Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add jianzhichun/emerge --skill emerge-reverse-synthesisgit clone --depth 1 https://github.com/jianzhichun/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/emerge-reverse-synthesis)<a href="https://agentmods.dev/skills/jianzhichun/emerge/emerge-reverse-synthesis"><img src="https://agentmods.dev/badge/skills/jianzhichun/emerge/emerge-reverse-synthesis/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/emerge-reverse-synthesis"><img src="https://agentmods.dev/badge/skills/jianzhichun/emerge/emerge-reverse-synthesis.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 | $0.00043 | $0.00403 |
| Opus 5 | $0.00022 | $0.00201 |
| Sonnet 5 | $0.00009 | $0.00081 |
| Haiku 4.5 | $0.00004 | $0.00040 |
Grade A, and why
emerge-reverse-synthesis 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 11d 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
Emerge Reverse Synthesis
Purpose
Turn repeated raw operator events into a deterministic pipeline candidate. The daemon only packages the job and validates your result.
Inputs
Use the synthesis_job_ready job payload:
normalized_intent: detected operator behaviorevents: raw operator eventsconnector_notesandsynthesis_hintscontext_hint,machine_ids,detector_signals
Rules
- Infer the smallest reusable operation from raw operator events.
- Parameterize operator-specific values through
__args[...]only when they are likely inputs. - Keep stable connector constants literal.
- Assign
__resultfor read mode or__actionfor write mode. - Remove debug code and narration from final code.
- Include a clear
rationaledescribing event evidence and parameter choices. - Validate the candidate through
icc_execwithno_replay=true; write only a pending artifact unless the operator explicitly approves activation.
Output JSON
Use this shape in your working notes and pending artifact rationale:
{
"connector": "desktop_drafting_app",
"mode": "write",
"pipeline_name": "create_room_labels",
"code": "__action = {'ok': True, 'created': []}",
"confidence": 0.82,
"rationale": "raw operator events repeatedly added room labels on the same layer; label text is parameterized via __args.",
"verify_strategy": {
"required_fields": []
}
}
Quality Bar
The generated code is compiled once, then runs without LLM. Treat this as compile-time distillation, not runtime reasoning.
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.
- 11d ago First seen · 51 lines · 43 tokens per session scan A 4065722d298b
emerge-reverse-synthesis is a skill published in the GitHub repository jianzhichun/emerge (107 stars, last pushed 4mo ago), licensed MIT. It adds 43 tokens to every session and 403 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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