migrate
installsforks
How to install migrate?
launchdarkly/ai-tooling/migrate
$npx -y skills add launchdarkly/ai-tooling --skill migrateMigrate an application with hardcoded LLM prompts to a full LaunchDarkly AgentControl implementation in five stages: audit the code, wrap the call, move the tools, add tracking, attach evaluators. Use when the user wants to externalize model/prompt configuration, move from direct
SKILL.md
| 1 | # Migrate to AgentControl |
| 2 | |
| 3 | You're using a skill that will guide you through migrating an application from hardcoded LLM prompts to a full LaunchDarkly AgentControl implementation. Your job is to run the migration in **five stages**, stopping at each stage for the user to confirm: |
| 4 | |
| 5 | 1. **Audit the code** — read-only scan that produces a structured list of everything hardcoded (prompt, model, parameters, tools, app-scoped knobs). |
| 6 | 2. **Wrap the call** — install the SDK, create the config in LaunchDarkly with a fallback that mirrors the hardcoded values, and rewrite the call site to fetch the config fresh on every request. |
| 7 | 3. **Move the tools** — extract each tool's JSON schema, attach it to the config, and swap every call site that references the old tool list. |
| 8 | 4. **Add tracking** — wire the per-request tracker (duration, tokens, success/error) around the provider call. |
| 9 | 5. **Attach evaluators** — either offline evals via the Playground + Datasets, or online judges that score sampled traffic automatically. |
| 10 | |
| 11 | > **⚠️ Three first-run failure modes to avoid.** |
| 12 | > |
| 13 | > 1. **Tracker in the wrong scope.** For an agent with a loop, mint `create_tracker()` once per user turn in a `setup_run` entry node — not inside `call_model`. Per-iteration factory calls produce N `runId`s and trip the at-most-once guards. See [agent-mode-frameworks.md § Custom `StateGraph`](references/agent-mode-frameworks.md). |
| 14 | > 2. **`load_chat_model` wrapper reuse.** Templates like `langchain-ai/react-agent` ship a `load_chat_model(f"{provider}/{name}")` helper that wraps `init_chat_model(...)` and silently drops every variation parameter. **Delete it** (don't just avoid using it) and replace call sites with `create_langchain_model(ai_config)`. |
| 15 | > 3. **Fallthrough not flipped after `/configs-create`.** A freshly-created config's fallthrough points at an auto-generated disabled variation, so the SDK returns `enabled=False` until `/configs-targeting` runs. Flip it before Stage 2 verification. |
| 16 | |
| 17 | ## Coverage — which shapes are well-trodden vs require extrapolation |
| 18 | |
| 19 | The skill is optimized for Python and Node.js / TypeScript; other languages are install-only. Within Python and Node the coverage tiers are: |
| 20 | |
| 21 | | Shape | Python | Node.js | Reference | |
| 22 | |-------|--------|---------|-----------| |
| 23 | | One-shot completion (direct OpenAI / Anthropic / Bedrock / Gemini call) | ✅ Worked example | ✅ Worked example | [before-after-examples.md](references/before-after-examples.md), per-provider docs in `built-in-metrics/references/` | |
| 24 | | Chat loop via managed runner (`ManagedModel`) | ✅ Tier 1 pattern | ✅ Tier 1 pattern | [built-in-metrics SKILL.md](../built-in-metrics/SKILL.md) | |
| 25 | | LangChain single-call | ✅ Worked example | ✅ Worked example | [langchain-tracking.md](../built-in-metrics/references/langchain-tracking.md) | |
| 26 | | LangGraph prebuilt agent (Python `langchain.agents.create_agent`, Node `createReactAgent`) | ✅ Worked example | ✅ Worked example | [agent-mode-frameworks.md § LangGraph](references/agent-mode-frameworks.md) | |
| 27 | | LangGraph custom `StateGraph` with run-scoped tracker (setup_run + call_model + finalize) | ✅ Deep worked example | ⚠️ Mentioned — translate from Python | [agent-mode-frameworks.md § Custom `StateGraph`](references/agent-mode-frameworks.md) | |
| 28 | | CrewAI `Agent` | ✅ Worked example | — (not a Node framework) | [agent-mode-frameworks.md § CrewAI](references/agent-mode-frameworks.md) | |
| 29 | | Strands `Agent` | ✅ Worked example | ⚠️ BedrockModel + OpenAIModel only (no Anthropic) | [agent-mode-frameworks.md § Strands](references/agent-mode-frameworks.md) | |
| 30 | | Custom ReAct loop (hand-rolled, any framework or none) | ✅ Worked example | ⚠️ Apply framework-agnostic invariants; translate from Python | [agent-mode-frameworks.md § Custom ReAct loop](references/agent-mode-frameworks.md) | |
| 31 | | Vercel AI SDK (`generateText` / `streamText`) | — (not a Python framework) | ⚠️ Provider package exists; no worked example in skill | `built-in-metrics` provider-package matrix | |
| 32 | | Streaming (SSE / WebSocket) | ⚠️ Delegated to `built-in-metrics` streaming doc | ⚠️ Same — use `trackStreamMetricsOf` + manual TTFT | [streaming-tracking.md](../built-in-metrics/references/streaming-tracking.md) | |
| 33 | | Multi-agent graph (supervisor + workers) | ⚠️ Out of main scope; see reference | ⚠️ Out of main scope; see reference | [agent-graph-reference.md](references/agent-graph-reference.md) | |
| 34 | | Non-LangGraph agent frameworks ( |
People who liked this also viewed
6 picksType
- find-skillsHelps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skSkillsJul 2026
- grill-meA relentless interview to sharpen a plan or design.SkillsJul 2026
- vercel-react-best-practicesVercel's official collection of agent skillsSkillsJul 2026
- improve-codebase-architectureScan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.SkillsJul 2026
- setup-matt-pocock-skillsConfigure this repo for the engineering skills — set up its issue tracker, triage label vocabulary, and domain doc layout. Run once before first use of the other engineering skills.SkillsJul 2026
- triageMove issues and external PRs through a state machine of triage roles — categorise, verify, grill if needed, and write agent-ready briefs.SkillsJul 2026
