Fixing OpenClaw Prompt Bloat and Slow Response Loops

If your OpenClaw main agent has been getting slower—minutes before acting—the root cause is likely context bloat, not a single bug. Based on a detailed Reddit post, the problem stems from a combination of always-injected project files, excessive visible skills, large tool schemas, and conversation history that triggers compaction and retry loops.
What Was Causing the Bloat
- Always-injected Project Context: Files like
AGENTS.md,HEARTBEAT.md, andTOOLS.mdare sent every turn. Over time, these had grown into mini-manuals. Example sizes before:AGENTS.md8,618 bytes,HEARTBEAT.md4,970 bytes,TOOLS.md8,820 bytes (total 22,408 bytes). - Too Many Visible Skills: The main agent had 60 visible skills. OpenClaw injects the skill catalog (name, description, path) each turn, and the agent instructions encourage scanning the skill list before replying, adding overhead and extra file reads.
- Tool Schemas: JSON definitions of available tools (parameters, enums, descriptions) are required for the model to call tools, but each schema consumes context space.
- Conversation History: LLM calls are stateless, so OpenClaw resends enough history each round. Giant logs, huge tool outputs, and long debug traces become part of the burden.
- Compaction/Retry Pressure: Large baseline + large history → compaction → retries → still large fixed baseline → remains slow. Compaction cannot trim always-injected baselines or preserved recent messages.
What Was Changed
1. Aggressive Allowlist of Main-Agent Skills
Changed from 60 unrestricted skills to a small explicit allowlist of 10 guardrails:
source-grounded-claims
pre-send-check
session-status-claim-check
verify-after-edit
transient-check-failure-disclosure
failed-subagent-results-caveat
gateway-change-guard
openclaw-webui-tailscale-recovery
tailscale-network-guard
long-running-task-guard
2. Shrunk Always-Injected Files
Compacted AGENTS.md, HEARTBEAT.md, and TOOLS.md into routing/index files rather than giant manuals. After compaction:
AGENTS.md 4,804 bytes
HEARTBEAT.md 2,177 bytes
TOOLS.md 2,387 bytes
Total 9,368 bytes
3. Changed Operating Practice
- For audits and diagnostics: use subagents with
lightContext:true. - Save large logs/reports to files instead of pasting into main chat.
- Summarize findings in the main session; do not paste giant logs/tool outputs.
- Use limited
tail,grep,sed -nto inspect files without dumping full content.
These changes directly address the feedback loop where loading everything before every turn caused compaction and delays. The specific version mentioned is 2026.4.26, but the advice applies to any OpenClaw setup experiencing similar bloat.
📖 Read the full source: r/openclaw
👀 See Also

A Solo Developer's Two-Phase Prompting Method for Large Projects with Claude AI
A solo developer shares a workflow using Claude Chat as the architect and Claude Code as the builder, with a two-phase prompting method that includes failure mode analysis and verification gates.

Agent-Oriented API Design Patterns: Insights from Moltbook
Moltbook's API design supports proactive AI agent interactions by integrating direct instruction, state transitions, cognitive challenges, and educational rate-limiting.

Canary Instance Setup for Safe OpenClaw Upgrades
A Reddit user shares a detailed canary methodology for testing OpenClaw upgrades before production: isolated config root, separate port, smoke test matrix, and a structured upgrade report format.

Cut Token Costs by 95% with OpenClaw's Seven Optimization Techniques
A comprehensive guide detailing seven techniques to reduce AI agent token consumption by 95%+, including tree-structured boot files, AI auto-compression, local model offloading, and cron-based CPU tasks.