onlyterp/prompt-cache-skills/continue-fix-volatile-msg
Claude Code and agent skill by onlyterp/prompt-cache-skills
- community
Checking that the SKILL.md file is still in the repository.
Ladder-aware Continue Anthropic caching — verify the rolling ladder on the wire, then enable it by default and add TTL coverage.
Install
npx vskill@latest install onlyterp/prompt-cache-skills/continue-fix-volatile-msgSKILL.md
Continue: the "volatile message" is a rolling ladder — verify, don't rip out
REANALYZED 2026-08-28. The previous version of this skillrenamedaddCacheControlToLastTwoUserMessagesto a "last stablemessage" variant. Direct source recon shows Continue ships the samedocumented rolling read/write ladder as Cline/Roo (the helper namepersists inpackages/openai-adapters/src/apis/AnthropicUtils.ts).Applying the old diff would remove a working cache write point.
Target
packages/openai-adapters/src/apis/AnthropicUtils.ts (helper) and its callers in the Anthropic adapter; core/llm/llms/Bedrock.ts (_addCachingToLastTwoUserMessages, cachePoint shape) for the Bedrock path.
What Continue actually does
Same two-breakpoint ladder as Cline/Roo: current user turn = write point, previous user turn = read point. See cline-fix-volatile-msg for the full explanation and the 3-turn wire test. Continue's distinct problem is not the ladder — it's that caching is gated behind config and off by default, so most users get nothing at all, and no TTL extension exists for long sessions.
Step 1 — verify the ladder on the wire (before any change)
Same 3-turn capture as the Cline skill. Continue gates the whole caching path behind cacheBehavior config — if the capture shows zero cache fields in the request at all, fix the config first (next step) and re-capture before judging the ladder.
Step 2 — default-on (the actual money fix)
Continue's cacheBehavior config defaults leave Anthropic caching off for most installs. See continue-enable-defaults — that skill remains the primary win for this harness. The ladder should be verified after defaults are on, never instead.
Step 3 — Bedrock path: verify the cachePoint translation
Continue's Bedrock adapter re-implements caching with cachePoint (not cache_control — gotcha 12). Two checks before trusting it:
- The
cachePointplacement mirrors the ladder (write point on the
current turn, read point on the previous) — same 3-turn wire test through the Bedrock envelope, reading cacheReadInputTokenCount/cacheWriteInputTokenCount.
- The Bedrock model ID in use actually supports cache points (gotcha
13 — the AWS support matrix drifts; verify, don't assume).
Verify (whole skill)
After default-on: request bodies contain cache_control on the ladder positions; 3-turn capture shows the write@N → read@N+1 pattern; Bedrock capture shows the same through cachePoint.
Background
- docs/gotchas.md #12 (cachePoint), #17
(relay field-stripping), #18 (the ladder test).
- Full audit: audits/continue.md.
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/continue-fix-volatile-msg/SKILL.md
Popularity
- Repository stars
- 114
- Repository forks
- 9
- 7-day trend score
- 24
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
Works with
Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.
- Claude Code
- Cursor
- GitHub Copilot
- Windsurf
- Codex
- Gemini CLI
- Cline
- Amp
- Roo Code
- Goose
- Continue
- Kilo Code
- Junie
- Trae
- OpenHands
- Qwen Code
- AI Agent
- Tabnine Chat
- Sourcegraph Cody
- Amazon Q
- Firebase Genkit
- Sweep
- Devin
- Phind
- Mentat
- Claude Desktop
- Aider
- GPT Pilot
- Plandex
- bolt.new
- v0
- Replit Agent
- Anse
- TypingMind
- BetterChatGPT
- LibreChat
- Warp AI
- Pieces
- Fig AI
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