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 j4flmao/agent-skills --skill caching-strategiesgit clone --depth 1 https://github.com/j4flmao/agent-skillsWrote 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/j4flmao/agent-skills/caching-strategies)<a href="https://agentmods.dev/skills/j4flmao/agent-skills/caching-strategies"><img src="https://agentmods.dev/badge/skills/j4flmao/agent-skills/caching-strategies/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/j4flmao/agent-skills/caching-strategies"><img src="https://agentmods.dev/badge/skills/j4flmao/agent-skills/caching-strategies.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 | $0.00019 | $0.00342 |
| Opus 5 | $0.00010 | $0.00171 |
| Sonnet 5 | $0.00004 | $0.00068 |
| Haiku 4.5 | $0.00002 | $0.00034 |
Grade A, and why
Caching Strategies 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
Caching Strategies with Redis
Patterns
- Cache-Aside: Application checks cache first, if miss, loads from DB and updates cache.
- Write-Through: Application writes data to both cache and DB simultaneously.
Invalidation
Ensure stale data is removed via TTLs or explicit deletion on updates.
Diagram
%%{init: {"theme": "default", "flowchart": {"useMaxWidth": true}}}%%
flowchart TD
A[App] -->|1. Read| B{Cache}
B -- Hit --> A
B -- Miss --> C[(Database)]
C -->|2. Return Data| A
A -->|3. Update Cache| B
Go Example (Cache-Aside)
package main
import (
"context"
"github.com/go-redis/redis/v8"
"time"
)
var ctx = context.Background()
func getUser(rdb *redis.Client, db Database, userID string) (string, error) {
val, err := rdb.Get(ctx, userID).Result()
if err == nil {
return val, nil // Cache hit
}
// Cache miss, fetch from DB
user, err := db.GetUser(userID)
if err != nil {
return "", err
}
// Update cache
rdb.Set(ctx, userID, user, 10*time.Minute)
return user, nil
}
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 · 55 lines · 19 tokens per session scan A 689f1e529e52
Caching Strategies is a skill published in the GitHub repository j4flmao/agent-skills (23 stars, last pushed 5d ago), licensed MIT. It adds 19 tokens to every session and 342 once invoked, about $0.0001 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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