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 dayfinggg/openai-codex-agent-skills --skill application-cache-changegit clone --depth 1 https://github.com/dayfinggg/openai-codex-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/dayfinggg/openai-codex-agent-skills/application-cache-change)<a href="https://agentmods.dev/skills/dayfinggg/openai-codex-agent-skills/application-cache-change"><img src="https://agentmods.dev/badge/skills/dayfinggg/openai-codex-agent-skills/application-cache-change/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/dayfinggg/openai-codex-agent-skills/application-cache-change"><img src="https://agentmods.dev/badge/skills/dayfinggg/openai-codex-agent-skills/application-cache-change.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00042 | $0.00364 |
| Opus 5.5 | $0.00017 | $0.00146 |
| Sonnet 5.5 | $0.00008 | $0.00073 |
| Haiku 4.5 | $0.00004 | $0.00036 |
Grade A, and why
application-cache-change 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 today.
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
Preserve the application's data contract while changing its cache.
- Establish the source of truth, existing cache client and server versions, serialization format, key construction, TTL, and invalidation path. Identify shared keys and all readers and writers.
- Determine which inputs affect the cached value. Include the verified identity and schema dimensions needed for correctness. Do not assume that a namespaced key replaces authorization.
- Trace writes, commits, events, and invalidation. Check races between reading old data, writing new data, and repopulating the cache. Publish invalidation at the appropriate transaction boundary.
- Define behavior for simultaneous misses, partial failures, negative results, and unavailable Redis. Use bounded concurrency or existing atomic primitives where needed. Do not silently make a correctness-critical store optional.
- For locks, verify ownership tokens, expiration, renewal, and atomic release against the actual client and Redis version. A successful SET does not by itself establish a distributed correctness guarantee.
- Check compatibility of serialized values during rolling releases. Avoid clearing all keys or changing global Redis settings to resolve one application's issue.
- Verify miss, hit, update, expiration, concurrent access, and relevant outage paths. Measure origin load and latency only with comparable data and conditions.
Use installed Redis specialists for command, connection, or cluster details. Preserve durability-sensitive data that happens to share the Redis instance.
Consult Redis caching patterns and version-matched client documentation. Finish with evidence that both cached and uncached behavior satisfy the requested contract.
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.
- today First seen · 20 lines · 42 tokens per session scan A 70e44a311566
application-cache-change is a skill published in the GitHub repository dayfinggg/openai-codex-agent-skills (8 stars, last pushed today), licensed MIT. It adds 42 tokens to every session and 364 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-30.
Other skills, from other repositories
bullmq-specialist
BullMQ expert for Redis-backed job queues, background processing, and reliable async execution in Node.js/TypeScript applications. Use when: bullmq, bull queue, redis queue, background job, job queue.
redis-caching-and-pubsub
Architecting high-performance caching strategies, Cache-Aside/Write-Through/Write-Behind patterns, Redis Pub/Sub, Streams, eviction policies, distributed locking (Redlock), and memory optimization. Use when implementing Redis caching, real-time messaging, rate limiting, or session management.
redis-patterns
Redis patterns — caching (cache-aside, write-through), sessions, pub/sub, work queues, distributed locks, data structures (sorted sets, streams, hashes). Covers ioredis, node-redis, Redis 7+. Use when designing Redis usage in Node.js or Python apps.
caching-strategy-helper
Recommend caching strategies and invalidation patterns. Use when a mid-level developer needs performance guidance.
caching
Caching strategies — invalidation, TTL guidelines, cache keys, cache layers, and when not to cache. Use when implementing or reviewing caching logic.
using-redis-token-buckets
Use when adding a bucket-like rate limit backed by Redis: a per-caller budget with burst capacity and continuous refill, a refund path for requests that did no work, or a limit whose Retry-After must be a real wait rather than a window edge. posthog/tokenbucket.py provides an atomic Lua token bucket (consume, refund…