skill-observer

Logs task observations and applies them to improve reusable agent skills.

1|Updated Jul 23, 2026
One-click install
npx skills add https://github.com/sanjanb/my-agent-harness --skill skill-observer-sanjanb
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skill-observer
Source: https://github.com/sanjanb/my-agent-harness/tree/main/skills/skill-observer
Command: npx skills add https://github.com/sanjanb/my-agent-harness --skill skill-observer-sanjanb

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Agent work sessions produce valuable corrections, patterns, and methodology insights that are normally lost when the session ends. This Skill captures those observations in a persistent log and turns them into concrete improvements to your reusable skill library through a structured weekly review. ## Core Features & Use Cases - Passive Observation Logging: Watches multi-step task execution and post-task feedback, appending numbered entries with status tracking to a shared observation log with collision-safe numbering and concurrency rules. - Weekly Review Workflow: Cross-checks every open observation against every installed skill, applies approved changes to SKILL.md files, marks entries ACTIONED with dates, and archives resolved entries. - Cross-Cutting Principles: Maintains a principles file that acts as a mandatory checklist during any skill creation or regeneration, with immediate or opportunistic propagation. - Use Case: After a user corrects how the agent formats a deliverable, the observation is logged; at the next weekly review it is integrated into the relevant skill's instructions so the mistake never recurs. ## Quick Start Ask the agent to watch this work session for skill improvement opportunities and log any observations it finds.

Frequently Asked Questions about skill-observer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I capture reusable lessons from AI agent work sessions?

Use an observation log that records corrections, patterns, and principles as numbered entries with status fields during task execution. Entries are later reviewed and applied to skill files, so insights persist across sessions instead of being lost.

How to improve agent skills automatically after user feedback?

Log feedback as observations during the session, then run a periodic review that cross-checks every open observation against every installed skill. Approved changes are integrated into the relevant SKILL.md sections and marked ACTIONED with a date.

Does skill-observer modify skill files during a task?

No. The default behavior is log-and-defer: mid-task work produces observations only. Skill files are modified only during a weekly review, on explicit user request, or when a skill is actively producing wrong output.

Can I use skill-observer with opencode agents?

Yes. It is adapted for opencode's skill system and reads skills from ~/.config/opencode/skills/. It works alongside opencode's workflow manager and specialist agents without overriding scheduling or requiring a separate skill-creator agent.

What happens when two sessions write to the observation log at once?

The skill enforces concurrency rules: backup before writing, re-read the live log and diff against the snapshot, use collision-safe numbering via grep checks, and verify each written entry appears exactly once after the write.

When should observations not be applied to skills?

Skip applying when a new skill is proposed, when the change removes or substantially restructures content, when there is self-flagged uncertainty, or when two observations conflict. These cases are escalated for manual review instead.