Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add jianzhichun/emerge/plugin install emergeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jianzhichun/emerge/reflection-deep-dive)<a href="https://agentmods.dev/skills/jianzhichun/emerge/reflection-deep-dive"><img src="https://agentmods.dev/badge/skills/jianzhichun/emerge/reflection-deep-dive/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jianzhichun/emerge/reflection-deep-dive"><img src="https://agentmods.dev/badge/skills/jianzhichun/emerge/reflection-deep-dive.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00031 | $0.00296 |
| Opus 5 | $0.00015 | $0.00148 |
| Sonnet 5 | $0.00006 | $0.00059 |
| Haiku 4.5 | $0.00003 | $0.00030 |
Grade A, and why
reflection-deep-dive scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Reflection Deep Dive
Overview
Use this skill to generate a deeper, cached muscle-memory summary for long-running
or noisy connectors. The cache is consumed by PreCompact, PostCompact, and
UserPromptSubmit hooks when fresh, with automatic fallback to lightweight
reflection when stale.
When to Use
- Connector intent volume is high (for example, 200+ intents).
- Recent failures or rollbacks are increasing.
- The user asks for a full reflection/review of existing flywheel memory.
Command
Run:
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/build_reflection_cache.py"
Optional:
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/build_reflection_cache.py" --max-items 12
Output
The command writes:
~/.emerge/state/reflection-cache/global.json(orEMERGE_STATE_ROOT/reflection-cache/global.json)
with:
generated_at_mssummary_textmeta
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.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 52 lines · 31 tokens per session scan A b0b27d11abed
reflection-deep-dive is a skill published in the GitHub repository jianzhichun/emerge (107 stars, last pushed 4mo ago), licensed MIT. It adds 31 tokens to every session and 296 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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