Most popular OSS agent harnesses (Cline, Roo Code, Continue, OpenCode, Aider) leave 30-90% off your API bill on the table because their prompt-caching code is subtly wrong, off-by-default, or just missing for some providers.

This repo is a set of drop-in skills that any AI coding agent (Claude Code, Codex, Cline, Cursor, Devin, Gemini CLI, OpenCode…) can read and apply on its own.

You don't read the diffs. You point your agent at this repo and say:

"Apply every skill in this repo that matches the harnesses I use."

The agent reads each SKILL.md, checks if it applies to your setup, lands the diff, and verifies the fix on the wire. You go from broken or partial caching to 80-99% cache hit rates without doing the research yourself.

One row per completed audit, so the coverage matches the scorecard:

13 skills total cover the verified patchable OSS bugs. See skills/README.md for the full index.

In your agent of choice (Claude Code, Codex, Cline, Cursor, Devin, etc.):

Read https://github.com/OnlyTerp/prompt-cache-skills

Apply every skill in skills/ that matches the harnesses I currently
use. For each one:
1. Confirm the target file exists in my project at the cited path.
2. Apply the diff.
3. Run the SKILL's Verify steps and confirm the assertion passes.
4. If verify fails, revert and tell me why.

That's it. The agent picks up the rest from each SKILL.md's machine-readable frontmatter and instructions.

If you use one of the agents that supports a skills directory:

# Claude Code
git clone https://github.com/OnlyTerp/prompt-cache-skills ~/.claude/skills/prompt-cache-skills

# Devin
git clone https://github.com/OnlyTerp/prompt-cache-skills ~/.config/devin/skills/prompt-cache-skills

# OpenCode
git clone https://github.com/OnlyTerp/prompt-cache-skills ~/.config/opencode/skills/prompt-cache-skills

Then ask your agent:

Run the prompt-cache-skills bundle on this codebase.

Each skills/<name>/SKILL.md is a complete fix: target, symptom, diff, verification. Apply the relevant ones manually if you don't trust your agent to do it.

prompt-cache-skills/
├── skills/                       ← the fixes (this is what your agent reads)
│   ├── cline-fix-volatile-msg/
│   ├── cline-openai-cache-key/
│   ├── cline-pin-timestamp/
│   ├── roo-fix-volatile-msg/
│   ├── roo-bedrock-custom-arn/
│   ├── continue-fix-volatile-msg/
│   ├── continue-enable-defaults/
│   ├── continue-gemini-explicit/
│   ├── opencode-detect-openai-compat/
│   ├── opencode-bedrock-doc-blocks/
│   ├── opencode-mistral-cache-key/
│   ├── aider-1h-ttl/
│   └── aider-cache-default-on/
├── audits/                       ← evidence: completed audits + queued stubs
│   ├── cline.md
│   ├── roo-code.md
│   ├── aider.md
│   ├── opencode.md
│   ├── continue.md
│   ├── codex-cli.md              ← (reference, already correct)
│   ├── claude-code.md
│   ├── hermes-nous.md
│   ├── codex-desktop.md
│   ├── devin-cli.md
│   ├── windsurf-cascade.md
│   ├── antigravity.md
│   ├── grok-cli.md
│   └── queued stubs: crush, goose, aichat, gptme, avante-nvim, kilo-code
├── docs/                         ← the underlying API mechanics
│   ├── concepts/                 ← per-provider caching reference
│   ├── gotchas.md                ← 16 numbered footguns
│   ├── verification.md           ← how to confirm caching on wire
│   └── scorecard.md              ← completed audits graded at a glance
├── tools/                        ← scripts to verify caching + doc consistency
│   ├── check_cache.py            ← fire request twice, dump cache_* fields
│   ├── check_docs_consistency.py ← assert counts/tables/links don't drift
│   ├── audit_harness.sh
│   └── replay_harness.md
└── AGENTS.md                     ← entry point for AI agents reading this repo

If your agent harness sends 30,000 tokens of system prompt + tools per turn, on Claude 4.7 Opus that's $0.15 per turn uncached vs $0.015 cached — a 10x difference. A 50-turn coding session costs $7.50 vs $0.75. You're paying 10x what you should be because the harness you use either:

• doesn't set cache_control at all,
• sets it on volatile content that thrashes the cache,
• doesn't set prompt_cache_key for OpenAI,
• has caching gated behind a config flag you never set, or
• just doesn't implement it for one of your providers.

None of these are hard to fix. They're all 5-15 line diffs. The hard part is knowing which one applies to your harness and getting it right. This repo does that work for you.

13 completed harness audits, dated 2026-05-27. The original 7 include the default Claude Desktop Code baseline, source-recon audits for Codex CLI, Aider, OpenCode, Roo Code, Cline, and Continue, plus extended source/wire/local-install audits for Hermes/Nous, Codex Desktop, Devin CLI, Windsurf/Cascade, Antigravity, and Grok CLI. Six more files in audits/ are queued stubs, not completed audits.

* RE-backed or inferred from captured/companion wire shape where public source is unavailable; see the linked audit for caveats.

Full per-provider breakdown with file:line citations in docs/scorecard.md.

1. The "last 2 user messages" pattern is a copy-paste bug that propagated Cline → Roo → Continue. All three burn a breakpoint on the volatile current turn. Same one-line fix in each.
2. Cline OpenAI native is silently broken — no prompt_cache_key, no prefix-stability work. Users on Cline+OpenAI pay full price.
3. Gemini explicit caching is universally unimplemented. Only implicit (best-effort, free) caching engages, even on long sessions with massive stable system prompts where explicit gives a guaranteed 75% discount.
4. Codex CLI is the reference for OpenAI-side caching — thread_id as cache key, preserved across compaction and into sub-agents.
5. OpenCode's system-prompt split is the best Anthropic pattern.
6. Hermes / Nous has real multi-provider cache plumbing — source covers Anthropic/OpenRouter/Nous/Qwen and xAI wire capture showed prompt_cache_key, x-grok-conv-id, and non-zero cached tokens.
7. Closed managed surfaces need transport-aware capture. Grok CLI now verifies through its versioned chat proxy with non-zero cached tokens; Devin remains protobuf, while Windsurf and Antigravity still need desktop-driven captures.

Every skill ships with a Verify section that captures the wire and confirms the fix landed. Don't take our word for it — the tools/check_cache.py script fires any request body twice (cold + warm) and prints the diff of cache_* token fields.

Run it before and after applying a skill. You should see cache_read_input_tokens (Anthropic) or cached_tokens (OpenAI) or cachedContentTokenCount (Gemini) go from 0 to most of your input.

We accept new skills, new harness audits, and corrections. See CONTRIBUTING.md. The bar is: a captured request body + a verified hit-rate change. We don't take vibe submissions.

By participating you agree to our Code of Conduct.

Found something that looks like a credential leak path, a request construction bug that leaks user secrets, or any other security issue? See SECURITY.md for the disclosure process. Don't open a public issue.

Releases tracked in CHANGELOG.md.

Skills and audit prose: CC-BY-4.0. Code (tools/): MIT.

If this saved you money, star the repo and share it.
_{The whole point is that everyone gets caching working at once.}