Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Correction Memory
Makes agent corrections persistent and reusable. When you override, reject, or correct an agent's output, this skill logs the correction and automatically in...
skill openclawclawhub Free
Makes agent corrections persistent and reusable. When you override, reject, or correct an agent's output, this skill logs the correction and automatically in...
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, references/correction-tracker-template.js
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.1.0
Provenance
- Publisher
- donovanpankratz-del
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
The Problem
When you correct an agent, that correction evaporates after the session. Next time you spawn the same agent type, it makes the same mistake. There's no memory of what you've already taught it.
What This Skill Installs
lib/correction-tracker.js β logs corrections per agent type to memory/corrections/[AgentType].jsonl Hook into agent-context-loader.js β correction preamble prepended to spawns automatically (if intent-engineering is also installed)
Step 1 β Install correction-tracker
cp references/correction-tracker-template.js $OPENCLAW_WORKSPACE/lib/correction-tracker.js Verify it runs: node $OPENCLAW_WORKSPACE/lib/correction-tracker.js
Step 2 β Wire agent-context-loader (if using intent-engineering)
If lib/agent-context-loader.js is installed (from intent-engineering skill), correction injection is automatic β no wiring needed. The loader checks for correction-tracker.js at startup and loads it if present. If you are NOT using intent-engineering, add this to your spawn logic manually: const { buildCorrectionPreamble } = require('./lib/correction-tracker'); const agentType = 'CoderAgent'; // or whatever agent you're spawning const corrections = buildCorrectionPreamble(agentType, workspaceRoot); const fullTask = corrections ? corrections + '\n\n---\n\n' + originalTask : originalTask;
Programmatic
const { logCorrection } = require('./lib/correction-tracker'); logCorrection( 'CoderAgent', // agent type 'Used ESM import instead of require()', // what was wrong 'Always use require() for Node.js stdlib modules', // correct behavior workspaceRoot, { session_channel: 'discord' } // optional metadata );
Via main agent (natural language)
Just tell the main agent: "Note that [AgentType]: [what it did wrong] β [correct behavior]" The main agent will log it programmatically.
How Corrections Are Replayed
On every subagent spawn, agent-context-loader detects the agent type from the task description and prepends: ## Corrections from Previous Sessions The following corrections were logged for CoderAgent. Apply these behaviors: 1. **[2026-03-01] Issue:** Used ESM import instead of require() **Correction:** Always use require() for Node.js stdlib modules Only corrections from the last 30 days are injected. Older corrections expire automatically β stale rules don't accumulate.
Viewing Corrections
# All corrections for an agent type cat $OPENCLAW_WORKSPACE/memory/corrections/CoderAgent.jsonl | jq . # List all agent types with corrections ls $OPENCLAW_WORKSPACE/memory/corrections/ # Count corrections per agent for f in $OPENCLAW_WORKSPACE/memory/corrections/*.jsonl; do echo "$(basename $f .jsonl): $(wc -l < $f) corrections" done
Agent Type Detection
The loader auto-detects agent type from the task description. Default rules: Task keywordsAgent typecode, coder, impl, debugCoderAgentwrit, author, novel, chapterAuthorAgentworld, buildWorldbuilderAgent(anything else)general To add custom agent types, edit detectAgentType() in agent-context-loader.js.
References
references/correction-tracker-template.js β Full implementation of correction-tracker.js
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs1 Scripts
- SKILL.md
- references/correction-tracker-template.js