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 Lingtai-AI/lingtai --skill cache-hit-rategit clone --depth 1 https://github.com/Lingtai-AI/lingtaiWrote 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/lingtai-ai/lingtai/cache-hit-rate)<a href="https://agentmods.dev/skills/lingtai-ai/lingtai/cache-hit-rate"><img src="https://agentmods.dev/badge/skills/lingtai-ai/lingtai/cache-hit-rate/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/lingtai-ai/lingtai/cache-hit-rate"><img src="https://agentmods.dev/badge/skills/lingtai-ai/lingtai/cache-hit-rate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 88 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00152 | $0.02795 |
| Opus 5 | $0.00076 | $0.01398 |
| Sonnet 5 | $0.00030 | $0.00559 |
| Haiku 4.5 | $0.00015 | $0.00280 |
Grade C, and why
dev-guide-cache-hit-rate scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
rm -rf "$T" How it starts
The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cache Hit Rate
Nested lingtai-dev-guide reference. Read this after the top-level router sends
you here when you need to know how well prompt caching has been working
recently for one or more LingTai agents, grounded in the token ledger rather
than guessed.
This pairs with reference/runtime-self-check/SKILL.md §6: when a cache/affinity
fix "should be live," the token ledger is the observable that proves it. This
reference is the measurement; runtime-self-check is the
did-the-object-rebuild diagnosis.
Core principle
A read-only metric. It only reads append-only logs/token_ledger.jsonl
files; it never writes, rotates, or mutates runtime state. Report rates without
pasting private absolute paths into human-facing deliverables — the ledger holds
no secrets, but its parent paths can be private, so generalize to
~/.lingtai-tui/... or <project>/.lingtai/<agent>/.
Data source: the token ledger
Single source of truth: logs/token_ledger.jsonl, one JSON object per LLM call,
written after every call by lingtai/kernel/token_ledger.py
(append_token_entry). Required fields:
| Field | Meaning |
|---|---|
ts |
Call time, UTC, %Y-%m-%dT%H:%M:%SZ (always Z/UTC). |
input |
Total prompt/input tokens for the call. Already includes the cached portion. For the Anthropic/Claude adapters this is raw_input + cache_read + cache_write. |
output |
Output tokens. |
thinking |
Reasoning/thinking tokens. |
cached |
Cache-read input tokens served from the provider prompt cache. A subset of input. |
model, endpoint |
Attribution (which model / base_url produced the tokens). |
Optional tags on some entries: source (main, soul, tc_wake, daemon),
and for daemon-attributed rows em_id / run_id / api_call_id / codex_*.
The kernel normalizes every provider's usage into these same fields before
writing, so the metric is provider-agnostic (verified across gpt-5.5,
mimo-v2.5-pro, deepseek-v4-pro, and the Anthropic adapters). Key invariant,
confirmed in the adapters (lingtai/llm/anthropic/adapter.py,
lingtai/llm/claude_code/adapter.py) and empirically over a full ledger:
0 <= cached <= input, so the hit rate is always in [0, 1].
What ships with it
1 file 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 · 224 lines · 152 tokens per session scan C e0a2978216da
dev-guide-cache-hit-rate is a skill published in the GitHub repository Lingtai-AI/lingtai (670 stars, last pushed yesterday), licensed Apache-2.0. It adds 152 tokens to every session and 2,795 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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