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 skills/jovesun-lab/whetstone/throughlinenpx skills add jovesun-lab/whetstone --skill throughlinegit clone --depth 1 https://github.com/jovesun-lab/whetstoneWrote 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/jovesun-lab/whetstone/throughline)<a href="https://agentmods.dev/skills/jovesun-lab/whetstone/throughline"><img src="https://agentmods.dev/badge/skills/jovesun-lab/whetstone/throughline.svg" alt="Measured on agentmods" 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 | $0.00232 | $0.02994 |
| Opus 5 | $0.00116 | $0.01497 |
| Sonnet 5 | $0.00046 | $0.00599 |
| Haiku 4.5 | $0.00023 | $0.00299 |
Grade A, and why
throughline 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 5d 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 — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Throughline
Keep the thread — Task Track within a session, Handoff across them.
For any AI agent reading this file. The frontmatter uses Claude's skill format; the body is plain markdown. It works the same for Claude, OpenAI, Gemini, Cursor, Cline, Aider, or a local model — paste the body in as a prompt if your platform has no skill system. Assume nothing about your host's capabilities; everything here degrades gracefully (see "Capability-agnostic by design" below).
What this is
Long or multi-agent work fails in two predictable ways, and this skill is two habits that each kill one of them:
- Within a session, reasoning drifts off the goal. You solve a small problem, which surfaces another, which pulls you somewhere adjacent to what you started on. Every step is locally reasonable; together they bend the trajectory. Task Track makes that drift visible by keeping one ⭐️ MAIN goal anchor in front of you.
- Across sessions, the thread is dropped. A fresh run (or a different agent) starts cold, re-derives what was already known, or trusts a stale summary. Handoff carries the thread forward as a plain-text artifact any agent can pick up.
The correlation — the load-bearing point. The ⭐️ MAIN tag is the shared goal anchor. Task Track holds it within a run; Handoff carries it (plus state) across runs. One sentence: don't lose the thread — within a session or between them. The same anti-drift purpose runs through both, which is why they ship together.
When to use
- A long or many-step task at real risk of losing the thread → set up Task Track. (For a short, self-contained task that finishes in one pass, skip it — the overhead isn't worth it.)
- You notice the work has wandered → re-read the ⭐️ MAIN and decide if you've drifted.
- Wrapping up, running low on context, or switching agents → write a Handoff.
- Beginning a session that has a prior handoff → run the Resume flow.
Part 1 — Task Track (the within-session half)
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.
- 5d ago First seen · 200 lines · 232 tokens per session scan A 714b8e1e2a06
throughline is a skill published in the GitHub repository jovesun-lab/whetstone (8 stars, last pushed 14d ago), licensed MIT. It adds 232 tokens to every session and 2,994 once invoked, about $0.0012 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.
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Autonomous recurring agent tasks — converts workflows into persistent background daemons that run on intervals. Stolen from Boris Cherny's Claude Code /loop pattern (2026-03-31).
Send WhatsApp messages, list chats, and search history via wacli (local CLI backed by a synced store at /.wacli). Unpaired? Run the guided connect flow (scripts/guidedconnect.py) from chat — no terminal needed.
obsidian-vault
Voice-inline capture into a Sutando-owned Obsidian vault. The voice agent calls addtovault(kind, body, title?) directly — no core round-trip, no Obsidian plugin required. Filesystem-direct: Obsidian's watcher picks up the change instantly when the vault is open.