jianzhichun/emerge/reflection-deep-dive

Claude Code and agent skill by jianzhichun/emerge

Trust tier 2
  • community
LLM review pending
Source check pending

Checking that the SKILL.md file is still in the repository.

Use when connector flywheel history is large/noisy and lightweight reflection is insufficient. Builds a deep reflection cache consumed by hooks.

Install

npx vskill@latest install jianzhichun/emerge/reflection-deep-dive

SKILL.md

Reflection Deep Dive

Overview

Use this skill to generate a deeper, cached muscle-memory summary for long-running or noisy connectors. The cache is consumed by PreCompact, PostCompact, and UserPromptSubmit hooks when fresh, with automatic fallback to lightweight reflection when stale.

When to Use

  • Connector intent volume is high (for example, 200+ intents).
  • Recent failures or rollbacks are increasing.
  • The user asks for a full reflection/review of existing flywheel memory.

Command

Run:

bash
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/build_reflection_cache.py"

Optional:

bash
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/build_reflection_cache.py" --max-items 12

Output

The command writes:

  • ~/.emerge/state/reflection-cache/global.json (or EMERGE_STATE_ROOT/reflection-cache/global.json)

with:

  • generated_at_ms
  • summary_text
  • meta

Notes

  • Hooks prefer this cache while it is fresh (TTL-based).
  • If missing/stale, hooks fall back to local lightweight reflection.
  • The cache path and TTL policy are implementation details in SpanTracker.

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

See the full security report

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

See evaluation results

Source

Popularity

Repository stars
106
Repository forks
13
7-day trend score
23

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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