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Aggressive Context Optimizer

by omaression · GitHub ↗ · v1.0.0-alpha · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install aggressive-context-optimizer
Description
Slash OpenClaw token costs and prevent context overflow. Use whenever the user mentions high API costs, expensive tokens, context truncation, context overflo...
README (SKILL.md)

Context Optimizer

Goal: cut input tokens to the minimum that preserves task quality.

Principle: diagnose → apply the single highest-impact fix → re-measure → repeat.

Fast path — use the script

Use the bundled script to audit and apply defaults quickly:

python scripts/context_optimizer.py
python scripts/context_optimizer.py --apply
python scripts/context_optimizer.py --apply --aggressive

The script auto-detects config path, validates after writing, and rolls back on failure. Use --config \x3Cpath> for a specific file.

After running, verify with /status and /usage tokens.

Step 1 — Diagnose (manual path)

If script use is not enough or unavailable, run:

/status
/context detail
/usage tokens

Identify the dominant sink: bootstrap, tool output, memory retrieval, or long-session buildup.

Step 2 — Apply fixes in impact order

Work top-down and stop when usage is acceptable.

Fix 1: Shrink bootstrap files

Trim AGENTS.md, SOUL.md, TOOLS.md, USER.md, MEMORY.md, and heavy skill files. Remove filler and move rarely-needed detail into references read on demand.

Set smaller bootstrap/image limits and related defaults. See references/configs.md for full config examples.

Fix 2: Throttle tool output

Reduce web search/fetch payloads and prefer targeted reads (line ranges/excerpts) over full dumps.

See references/configs.md for full config examples.

Fix 3: Prune stale tool results

Enable context pruning so older, large tool payloads expire automatically while recent turns stay intact.

See references/configs.md for full config examples.

Fix 4: Tighten memory retrieval

Lower recall volume and raise relevance thresholds; keep deduplication and recency bias enabled. Narrow memorySearch.extraPaths if too broad.

See references/configs.md for full config examples.

Fix 5: Session hygiene

Use /compact mid-session, /new for topic shifts, /reset when recovery is unlikely. Enable automatic compaction for sessions that routinely run long.

See references/configs.md for full config examples.

Step 3 — Validate

After each change:

  1. Run openclaw config validate.
  2. Restart gateway if prompted.
  3. Re-check /status and /usage tokens.
  4. Spot-check recall on a representative task.
  5. If quality drops, loosen the most recent change one notch.

Quick-reference: symptom → fix

Symptom Go to
Every turn is expensive, even simple ones Fix 1 (bootstrap)
Cost spikes after searches or file reads Fix 2 (tool output)
Long sessions get slow/truncated Fix 3 (pruning) + Fix 5 (session hygiene)
Memory results feel noisy or irrelevant Fix 4 (memory retrieval)
Screenshots are costly Fix 1, set imageMaxDimensionPx: 512
"Context too large" / truncation errors Fix 5 (/compact or /new), then Fix 3

See references/aggressive-config.md for the full aggressive all-in-one config. See references/commands.md for the full commands cheat sheet.

Usage Guidance
This skill is coherent with its purpose but it will modify your global OpenClaw config. Recommended precautions before using --apply: - Run the script without --apply first to audit (python scripts/context_optimizer.py). - Back up your openclaw.json manually (copy the file) so you can restore it if needed. - Inspect the printed changes the script will make; the script prints SET lines before applying. - Ensure the 'openclaw' CLI on the host is the expected trusted binary (the script relies on its output to find the config path and to validate changes). - Prefer trying changes in a non-production or test agent first, or apply balanced (not aggressive) defaults initially. - If you have concerns about automatic writes, manually edit the config using the examples in references/ to control exactly what changes are made.
Capability Analysis
Type: OpenClaw Skill Name: aggressive-context-optimizer Version: 1.0.0-alpha This skill bundle provides a utility to optimize OpenClaw token usage by adjusting configuration settings. The primary component is a Python script (scripts/context_optimizer.py) that audits and modifies the local openclaw.json file to reduce context overhead. It uses hardcoded subprocess calls to the openclaw CLI for configuration discovery and validation, and includes a rollback mechanism for failed updates. The behavior is transparent, well-documented, and strictly aligned with its stated purpose without any signs of malicious intent or data exfiltration.
Capability Assessment
✓ Purpose & Capability
Name and description match the contained files and instructions. The SKILL.md and bundled Python script both audit and apply OpenClaw configuration changes (bootstrap, memory, tool caps, pruning, compaction). No unrelated binaries, env vars, or external services are requested.
ℹ Instruction Scope
The runtime instructions direct the agent (and the user) to run the included script and OpenClaw CLI commands (/status, /usage, openclaw config validate). The script legitimately reads the openclaw.json, reports findings, and can write tuned settings. This stays within the advertised purpose, but it does perform file I/O on a global config and invokes the 'openclaw' CLI.
✓ Install Mechanism
No install spec; the skill is instruction + source files only. Nothing is downloaded or installed automatically — lowest risk for arbitrary code fetching. The provided Python script runs locally.
✓ Credentials
The skill declares no required environment variables, no credentials, and no config paths up front. The behavior (reading/writing the OpenClaw config) is proportional to its purpose.
ℹ Persistence & Privilege
The skill does not force persistent inclusion (always:false) nor request special platform privileges, but it writes changes to the shared openclaw.json (global agent config). That is expected for a config-tuning tool but is high-impact: changes affect all agents using that config. The script attempts rollback on validation failure but does not make an on-disk backup before writing and relies on re-writing the original in-memory object on error. Also _extract_config_path parses the CLI output for a path — if the 'openclaw config file' output were untrusted or manipulated this could point to an unexpected file path.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install aggressive-context-optimizer
  3. After installation, invoke the skill by name or use /aggressive-context-optimizer
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0-alpha
- Initial alpha release of "context-optimizer" skill. - Aggressive, opinionated tool for slashing OpenClaw token costs and preventing context overflow. - Provides step-by-step diagnosis and targeted fixes, focusing on concrete config changes rather than generic options. - Includes a script for automated optimization and rollback, plus detailed manual optimization guidance. - Quick-reference table links common symptoms to specific fixes for fast troubleshooting.
Metadata
Slug aggressive-context-optimizer
Version 1.0.0-alpha
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Aggressive Context Optimizer?

Slash OpenClaw token costs and prevent context overflow. Use whenever the user mentions high API costs, expensive tokens, context truncation, context overflo... It is an AI Agent Skill for Claude Code / OpenClaw, with 167 downloads so far.

How do I install Aggressive Context Optimizer?

Run "/install aggressive-context-optimizer" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Aggressive Context Optimizer free?

Yes, Aggressive Context Optimizer is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Aggressive Context Optimizer support?

Aggressive Context Optimizer is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Aggressive Context Optimizer?

It is built and maintained by omaression (@omaression); the current version is v1.0.0-alpha.

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