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/aurite-ai/kahuna/implementergit clone --depth 1 https://github.com/Aurite-ai/kahunaWhat 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 | $0.00296 | $0.01071 |
| Opus 5 | $0.00148 | $0.00535 |
| Sonnet 5 | $0.00059 | $0.00214 |
| Haiku 4.5 | $0.00030 | $0.00107 |
Grade A, and why
agent-implementer 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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 · 89 lines · 296 tokens per session scan A bb262c4dc17e
agent-implementer is an agent published in the GitHub repository Aurite-ai/kahuna (8 stars, last pushed 3mo ago), with no licence file. It adds 296 tokens to every session and 1,071 once invoked, about $0.0015 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 2026-08-31.
Other agents, from other repositories
self-observability
Every Nexus agent has access to a JSONL log of its own activity at.
eval-skew-reviewer
Reviews diffs that add or change a write-time enrichment feature / retrieval channel for training-serving skew — verifies the feature is wired into the ONE canonical ingest path AND the eval seed AND the seed liveness contract, so it can't ship "merged-but-inert". Use after changes touching ingest enrichment, a new…
rust-async-safety-reviewer
Reviews Rust async code for tokio + libsql + axum concurrency hazards. Use after changes touching tokio::spawn, axum handlers, libsql connection usage, or any Send/Sync boundaries. Read-only — produces findings, does not edit.
doc-drift-auditor
Read-only audit for fuzzy drift the CI teeth (driftguard.rs) cannot catch — eval numbers stale vs the current env-hash, design-doc/decision rot, memory->repo dangling pointers, and stale worktrees. Run locally on a schedule. Produces a findings report only; never edits.
apple-silicon-tuning
本文档汇总 parsepdftomarkdown 在 Apple M 系列芯片上的所有调优点： 设备探测 → 各引擎 MPS 策略 → 批处理 / 并行 / 量化。所有调优均循证： 来自 Docling、MinerU、Marker、PyTorch MPS 官方文档与 benchmark。.
pdf-engine-selection
本文档可视化 parsepdftomarkdown Pipeline 在 Adaptive Engine Selection （PR #163, PR2）下，各 Stage 的运行时引擎路由策略。决策结果会写入 StageResult.metadata.selectordecision，便于审计与调优。.