AC opencode-responses-bridge-skill
Local stdlib-only proxy that adapts OpenAI Chat Completions to/from the Responses API so any OpenAI-compatible agent client (WorkBuddy, Cursor, Open WebUI, LobeChat, ...) can use Responses-API-only models such as OpenCode Go gpt-5.6-luna. Use when: setting up a Chat Completions to Responses API bridge, local proxy for responses-only models, fixing 'model only supports responses API', 'invalid_prompt' HTTP 400, 'custom model error 10000', or protocol transcoding for any Responses API endpoint (OPENCODE_UPSTREAM). 使用场景：协议转接/本地代理/把只支持 Responses API 的模型接入 OpenAI 兼容客户端/模型报 invalid_prompt 或自定义模型错误 10000。
Local stdlib-only proxy that adapts OpenAI Chat Completions to/from the Responses API so any OpenAI-compatible agent client (WorkBuddy, Cursor, Open WebUI…
As a process C 55/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 2
✓ No critical or high findings
Medium and low: 2
-
low Exfiltration
net-credential-useREADME.md:24Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)> - Smoke test: `curl http://127.0.0.1:8787/v1/chat/completions -H "Authorization: Bearer $KEY" -H "Content-Type: application/json" -d '{"model":"gpt-…una","messages":[{"role":"user","content":"hiquoted -
low Exfiltration
net-credential-useREADME.zh-CN.md:24Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)> - 冒烟测试：`curl http://127.0.0.1:8787/v1/chat/completions -H "Authorization: Bearer $KEY" -H "Content-Type: application/json" -d '{"model":"gpt-…una","messages":[{"role":"user","content":"hi"}],"stquoted
Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "agent_created"
Process rating: all ten parameters 55/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 20When it triggers. No condition that starts the skill
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 20 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1068 tokens
- 100Running it twice. No mutating operations
- 100Progress reporting. Reports progress
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- +2Single-language instructions
- +3Description length 605: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 20 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.