From moe-execution
Use for coding, refactoring, or debugging execution on a Mixture-of-Experts (MoE) model (Qwen, GLM, DeepSeek, Mixtral, local MoE), after workflow gating. Stabilize expert routing through role anchors, consistent vocabulary, keyword anchoring, single-domain turns, and structured prompts, then enforce impact-mapping and per-change verification.
How this skill is triggered — by the user, by Claude, or both
Slash command
/moe-execution:moe-executionThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Use this execution order:
Use this execution order:
brainstorming or writing-plans).workflow-gate:impact-analysis first.moe-execution for implementation/refactor/debug execution.moe-execution does not own project bootstrap or policy patching; it owns execution discipline.
Models such as Qwen, GLM, DeepSeek, Mixtral, and many local models are Mixture-of-Experts (MoE). For each token a lightweight router activates a small subset of "experts" (sub-networks). The router keys heavily on surface phrasing — keywords, tokens, n-grams.
Two consequences drive everything in this skill:
Strategy: make routing stable and well-targeted, then externalize global state. You cannot make the experts smarter; you can keep the right experts consistently active.
Pick ONE name for each function, file, variable, type, and concept, and reuse it verbatim
for the entire task. parseConfig stays parseConfig — not "the config parser", "that
loader", "the parsing logic". Each synonym re-routes to different experts and desyncs
behavior. Consistency of tokens matters more than elegance of prose.
Open each request with the concrete technical anchors so the correct experts fire on the
first tokens: language, framework, and the action verb (refactor, debug, test,
implement). "In Go, refactor the auth middleware…" routes better than "Could
you take a look at the middleware and clean it up a bit".
Keep each turn to a single language / module / concern. Mixing unrelated topics (e.g. SQL schema + CSS + shell script) in one turn forces the router to spread across many experts and degrades all of them. Split unrelated work into separate turns.
Small wording changes change behavior, so keep a fixed structure: Context → Task → Constraints → Verify. Reuse the same headings/phrasing across turns. Predictable input shape ⇒ predictable routing.
As context grows, early anchors lose influence and routing drifts. Periodically restate the canonical names and the current goal in one short line before continuing. If drift is bad (model contradicts earlier decisions), start a fresh turn and reload state from a file.
Code tasks want low temperature (≈0.0–0.3). If you control sampling, set it low. If you don't (fixed endpoint), compensate by being more explicit and structured — explicitness reduces the router's freedom to wander.
The router keys strongly on role/persona tokens. A precise role pulls in better-targeted experts than generic "assistant". Rules:
[role] + [language/framework] + [verb] →
e.g. "As a security reviewer, audit this Express route for injection."Canonical roles for software-dev concerns (use the name verbatim, per A1):
| Concern | Role anchor | Stack with |
|---|---|---|
| System/architecture design | senior software architect | the domain + "design", "tradeoffs" |
| Feature implementation | senior engineer | framework + "implement" |
| Refactoring | refactoring engineer | language + target symbol name |
| Debugging | debugging engineer | error text + "root cause" |
| Testing | test engineer (TDD) | framework + "failing test first" |
| Code review | staff code reviewer | "bugs, correctness only" |
| Security | application security reviewer | "injection / authz / secrets" |
| Performance | performance engineer | "profile", "hot path", complexity |
| Concurrency | concurrency engineer | "races", "locks", "goroutines/async" |
| API design | API designer | "REST/gRPC", "contract", "versioning" |
| Database / SQL | database engineer | engine (Postgres…) + "query/schema/index" |
| Frontend / UI | frontend engineer | framework + "accessibility/responsive" |
| DevOps / CI | platform/DevOps engineer | tool (Docker, CI) + "pipeline" |
| Types/generics | type-system engineer | language + "generics/inference" |
Don't invent elaborate personas — a 2–4 word precise role is the sweet spot. Longer backstories add noise tokens that can mis-route.
After pre-change gating is complete, keep a working MAP of impacted dependents for execution safety.
workflow-gate:impact-analysis first and use that blast-radius report as baseline.grep the canonical name across the whole repo, not just the open file.todos) before implementation steps fan out.For multi-file work, write the impact MAP + an ordered list of tiny steps to plan.md
(session folder) or todos. The file is the global memory the model cannot hold itself.
Each step should name exactly one change and its verify command.
The MAP and wide searches are token-heavy and pollute the main context (which then drifts routing). Dispatch them to a subagent and take back only the distilled dependent list. Small, focused context = stable routing.
This skill adds the MoE-routing layer on top of, and defers detailed procedure to:
brainstorming, writing-plans, executing-plans, subagent-driven-development,
test-driven-development, systematic-debugging, verification-before-completion,
karpathy-guidelines.
| Thought | Reality |
|---|---|
| "I'll call it 'the parser' here, clearer" | Synonyms re-route experts. Use the one canonical name. |
| "I'll batch these unrelated fixes in one turn" | Mixed domains scatter routing. One domain per turn. |
| "I'll just edit this function" | Did you complete required gate + MAP dependents needed for this change? If not, stop. |
| "It's obviously right" | MoE is confidently wrong under routing drift. Run the test. |
| "The session's long but I remember the plan" | Anchors decayed. Re-anchor or reload from file. |
| "Close enough, done" | Run the done gate. All boxes or not done. |
npx claudepluginhub uuie/deepseek-instructions --plugin moe-executionProvides behavioral guidelines to reduce common LLM coding mistakes, focusing on simplicity, surgical changes, assumption surfacing, and verifiable success criteria.
Searches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.