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/lovstudio/skills/auto-contextnpx skills add lovstudio/skills --skill auto-contextgit clone --depth 1 https://github.com/lovstudio/skillsWhat 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 | $0.00112 | $0.01964 |
| Opus 5 | $0.00056 | $0.00982 |
| Sonnet 5 | $0.00022 | $0.00393 |
| Haiku 4.5 | $0.00011 | $0.00196 |
Grade A, and why
lov-auto-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 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.
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.
AutoContext: Context Operator
Not just a health check — a full operator over everything that shapes context. Three layers by action sensitivity:
| Layer | Examples | Behavior |
|---|---|---|
| Auto-execute | write project memory, update MEMORY.md index |
Do it, report path |
| Confirm-first | edit global agent instructions, edit project CLAUDE.md, overwrite/delete existing memory |
Show diff, wait for "yes" |
| Suggest-only | /fork, /compact, /btw, new session |
Print the exact command to paste |
The harness owns /fork and /compact; this skill cannot invoke them. But
it can do everything else and will.
Auto Mode (via Plugin Hook)
When the skill-publisher plugin is enabled, a UserPromptSubmit hook monitors
transcript size. Above threshold (40+ entries or 150KB+), it injects a
lightweight <auto-context> reminder.
When you see <auto-context>:
| Context State | Action |
|---|---|
| Mostly relevant | Continue, say nothing |
| Some stale noise | Mentally deprioritize, proceed |
| Mostly irrelevant | Suggest /fork or /btw with exact command |
| Near capacity | Suggest /compact or /fork with exact command |
Rules:
- 1 sentence max unless acting.
- If context is fine, say nothing.
- Never auto-fork/auto-compact (can't anyway — harness-only).
- Don't mention "AutoContext" unless asked.
Manual Mode (/lov-auto-context [args])
Two call shapes:
A. Bare call — health report + opportunistic memory write
/lov-auto-context
- Measure — estimate turns, tool calls, distinct topics
- Assess — healthy / getting noisy / polluted / critical
- Scan recent turns for unpersisted feedback/preferences —
if the user stated a rule or preference earlier in the session that
should persist to future conversations (typical trigger phrases:
"从今以后", "以后都", "所有 X 应该 Y", "别再", "记住"), and no
memory was written, auto-execute: write the memory file + update
MEMORY.md. Report the path. - Recommend harness actions if needed (
/fork,/compact,/btw) with the exact command to paste.
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.
- 2d ago First seen · 200 lines · 112 tokens per session scan A 6f3cb48f69e8
lov-auto-context is a skill published in the GitHub repository lovstudio/skills (64 stars, last pushed 3d ago), licensed MIT. It adds 112 tokens to every session and 1,964 once invoked, about $0.0006 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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