# Send Correction Memory to your agent Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually. ## Fast path - 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. ## Suggested prompts ### New install ```text 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 ```text 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. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "correction-memory", "name": "Correction Memory", "source": "tencent", "type": "skill", "category": "AI 智能", "sourceUrl": "https://clawhub.ai/donovanpankratz-del/correction-memory", "canonicalUrl": "https://clawhub.ai/donovanpankratz-del/correction-memory", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/correction-memory", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=correction-memory", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "SKILL.md", "references/correction-tracker-template.js" ], "downloadMode": "redirect", "sourceHealth": { "source": "tencent", "slug": "correction-memory", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-04-30T20:35:58.824Z", "expiresAt": "2026-05-07T20:35:58.824Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=correction-memory", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=correction-memory", "contentDisposition": "attachment; filename=\"correction-memory-1.1.0.zip\"", "redirectLocation": null, "bodySnippet": null, "slug": "correction-memory" }, "scope": "item", "summary": "Item download looks usable.", "detail": "Yavira can redirect you to the upstream package for this item.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/correction-memory" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] } }, "links": { "detailUrl": "https://openagent3.xyz/skills/correction-memory", "downloadUrl": "https://openagent3.xyz/downloads/correction-memory", "agentUrl": "https://openagent3.xyz/skills/correction-memory/agent", "manifestUrl": "https://openagent3.xyz/skills/correction-memory/agent.json", "briefUrl": "https://openagent3.xyz/skills/correction-memory/agent.md" } } ``` ## 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 — logs corrections per agent type to memory/corrections/[AgentType].jsonl Hook into agent-context-loader.js — correction preamble prepended to spawns automatically (if intent-engineering is also installed) ### Step 1 — 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 — Wire agent-context-loader (if using intent-engineering) If lib/agent-context-loader.js is installed (from intent-engineering skill), correction injection is automatic — 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] — [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 — 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 — Full implementation of correction-tracker.js ## Trust - Source: tencent - Verification: Indexed source record - Publisher: donovanpankratz-del - Version: 1.1.0 ## Source health - Status: healthy - Item download looks usable. - Yavira can redirect you to the upstream package for this item. - Health scope: item - Reason: direct_download_ok - Checked at: 2026-04-30T20:35:58.824Z - Expires at: 2026-05-07T20:35:58.824Z - Recommended action: Download for OpenClaw ## Links - [Detail page](https://openagent3.xyz/skills/correction-memory) - [Send to Agent page](https://openagent3.xyz/skills/correction-memory/agent) - [JSON manifest](https://openagent3.xyz/skills/correction-memory/agent.json) - [Markdown brief](https://openagent3.xyz/skills/correction-memory/agent.md) - [Download page](https://openagent3.xyz/downloads/correction-memory)