ClawCodex /advisor Mode: Pair Cheap Worker with Expensive Reviewer to Cut Costs Without Losing Quality
Most agent CLIs force you to pick a single model: Opus delivers great decisions but burns through your budget, while Haiku is cheap but misses critical architectural calls. ClawCodex, an open-source Python port of Claude Code, solves this with an /advisor mode that pairs a cheap worker model with an expensive reviewer model at key decision points.
How It Works
The cheap worker (e.g., haiku-4-5, deepseek-v4-pro) handles the heavy lifting — file reads, edits, test runs. At decision points — before committing to an interpretation, before declaring a task done, or when stuck — the worker pauses and consults a stronger reviewer (e.g., opus-4-7). The reviewer sees the full conversation (every tool call, every result) and returns a short Gaps / Risks / Do-next advice snippet. The worker then continues.
Two Execution Modes
- Server-side (Anthropic 1P): Uses an advisor beta header — one roundtrip, prompt-cache friendly. Both worker and advisor run on Anthropic.
- Client-side (any provider): The worker emits a regular
tool_use, the agent intercepts it and makes a separate call to the configured advisor model. Two roundtrips, but you can mix providers — e.g., DeepSeek worker + Claude Opus advisor, or Gemini worker + GLM advisor.
Configuration & Monitoring
Configuration is a single line in the REPL:
/advisor anthropic:claude-opus-4-7
/advisor deepseek:deepseek-v4-proThe status bar shows worker tokens, advisor tokens, and USD cost separately, so you can see exactly where your spend is going.
Benchmarks & Compatibility
ClawCodex natively supports Anthropic, OpenAI, Gemini, DeepSeek, GLM, Minimax, and OpenRouter. On SWE-bench Verified the agent scores 58.2% with Gemini 2.5 Pro vs. OpenClaude’s 53% under the same harness.
The Hard Part: Prompts
The trickiest engineering challenge was preventing the advisor from simply echoing the worker’s plan back — early versions wasted context on verbatim repeats. The fix was a strict “no first-person voice, no echoes” rule combined with the Gaps / Risks / Do-next template.
Who It's For
Developers using AI coding agents who want Opus-level architectural judgment without paying Opus rates for every single call.
📖 Read the full source: r/openclaw
👀 See Also
Founder Operations in Claude: 19 Reusable Skills for Early-Stage Startups
A founder who exited their first startup published 19 Claude-compatible skill prompts for functions like positioning, pricing, prospecting, and copy — based on their own SOPs and Notion workflows.
Shieldbot: Open-Source Security Scanner Plugin for Claude Code
Shieldbot is an open-source security scanner that runs as a plugin inside Claude Code, integrating six scanners including Semgrep with 5,000+ rules, Bandit, Ruff, detect-secrets, pip-audit, and npm audit. It deduplicates findings and generates prioritized reports with risk scores and code fixes.
Signet: Open-Source Memory Layer for AI Coding Agents Hits 80% F1 on LoCoMo
Signet is an open-source memory system for AI coding agents that achieves 80% F1 on the LoCoMo benchmark, compared to 41% for standard RAG. It extracts memories after each session and injects relevant context before prompts, running locally with SQLite.
Four Free Claude Code Skills for Prompt Clarity, Tutorials, and Bug Hunting
Four Apache 2.0, no-paid-tier Claude Code skills: prompter (prompt rewriting), tutorial-creator (annotated code walkthroughs), bug-echo (post-fix anti-pattern sweep), and bug-prospector (pre-release audit with 7 analysis lenses).