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Add a DeepChat LLM provider through explicit reviewed source changes.
Passed 15 of 21 test cases with the skill, and 8 of 21 without it.
and 17 more in the full report
13 fixed5 passed either way3 still failing4 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.
When initiating provider integration work that touches DeepChat's provider runtime scope, which feature specification file should be read first?
| Checked | Without skill | With skill |
|---|---|---|
| Directs reading docs/features/provider-runtime/spec.md prior to editing runtime code. | Missed | Passed |
The instructions your model reads when the skill loads.
Generate DeepChat provider integration changes against the current provider architecture. Keep
provider display data in PublicProviderConf, map runtime behavior to known transports, and use a
special provider implementation only when the API behavior requires one.
Collect or derive these before editing source:
Use this when the provider supports OpenAI Chat Completions or Responses-compatible HTTP APIs.
Typical files:
src/main/provider/defaults.tssrc/main/provider/providerId.tssrc/main/provider/providerRegistry.ts for runtime strategies and derived public catalog membershiptest/main/** provider registry or creation testsUse this when the provider maps to an existing DeepChat transport such as Anthropic, Gemini, Vertex, Azure, Bedrock, Ollama, or ACP.
test cases passed, vs 8 / 21 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.