How do I install the Deepseek Migration skill?

Run npx skillmds@latest add zhangliang0115/deepseek-migration in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Deepseek Migration safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Deepseek Migration?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Deepseek Migration free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Deepseek Migration?

zhangliang0115 (@zhangliang0115) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Deepseek Migration by zhangliang0115

Name: Deepseek Migration
Author: zhangliang0115

Deepseek Migration

Migrate an existing coding agent or workflow from OpenAI/Anthropic APIs to DeepSeek (deepseek-chat / deepseek-reasoner). Covers endpoint compatibility, environment variables, caching behavior, tool-calling differences, cost levers, and the DeepSeek Harness (dsh) option. Use when a user wants to switch to DeepSeek or cut their LLM bill.

File contents

Migrating an agent setup to DeepSeek

DeepSeek is OpenAI-API-compatible, and Anthropic-compatible endpoints exist for harnesses like Claude Code — so migration is mostly configuration, not rewrites. What actually breaks is rarely the endpoint; it's caching behavior, tool calling, and cost assumptions.

Step 1 — pick the integration path

Current setup	Path
OpenAI SDK / any OpenAI-compatible tool	Point `base_url` to `https://api.deepseek.com`, swap the key, set model ids
Claude Code	Use the documented Anthropic-compatible endpoint (env-var style config)
Want a native harness	DeepSeek Harness (`dsh`): `npx @deepseek-ai/dsh web` — reads `DEEPSEEK_API_KEY`
Editor plugins (Cline etc.)	Custom provider with DeepSeek base URL

Official per-tool guides: https://api-docs.deepseek.com/guides/coding_agents

Model ids: deepseek-chat (fast, cheap, non-thinking) and deepseek-reasoner (chain-of-thought, slower, pricier).

Step 2 — the four things that actually differ

Prefix caching is automatic and prefix-sensitive. DeepSeek bills repeated identical prompt prefixes at a steep discount — but the prefix must be identical. Put the stable system prompt and repo map first; never shuffle timestamps or dynamic content in front of them. A reordering silently kills your cache-hit rate.
deepseek-reasoner thinking tokens bill as output. A reasoner call can cost many multiples of a chat call. Route: routine edits on chat, escalate only hard debugging/design to reasoner (see the deepseek-cost-router skill for the ladder).
Tool calling shape. OpenAI-style function calling works, but weaker harness adherence shows up as missed tool calls. If a tool-heavy workflow degrades, simplify tool schemas (fewer optional params) before blaming the model. Editor-plugin users report Cline handles DeepSeek tool calls better than some alternatives.
Context handling. Long back-and-forth sessions lose the shared prefix and re-bill at full price. For batch/offline work (branch review, doc generation), use dedicated sessions so the prefix stays stable.

Step 3 — verify the migration

# smoke test the endpoint directly (OpenAI-compatible):
curl https://api.deepseek.com/chat/completions \
  -H "Authorization: Bearer $DEEPSEEK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"deepseek-chat","messages":[{"role":"user","content":"ping"}]}'

Then in your agent: one trivial task on deepseek-chat, one hard task on deepseek-reasoner, and check the platform dashboard shows both models and (non-zero) cache-hit tokens. Zero cache hits = your prompt prefix is being mutated before each call — fix ordering.

Rollback and hybrid

The API is compatible enough to keep the old provider configured alongside: route critical-path work to the old provider during the trial week and batch work to DeepSeek. Compare cost per completed task, not per token — reasoner tokens cost more but can replace whole retry loops.

---name: deepseek-migrationdescription: Migrate an existing coding agent or workflow from OpenAI/Anthropic APIs to DeepSeek (deepseek-chat / deepseek-reasoner). Covers endpoint compatibility, environment variables, caching behavior, tool-calling differences, cost levers, and the DeepSeek Harness (dsh) option. Use when a user wants to switch to DeepSeek or cut their LLM bill.---# Migrating an agent setup to DeepSeekDeepSeek is OpenAI-API-compatible, and Anthropic-compatible endpoints existfor harnesses like Claude Code — so migration is mostly configuration, notrewrites. What actually breaks is rarely the endpoint; it's caching behavior,tool calling, and cost assumptions.## Step 1 — pick the integration path| Current setup | Path ||---|---|| OpenAI SDK / any OpenAI-compatible tool | Point `base_url` to `https://api.deepseek.com`, swap the key, set model ids || Claude Code | Use the documented Anthropic-compatible endpoint (env-var style config) || Want a native harness | DeepSeek Harness (`dsh`): `npx @deepseek-ai/dsh web` — reads `DEEPSEEK_API_KEY` || Editor plugins (Cline etc.) | Custom provider with DeepSeek base URL |Official per-tool guides: https://api-docs.deepseek.com/guides/coding_agentsModel ids: **`deepseek-chat`** (fast, cheap, non-thinking) and**`deepseek-reasoner`** (chain-of-thought, slower, pricier).## Step 2 — the four things that actually differ1. **Prefix caching is automatic and prefix-sensitive.** DeepSeek bills repeated identical prompt prefixes at a steep discount — but the prefix must be *identical*. Put the stable system prompt and repo map first; never shuffle timestamps or dynamic content in front of them. A reordering silently kills your cache-hit rate.2. **`deepseek-reasoner` thinking tokens bill as output.** A reasoner call can cost many multiples of a chat call. Route: routine edits on chat, escalate only hard debugging/design to reasoner (see the `deepseek-cost-router` skill for the ladder).3. **Tool calling shape.** OpenAI-style function calling works, but weaker harness adherence shows up as missed tool calls. If a tool-heavy workflow degrades, simplify tool schemas (fewer optional params) before blaming the model. Editor-plugin users report Cline handles DeepSeek tool calls better than some alternatives.4. **Context handling.** Long back-and-forth sessions lose the shared prefix and re-bill at full price. For batch/offline work (branch review, doc generation), use dedicated sessions so the prefix stays stable.## Step 3 — verify the migration```sh# smoke test the endpoint directly (OpenAI-compatible):curl https://api.deepseek.com/chat/completions \ -H "Authorization: Bearer $DEEPSEEK_API_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"deepseek-chat","messages":[{"role":"user","content":"ping"}]}'```Then in your agent: one trivial task on `deepseek-chat`, one hard task on`deepseek-reasoner`, and check the platform dashboard shows both models and(non-zero) cache-hit tokens. Zero cache hits = your prompt prefix is beingmutated before each call — fix ordering.## Rollback and hybridThe API is compatible enough to keep the old provider configured alongside:route critical-path work to the old provider during the trial week and batchwork to DeepSeek. Compare cost per completed task, not per token — reasonertokens cost more but can replace whole retry loops.

Frequently asked questions