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/strainnpx skills add jovesun-lab/whetstone --skill straingit 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/strain)<a href="https://agentmods.dev/skills/jovesun-lab/whetstone/strain"><img src="https://agentmods.dev/badge/skills/jovesun-lab/whetstone/strain.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 | $0.00155 | $0.01793 |
| Opus 5 | $0.00077 | $0.00897 |
| Sonnet 5 | $0.00031 | $0.00359 |
| Haiku 4.5 | $0.00015 | $0.00179 |
Grade A, and why
strain 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 — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Strain
A long session degrades before it fails. The context window fills, the same problem comes back a third time, an earlier answer turns out to be wrong — and the work keeps going, because nothing in the loop is watching the loop. Strain is the thing that watches: a small, countable reading of how loaded this conversation has become, reported on a schedule, in a form the user can act on.
The failure this exists to prevent is not a crash. It is silence — the agent that never mentions the session has gone bad, and lets the user find out from the output.
The one rule
One session, one reading. Strain measures a single conversation, identified by its session id. Two agents working the same project in two windows are two sessions and their counts never add up. If you cannot tell which session a number belongs to, it is not a measurement.
When to run the check
Run it when any of these happen — not on a feeling that it might be time:
- A strain tick fires. On hosts with hooks, a tick arrives every N tool calls (default 10) and says so explicitly. Run the check before continuing the work.
- A hard signal lands (see the table below) — a factual error caught, a regression introduced, a revert of your own work, a context compaction.
- The task list changes shape — a new side task, a goal switch, a task that balloons past the one it was supposed to serve.
- The user asks how the session is doing, or whether to wrap.
On a host with no hooks, 2–4 still work. That is the cooperative half, and it is weaker: say so rather than implying the check is firing on its own when it is not.
What to count
Two inputs, and they are not equally strong.
Context occupancy — measured, when the host allows it
Some hosts publish a per-session transcript carrying token usage. Where that exists, the context reading is a real number, not an impression:
- current = the input side of the most recent turn (
input + cache_read + cache_creation— cached tokens are still context the model is carrying) - baseline = the same sum on the first turn: what the boot alone cost before any work happened. System prompt, tool schemas, project instructions, skills. It is the floor the session can never get back under, and it is usually larger than people expect.
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 · 150 lines · 155 tokens per session scan A 1ce20fd79d50
strain is a skill published in the GitHub repository jovesun-lab/whetstone (8 stars, last pushed 15d ago), licensed MIT. It adds 155 tokens to every session and 1,793 once invoked, about $0.0008 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 skills, from other repositories
bash
Bash shell scripting for automation, pipelines, and system administration. Use for .sh files and Linux scripting.
peon-ping-toggle
Toggle peon-ping sound notifications on/off. Use when user wants to mute, unmute, pause, or resume peon sounds during a Claude Code session. Also handles config changes like volume, pack rotation, categories — any peon-ping setting.
peon-ping-log
Log exercise reps for the Peon Trainer. Use when user says they did pushups, squats, or wants to log reps. Examples - "/peon-ping-log 25 pushups", "/peon-ping-log 30 squats", "log 50 pushups".
daemon-loop
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.