Borrowing it
Nothing to install: this file belongs to cybertronai/SutroYaro. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/cybertronai/SutroYaro/main/.claude/skills/sutro-context/SKILL.mdgit clone --depth 1 https://github.com/cybertronai/SutroYaroWrote 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/cybertronai/sutroyaro/sutro-context)<a href="https://agentmods.dev/skills/cybertronai/sutroyaro/sutro-context"><img src="https://agentmods.dev/badge/skills/cybertronai/sutroyaro/sutro-context.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 5.1 | $0.00034 | $0.00616 |
| Opus 5 | $0.00017 | $0.00308 |
| Sonnet 5 | $0.00007 | $0.00123 |
| Haiku 4.5 | $0.00003 | $0.00062 |
Grade A, and why
sutro-context 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 8d 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sutro Research Context
Load this before doing any research work, running experiments, or reviewing PRs.
Step 1: Read core files
Read these in order. Stop and report if anything is unexpected.
- CLAUDE.md -- project context, current best methods, constraints
- DISCOVERIES.md -- what's proven, what failed, open questions (bottom of file)
- AGENT.md -- machine-executable experiment loop (if running autonomous)
- LAB.md -- experiment protocol, rules (especially rule #9: metric isolation)
Step 2: Check recent activity
Read the last 10 messages from priority Telegram topics:
import json
for f in ['chat-yad.json', 'chat-yaroslav.json', 'challenge-1-sparse-parity.json']:
path = f'src/sparse_parity/telegram_sync/{f}'
try:
msgs = json.load(open(path))
print(f'\n=== {f} (last 3) ===')
for m in msgs[:3]:
print(f" [{m['date'][:10]}] {m['sender']}: {m['text'][:150]}")
except FileNotFoundError:
print(f'{f} not found -- run: bun run sync_telegram.ts')
Check GitHub for open work:
gh pr list --repo cybertronai/SutroYaro --state open
gh issue list --repo cybertronai/SutroYaro --state open
Step 3: Know the current state
| Fact | Value |
|---|---|
| Best method | GF(2) Gaussian elimination, 509us, ARD ~500 |
| Best energy proxy | DMC (Data Movement Complexity, Ding et al.) |
| Experiments done | 33+ (see research/log.jsonl) |
| Open questions | Bottom of DISCOVERIES.md (Q7, Q11-Q13 still open) |
| Next milestone | Energy-efficient nanoGPT training ("final exam") |
| Meeting cadence | Mondays 18:00 at South Park Commons |
Step 4: Before writing code
- Check
research/search_space.yamlfor allowed parameter ranges - Check
research/questions.yamlfor the dependency graph of open questions - Run
checks/env_check.pyto verify environment - Run
checks/baseline_check.pyif baselines may differ on your machine
For contributors using other tools
This context applies regardless of which AI tool you use. The key files are plain markdown and YAML. Read them before starting work. The experiment protocol in LAB.md and AGENT.md defines the loop: hypothesis, code, run, measure, record.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 64 lines · 34 tokens per session scan A b49e40ee58de
sutro-context is a skill published in the GitHub repository cybertronai/SutroYaro (16 stars, last pushed 3mo ago), licensed Unlicense. It adds 34 tokens to every session and 616 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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