizer

Optimize Claude API costs by matching thinking effort to task complexity. Critical tasks get maximum reasoning; repetitive patterns get minimal overhead.

## Task Categories & Effort Levels

| Category | Effort | Tokens | When to Use |
|----------|--------|--------|-------------|
| `database.schema` | high | max | Table design, migrations |
| `database.rls` | high | max | Security policies |
| `database.indexes` | medium | balanced | Performance optimization |
| `types` | medium | balanced | Type definitions |
| `validation` | medium | balanced | Zod schemas |
| `service` | medium | balanced | Business logic |
| `api.routes` | low | minimal | CRUD endpoints |
| `api.actions` | medium | balanced | Server actions |
| `frontend.components` | medium | balanced | React components |
| `frontend.forms` | medium | balanced | Form handling |
| `frontend.pages` | low | minimal | Page composition |
| `tests.unit` | low | minimal | Unit tests |
| `tests.integration` | medium | balanced | Integration tests |
| `tests.e2e` | low | minimal | E2E tests |

## Usage

### Categorize a Sub-Story

Run `scripts/categorize_task.py`:

```bash
python scripts/categorize_task.py "Create RLS policies for posts table"
# Output: { "category": "database.rls", "effort": "high" }
```

### Analyze PRD for Effort Distribution

```bash
python scripts/analyze_effort.py specs/1-posts-crud/prd.json
```

Output:
```json
{
  "summary": {
    "high": 3,
    "medium": 10,
    "low": 6
  },
  "estimated_savings_pct": 35,
  "stories": [
    { "id": "US-000-1", "category": "database.schema", "effort": "high" },
    { "id": "US-001-1", "category": "api.actions", "effort": "medium" }
  ]
}
```

### Generate Frontmatter Suggestions for Skills

Scan all SKILL.md files and suggest `effort` frontmatter values based on each skill's name and description:

```bash
python scripts/analyze_effort.py --generate-frontmatter skills/
```

Output flags mismatches between current and suggested effort levels:
```json
{
  "total_skills": 33,
  "suggested_distribution": { "high": 5, "medium": 20, "low": 8 },
  "mismatches": 2,
  "skills": [
    { "name": "ralph-loop", "current_effort": "high", "suggested_effort": "high" },
    { "name": "speckit-specify", "current_effort": "medium", "suggested_effort": "medium" }
  ]
}
```

## Relationship with Native `effort` Frontmatter

Claude Code now supports `effort` frontmatter natively in SKILL.md files:

```yaml
---
name: my-skill
effort: low   # low | medium | high
---
```

All 33 skills in this project already have this frontmatter set. The two mechanisms are complementary:

| Scope | Mechanism | What It Controls |
|-------|-----------|-----------------|
| **Skill-level** | `effort` frontmatter in SKILL.md | Default thinking effort when Claude executes a skill |
| **Task-level** | effort-optimizer analysis | Per-story effort in a PRD, used by Ralph++ agents |

The frontmatter sets a static default per skill. The effort-optimizer does dynamic analysis: given a PRD with N sub-stories, it categorizes each one and assigns effort levels based on content, enabling cost optimization across a full implementation run.

### Mapping: Task Categories to Frontmatter Values

If you want to set frontmatter for a new skill based on its dominant task type:

| Dominant Category | Suggested Frontmatter `effort` |
|-------------------|-------------------------------|
| `database.schema`, `database.rls` | `high` |
| `service`, `validation`, `api.actions`, `frontend.components`, `frontend.forms`, `tests.integration` | `medium` |
| `api.routes`, `frontend.pages`, `tests.unit`, `tests.e2e` | `low` |

Use `--generate-frontmatter` with `analyze_effort.py` to scan SKILL.md files and suggest effort values (see below).

## Integration with Ralph++

In `ralph-agent-teams`, effort tuning is applied per sub-story:

```python
# In team orchestrator
effort = get_effort_for_story(story)
agent_config = {
    "thinking": effort,  # "high" | "medium" | "low"
    "max_tokens": EFFORT_TOKENS[effort]

From JimmyBlanquet/project-forge, MIT.

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Last commit (this folder)
May 10, 2026 (5 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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effort-optimizer skill. Agent Mart. https://agentmart.dev/skills/jimmyblanquet-effort-optimizer (last updated 2026-10-24)