Use when the user wants to learn, be taught, be quizzed, or understand an idea across any domain — science, math, philosophy, code, law, politics, psychology, medicine, arts, or history — with active scaffolding.
中文简介正在准备中。当前显示原文说明。
Use when the user wants to rename, extract, split, move, or restructure code safely. Examples: "Rename this function", "Extract this into a module", "Refactor this class", "Move this to a separate file"
中文简介正在准备中。当前显示原文说明。
实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Refactoring writes to disk. rename with dry_run: false edits files in
whichever repository was resolved, so binding identity here is a safety gate,
not bookkeeping.
Call list_repos {} before the first tool call. With one indexed repository,
use the examples below as written. With more than one, pass repo on every
call: an omitted repo normally errors, but under an MCP policy with a
configured default it resolves to that default silently. If you cannot tell
which repository is meant, stop and ask. Never run rename with
dry_run: false until the preview in the same bound repository has been
reviewed — its returned file_path values show which checkout is about to be
written, so read them as a confirmation of identity.
list_repos is paginated, so page with offset: pagination.nextOffset until
hasMore is false before concluding a repository is absent.
detect_changes takes worktree when you are editing a linked worktree the
MCP server was not launched from; otherwise git diff runs in the wrong
checkout and reports nothing changed, which reads as a verified refactor.
0. list_repos {} → Bind repo (and worktree)
1. impact({target: "X", direction: "upstream"}) → Map all dependents
2. query({search_query: "X"}) → Find execution flows involving X
3. context({name: "X"}) → See all incoming/outgoing refs
4. Plan update order: interfaces → implementations → callers → tests
If "Index is stale" → run
node .gitnexus/run.cjs analyzein terminal.
- [ ] list_repos {} — bind repo; explicit repo when >1 indexed, ask if ambiguous
- [ ] rename({symbol_name: "oldName", new_name: "newName", dry_run: true}) — preview all edits
- [ ] Confirm the previewed file paths are in the bound repository/worktree
- [ ] Review graph edits (high confidence) and text_search edits (review carefully)
- [ ] If satisfied: rename({..., dry_run: false}) — apply edits
- [ ] detect_changes() — verify only expected files changed
- [ ] Run tests for affected processes
- [ ] list_repos {} — bind repo; explicit repo when >1 indexed, ask if ambiguous
- [ ] context({name: target}) — see all incoming/outgoing refs
- [ ] impact({target, direction: "upstream"}) — find all external callers
- [ ] Define new module interface
- [ ] Extract code, update imports
- [ ] detect_changes() — verify affected scope
- [ ] Run tests for affected processes
- [ ] list_repos {} — bind repo; explicit repo when >1 indexed, ask if ambiguous
- [ ] context({name: target}) — understand all callees
- [ ] Group callees by responsibility
- [ ] impact({target, direction: "upstream"}) — map callers to update
- [ ] Create new functions/services
- [ ] Update callers
- [ ] detect_changes() — verify affected scope
- [ ] Run tests for affected processes
rename — automated multi-file rename:
rename({symbol_name: "validateUser", new_name: "authenticateUser", repo: "my-app", dry_run: true})
→ 12 edits across 8 files
→ 10 graph edits (high confidence), 2 text_search edits (review)
→ Changes: [{file_path, edits: [{line, old_text, new_text, confidence}]}]
impact — map all dependents first:
impact({target: "validateUser", repo: "my-app", direction: "upstream"})
→ d=1: loginHandler, apiMiddleware, testUtils
→ Affected Processes: LoginFlow, TokenRefresh
detect_changes — verify your changes after refactoring:
detect_changes({scope: "all"})
→ Changed: 8 files, 12 symbols
→ Affected processes: LoginFlow, TokenRefresh
→ Risk: MEDIUM
partial: true (a graph query failed) or truncated: true (the changed-symbol
listing was capped) means the result is short of the truth: a short or empty
list is not proof that only the expected files changed. Re-run it rather than
treat the refactor as verified.
A wrong-worktree zero carries neither flag and is indistinguishable from a clean verification, so confirm the diffed checkout is the one you edited.
cypher — custom reference queries:
MATCH (caller)-[:CodeRelation {type: 'CALLS'}]->(f:Function {name: "validateUser"})
RETURN caller.name, caller.filePath ORDER BY caller.filePath
| Risk Factor | Mitigation |
|---|---|
| Many callers (>5) | Use rename for automated updates |
| Cross-area refs | Use detect_changes after to verify scope |
| String/dynamic refs | query to find them |
| External/public API | Version and deprecate properly |
| Same name in another indexed repo | Bind repo; verify previewed paths before applying |
validateUser to authenticateUser0. list_repos {}
→ total: 2 (my-app, billing-api) — both define validateUser, so bind explicitly
1. rename({symbol_name: "validateUser", new_name: "authenticateUser", repo: "my-app", dry_run: true})
→ 12 edits: 10 graph (safe), 2 text_search (review)
→ Files: validator.ts, login.ts, middleware.ts, config.json...
2. Review text_search edits (config.json: dynamic reference!)
3. rename({symbol_name: "validateUser", new_name: "authenticateUser", repo: "my-app", dry_run: false})
→ Applied 12 edits across 8 files
4. detect_changes({scope: "all", repo: "my-app"})
→ Affected: LoginFlow, TokenRefresh
→ Risk: MEDIUM — run tests for these flows
Repository: my-app (/abs/path/my-app) Worktree: same Index: current
With a single indexed repository, step 0 returns total: 1 and the repo
argument drops out of every call above.
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Use when the user wants to learn, be taught, be quizzed, or understand an idea across any domain — science, math, philosophy, code, law, politics, psychology, medicine, arts, or history — with active scaffolding.
中文简介正在准备中。当前显示原文说明。
This skill helps with using the @ax-llm/ax TypeScript library for building LLM applications. Use when the user asks about ax(), ai(), f(), s(), agent(), flow(), AxGen, AxAgent, AxFlow, signatures, streaming, or mentions @ax-llm/ax.
中文简介正在准备中。当前显示原文说明。
This skill helps an LLM generate correct AxAgent code using @ax-llm/ax. Use when the user asks about agent(), child agents, namespaced functions, discovery mode, shared fields, llmQuery(...), RLM code execution, recursionOptions, or agent runtime behavior. For tuning and eval with agent.optimize(...), use ax-agent-optimize.
中文简介正在准备中。当前显示原文说明。
This skill helps an LLM generate correct AxAgent tuning and evaluation code using @ax-llm/ax. Use when the user asks about agent.optimize(...), judgeOptions, eval datasets, optimization targets, saved optimizedProgram artifacts, or recursive optimization guidance.
中文简介正在准备中。当前显示原文说明。
This skill helps an LLM generate correct AI provider setup and configuration code using @ax-llm/ax. Use when the user asks about ai(), providers, models, presets, embeddings, extended thinking, context caching, or mentions OpenAI/Anthropic/Google/Azure/Groq/DeepSeek/Mistral/Cohere/Together/Ollama/HuggingFace/Reka/OpenRouter with @ax-llm/ax.
中文简介正在准备中。当前显示原文说明。
This skill helps an LLM generate correct AxFlow workflow code using @ax-llm/ax. Use when the user asks about flow(), AxFlow, workflow orchestration, parallel execution, DAG workflows, conditional routing, map/reduce patterns, or multi-node AI pipelines.
中文简介正在准备中。当前显示原文说明。