introspect

Solid

Agent self-debugging and recovery. Use when stuck in loops, making repeated errors, or quality degrades. Triggers: introspect, self-debug, stuck, loop, why failing.

AI & Automation 155 stars 19 forks Updated 2 days ago MIT

Install

View on GitHub

Quality Score: 93/100

Stars 20%
73
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# Agent Self-Debugging $ARGUMENTS Structured self-analysis for when the agent is stuck, looping, or producing degraded output. --- ## Step 1: Capture Failure State Before diagnosing, gather the facts. Answer each question concisely: | Question | Answer | |----------|--------| | **Last goal/task** | What was the agent trying to accomplish? | | **Actions taken** | List the last 3-5 actions in order | | **Errors or unexpected results** | What went wrong? What was expected vs actual? | | **Attempt count** | How many times has this been tried? | | **Time spent** | Rough estimate of effort so far | --- ## Step 2: Classify the Failure Pattern Identify which pattern matches the current situation: | Pattern | Symptoms | Common Cause | |---------|----------|--------------| | **Loop** | Same action repeated 3+ times | Missing exit condition, wrong approach | | **Drift** | Actions diverge from original goal | Lost context, scope creep | | **Assumption Error** | Working with wrong mental model | Didn't read code, assumed behavior | | **Tool Misuse** | Wrong tool for the job | Grep when should Read, Bash when should Edit | | **Context Overflow** | Forgetting earlier findings | Too much context, need compaction | | **Wrong Abstraction** | Over-engineering simple task | Premature abstraction, YAGNI violation | | **Missing Information** | Can't proceed without data | Need to ask user, read more code | Pick the **single best match**. If multiple apply, pick the root cause pattern (t...

Details

Author
softspark
Repository
softspark/ai-toolkit
Created
2 months ago
Last Updated
2 days ago
Language
Python
License
MIT

Integrates with

Similar Skills

Semantically similar based on skill content — not just same category