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 skills add xg-gh-25/SwarmAI --skill s_context-hygienegit clone --depth 1 https://github.com/xg-gh-25/SwarmAIWrote 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/xg-gh-25/swarmai/s_context-hygiene)<a href="https://agentmods.dev/skills/xg-gh-25/swarmai/s_context-hygiene"><img src="https://agentmods.dev/badge/skills/xg-gh-25/swarmai/s_context-hygiene/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/xg-gh-25/swarmai/s_context-hygiene"><img src="https://agentmods.dev/badge/skills/xg-gh-25/swarmai/s_context-hygiene.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00212 | $0.00446 |
| Opus 5 | $0.00106 | $0.00223 |
| Sonnet 5 | $0.00042 | $0.00089 |
| Haiku 4.5 | $0.00021 | $0.00045 |
Grade A, and why
context-hygiene 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 11d 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.
What it actually says
Context Hygiene — Clean & Compress the Context Files
The codified methodology for cleaning / 瘦身 SwarmAI's 12 context files: the
source-routing table (which file's SoT is backend/context/ + needs rebuild vs
.context/ direct vs auto-generated), the cleaning rules (drift numbers, echoed
titles, dated pointers, blow-by-blow→pattern+tell, CJK-in-system-prose), the C046
red-line (never cut a correction's pattern+durable-tell or a principle kernel), and
the read-and-judge method (a read-only scanner surfaces candidates; the agent reads,
judges, and deletes by hand — never a batch auto pass).
Scopes AWAY from context_health_hook (autonomous decay/dedup/regen) and s_persist
(content-type routing for NEW knowledge) — this is the manual SEMANTIC sweep neither does.
→ Read INSTRUCTIONS.md for the full methodology + scripts/scan.py for the read-only scanner.
What ships with it
3 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.
- 11d ago First seen · 20 lines · 212 tokens per session scan A a3bec1d7c213
context-hygiene is a skill published in the GitHub repository xg-gh-25/SwarmAI (44 stars, last pushed 4d ago), licensed MIT. It adds 212 tokens to every session and 446 once invoked, about $0.0011 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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