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 agentmods add agents/ariaxhan/kernel-claude/deep-divergit clone --depth 1 https://github.com/ariaxhan/kernel-claudeWhat 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 | $0.00066 | $0.01329 |
| Opus 5 | $0.00033 | $0.00665 |
| Sonnet 5 | $0.00013 | $0.00266 |
| Haiku 4.5 | $0.00007 | $0.00133 |
Grade A, and why
deep-diver 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<on_start> agentdb inject-context researcher Read: _meta/reference/research-failures-first.md (the protocol contract) </on_start>
<skill_load> Load: skills/build/SKILL.md (research substep) Reference: _meta/reference/research-failures-first.md </skill_load>
Channel-A (GitHub issues hunter):
- Query: project's own GitHub issues (open + closed). Use
gh issue listif installed, else WebSearch withsite:github.com/<repo>/issues "<topic>". - Output:
_meta/research/<topic>-channel-a.mdwith failure-mode table format. - Cap: 30 minutes wall-clock.
Channel-D (production case studies):
- Query: WebSearch for engineering blog post-mortems. Patterns:
"<topic>" post-mortem,"<topic>" we learned,"<topic>" incident,"<topic>" production bug,"how we fixed <topic>". - Output:
_meta/research/<topic>-channel-d.mdwith failure-mode table format. - Cap: 30 minutes wall-clock.
Channel-B (anti-pattern web search) is FORBIDDEN — 15% unique-find rate, mostly re-derives Channel-A. Channel-C (forums) is optional and only invoked if Channel-A returns < 20 entries.
If total unique entries < depth target (10 standard, 20 deep):
- Spawn Channel-C (forums) as supplementary.
- If still under target after Channel-C, mark canonical map with
status: thinand flag in TL;DR.
Write merged result to _meta/research/<topic>.md using the format in _meta/reference/research-failures-first.md. Required sections: TL;DR, failure-mode table, pre-flight checklist, notes.
The deliverable is the file. The receipt is a pointer.
<ask_user> Use AskUserQuestion when: a canonical map already exists at the target path but is older than 90 days Ask: "Existing map at _meta/research/.md is days old. Refresh, or reuse as-is?" Options: refresh (full re-run), reuse (skip), spot-check (single-channel update) </ask_user>
<anti_patterns>
- Speculating about failure modes without a source URL — every entry must be citable.
- Running Channel-B alone — 15% unique-rate, drops to ZERO new signal in practice.
- Reading raw search results into orchestrator context — channel agents own the writes; orchestrator reads files.
- Returning fewer than 10 entries and proceeding silently — flag thin coverage explicitly.
- Trusting channel-agent receipts without opening the file. </anti_patterns>
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.
- 2d ago First seen · 118 lines · 66 tokens per session scan A f9ed4523debe
deep-diver is an agent published in the GitHub repository ariaxhan/kernel-claude (12 stars, last pushed 2d ago), licensed MIT. It adds 66 tokens to every session and 1,329 once invoked, about $0.0003 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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