| name | cline-openai-cache-key |
| description | Cline OpenAI native provider sends no prompt_cache_key. Add a stable per-task key so cached_tokens stops being zero. |
| target_harness | Cline |
| target_repo | cline/cline |
| target_files | ["src/core/api/providers/openai-native.ts"] |
| target_commit | 65e9727c (verify current at apply time) |
| estimated_savings | 50-90% input discount on OpenAI calls (currently 0%) |
Cline: add prompt_cache_key to OpenAI native provider
Target
src/core/api/providers/openai-native.ts in cline/cline.
Permalink: https://github.com/cline/cline/blob/65e9727c/src/core/api/providers/openai-native.ts
Symptom
Cline's OpenAI native provider only READS cache stats from responses,
it never enables caching:
const cacheReadTokens = usage?.prompt_tokens_details?.cached_tokens || 0
const cacheWriteTokens = 0
No prompt_cache_key set on the Responses API call, no work done to
verify prefix stability. OpenAI's automatic prefix caching may still
fire if the prefix happens to be byte-stable, but routing is random
across pods so hit rates are low and unpredictable.
Open issue #554 ("OpenAI Prompt Caching appears not enabled?") tracks
user-side confusion. PR #1156 attempted a partial fix but was closed
without merging.
Fix
Set a stable prompt_cache_key derived from the task ID (or a hash of
the system instructions if no task ID is available). NEVER use a
per-request UUID — that's worse than no key.
@@
- const response = await client.responses.create({
+ // Stable cache key: same task = same pod = warm cache.
+ // NEVER use uuid() — random keys force random pod routing and
+ // kill cache hits.
+ const cacheKey = this.options.taskId
+ || this.options.ulid
+ || crypto.createHash("sha256")
+ .update(systemPrompt)
+ .digest("hex")
+ .slice(0, 16)
+
+ const response = await client.responses.create({
model: modelId,
input: messages,
+ prompt_cache_key: `cline:${modelId}:${cacheKey}`,
...
})
If the harness uses the legacy Chat Completions endpoint
(client.chat.completions.create), prompt_cache_key isn't a valid
field there. In that case the only knob is prefix stability — make
sure the system prompt has no per-request timestamps, session IDs, or
randomized content.
Verify
- Start mitmproxy capture as before.
- Configure Cline with an OpenAI model (
gpt-5.4, gpt-5-codex, etc.).
- Send two identical prompts in the same task.
- Inspect captured requests:
prompt_cache_key field present and identical across both
- System prompt bytes identical
- Inspect responses:
- Turn 2
usage.prompt_tokens_details.cached_tokens > 0
- Ratio
cached_tokens / prompt_tokens ≥ 0.5 on a steady-state turn
Background
OpenAI's Responses API uses prompt_cache_key as a pod-routing hint.
Stable key = same pod = warm cache. Per-request UUIDs are the #1
silent killer of OpenAI cache hits.
See docs/gotchas.md #9b for the full
explanation, and docs/concepts/openai.md
"The prompt_cache_key trick".
Reference implementation: Codex CLI uses session thread_id as the
cache key and preserves it across compaction and sub-agents — see
audits/codex-cli.md.
Full audit: audits/cline.md.