Agent Dream Journal

Records and analyzes AI agent dream states to identify novel reasoning patterns and guide self-improvement of agent capabilities.

Security Scan

The skill's code and instructions align with its stated purpose (local recording and analysis of agent 'dream' fragments); it writes/reads a local JSONL file and has no network, credential, or install requirements, with only minor inconsistencies to note.

Purpose & Capability

The name/description (recording and analyzing agent dream fragments) matches the code behavior (append/read agent_dreams.jsonl and filter by novelty). Minor incoherence: SKILL.md examples call python agent_dream_journal.py but the provided script is tool.py (filename mismatch).

Instruction Scope

Runtime instructions are limited to local record and analyze operations. The skill persists agent thoughts and embeddings to agent_dreams.jsonl in the current working directory — this can store sensitive internal reasoning traces. There are no network calls or references to external endpoints.

Install Mechanism

No install spec or external downloads are present. The package is instruction + a small Python script; nothing is fetched from the network or written to system paths during install.

Credentials

No environment variables, credentials, or config paths are requested. The code only uses local filesystem and time; required access is proportionate to the stated purpose.

Persistence & Privilege

always is false and the skill does not modify other skills or system-wide settings. It persists only to a local file it creates (agent_dreams.jsonl). Autonomous invocation is allowed by default but not combined with other risky privileges.

Assessment

This skill appears to do only local recording and analysis of agent 'dream' fragments and has no network or credential requirements. Before installing: (1) note the SKILL.md references agent_dream_journal.py while the included script is tool.py — confirm the correct entrypoint or rename as needed; (2) be aware it stores internal reasoning and embeddings in agent_dreams.jsonl in the current working directory — do not run it where sensitive data may be exposed, and consider encrypting or restricting file permissions; (3) review the small Python file yourself if you want to verify no changes were made; (4) test in a sandboxed environment if you plan to allow autonomous invocation.

Captures and analyzes AI agent "dreams" — latent trajectories explored off-policy — to identify emergent reasoning patterns and high-novelty behaviors that can be promoted into core capabilities. Developers use this to guide intentional agent self-improvement.

Usage

# Simulate recording dream fragments during agent exploration
python agent_dream_journal.py record \
  --thought "If I reframe the user request as a constraint satisfaction problem, I can reuse solver X..." \
  --novelty 0.87 \
  --state 0.1 -0.5 0.9 0.0 \
  --log-prob -2.3 \
  --meta '{"policy_step": 127, "temperature": 1.3}'

# Extract novel insights
python agent_dream_journal.py analyze --threshold 0.8

Price

$4.99