Entity Generator

Overview

This skill analyzes the current conversation to extract guidelines that correct the agent's reasoning chain. A good guideline is one that, if known beforehand, would have led to a shorter or more correct execution. Only extract guidelines that fall into one of these three categories:

1. Shortcuts — The agent took unnecessary steps or tried an approach that didn't work before finding the right one. The guideline encodes the direct path so future runs skip the detour.
2. Error prevention — The agent hit an error (tool failure, exception, wrong output) that could be avoided with upfront knowledge. The guideline prevents the error from happening at all.
3. User corrections — The user explicitly corrected, redirected, or stated a preference during the conversation. The guideline captures what the user said so the agent gets it right next time without being told.

Do NOT extract guidelines that are:

• General programming best practices (e.g., "use descriptive variable names")
• Observations about the codebase that can be derived by reading the code
• Restatements of what the agent did successfully without any detour or correction
• Vague advice that wouldn't change the agent's behavior on a concrete task

DO extract guidelines for: environment-specific constraints discovered through errors (e.g., tools not installed, permissions blocked, packages unavailable) — these are not "known" until encountered in a specific environment.

Workflow

Step 1: Analyze the Conversation

Review the conversation and identify:

• Wasted steps: Where did the agent go down a path that turned out to be unnecessary? What would have been the direct route?
• Errors hit: What errors occurred? What knowledge would have prevented them?
• User corrections: Where did the user say "no", "not that", "actually", "I want", or otherwise redirect the agent?

If none of these occurred, output zero entities. Not every conversation produces guidelines.

Step 2: Extract Entities

For each identified shortcut, error, or user correction, create one entity — up to 5 entities; output 0 when none qualify. If more candidates exist, keep only the highest-impact ones.

Principles:

1. State what to do, not what to avoid — frame as proactive recommendations

   • Bad: "Don't use exiftool in sandboxes"
   • Good: "In sandboxed environments, use Python libraries (PIL/Pillow) for image metadata extraction"

2. Triggers should be situational context, not failure conditions

   • Bad trigger: "When apt-get fails"
   • Good trigger: "When working in containerized/sandboxed environments"

3. For shortcuts, recommend the final working approach directly — eliminate trial-and-error by encoding the answer

4. For user corrections, use the user's own words — preserve the specific preference rather than generalizing it

Step 3: Save Entities

Output entities as JSON and pipe to the save script. The type field must always be "guideline" — no other types are accepted.

Method 1: Direct Pipe (Recommended)

echo '{
  "entities": [
    {
      "content": "Proactive entity stating what TO DO",
      "rationale": "Why this approach works better",
      "type": "guideline",
      "trigger": "Situational context when this applies"
    }
  ]
}' | python3 ${CLAUDE_PLUGIN_ROOT}/skills/learn/scripts/save_entities.py

Method 2: From File

cat entities.json | python3 ${CLAUDE_PLUGIN_ROOT}/skills/learn/scripts/save_entities.py

Method 3: Interactive

python3 ${CLAUDE_PLUGIN_ROOT}/skills/learn/scripts/save_entities.py
# Then paste your JSON and press Ctrl+D

The script will:

• Find or create the entities directory (.evolve/entities/)
• Write each entity as a markdown file in {type}/ subdirectories
• Deduplicate against existing entities
• Display confirmation with the total count

Quality Gate

Before saving, review each entity against this checklist:

• Does it fall into one of the three categories (shortcut, error prevention, user correction)?
• Would knowing this guideline beforehand have changed the agent's behavior in a concrete way?
• Is it specific enough that another agent could act on it without further context?

If any answer is no, drop the entity. Zero entities is a valid output.