「dise」の検索結果

Mindset theory, implicit theories of intelligence, and motivation research applied to learning. Covers fixed vs. growth mindset, the difference between process praise and ability praise, the "not yet" intervention, attribution patterns after failure, mindset critiques and the replication record, and the integration of mindset work with self-determination theory (autonomy, competence, relatedness). Use when a learner is stuck on motivation, disengaging after failure, or when a curriculum's feedback language is undermining persistence.

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Query CZ CELLxGENE Census (61M+ cells). Filter by cell type/tissue/disease, retrieve expression data, integrate with scanpy/PyTorch, for population-scale single-cell analysis.

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Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR screening design, single-cell RNA-seq analysis, ADMET prediction, GWAS interpretation, rare disease diagnosis, or lab protocol optimization. Leverages LLM reasoning with code execution and integrated biomedical databases.

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Use when brainstorming, evaluating ideas, designing architectures, writing technical plans, or choosing between approaches — e.g. "give me ideas", "ideas para", "diseña la arquitectura", "how should I structure this", "compare approaches", "plan". Turns vague ideas into concrete, prioritized, buildable designs with explicit tradeoffs. Use before writing code, not after.

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Run automated QA checks on Grafema VS Code extension via Playwright + MCP cross-validation. Use when: (1) user says "/qa" to start or resume QA session, (2) user wants to validate extension panels against graph data, (3) user wants to re-check previously found bugs after a fix, (4) user wants to run a custom QA task. Requires Docker code-server running.

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Pattern for adding derived edge types in the Grafema Rust orchestrator (main.rs). Use when: (1) need to create new graph edges derived from existing edges (e.g., MODULE-level DEPENDS_ON from IMPORTS_FROM), (2) Datalog joins on large edge sets time out, (3) adding enrichment steps that combine data from multiple resolver outputs, (4) need to understand how resolver outputs flow through the orchestrator pipeline.

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Fix stale Haskell analyzer binaries silently being used by the orchestrator even after a successful rebuild. Use when: (1) modified `packages/js-analyzer/` or other Haskell analyzer source, ran `scripts/build-native.sh ... cabal install`, but a subsequent `grafema analyze` shows old behavior (missing new edges, no new node types, etc.), (2) `~/.cabal/bin/grafema-analyzer` has fresh timestamp but `grafema analyze` produces output as if the change didn't happen, (3) a test verifying new analyzer output passes locally in unit tests but fails in end-to-end runs that go through the orchestrator. Root cause: the Rust orchestrator's `resolve_binary` checks `~/.grafema/bin/<name>` BEFORE `~/.cabal/bin/<name>`, so any stale copy that was once installed there (possibly months ago) shadows the fresh `cabal install` output.

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How to write a Grafema batch-mode plugin that reads the graph and filesystem, then writes new edges/nodes directly to RFDB. Use when: (1) need to add project-specific edges that generic analyzers can't produce, (2) need to read config files (JSON/YAML) and trace values into code, (3) implementing framework-specific resolvers (Django settings, Express routes, pipeline configs). Covers: grafema.config.yaml plugin config, RFDB field naming (src/dst NOT source/target), addEdges/addNodes API, RFDBServerBackend connection pattern.

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Cyclical dogfooding loop: test AI-AGENT-STORIES.md against the live graph, discover new stories, analyze gaps, fix root causes, re-test, write report. Use when: (1) user says "/gap-loop", (2) periodic dogfooding session, (3) after a release or major feature to re-validate stories, (4) before sprint planning to prioritize product gaps.

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Fix intermittent `{:no_translation, :unicode, :latin1}` crashes in Elixir escript daemons that use length-prefixed framed IPC on stdin/stdout. Use when: (1) daemon worker crashes only on some input files, usually ones with non-ASCII bytes (kanji, cyrillic, emoji); (2) error surfaces as `Protocol error` from daemon's error branch or as garbled frame-length bytes seen by the orchestrator/client side; (3) standalone one-shot mode works fine on the same input but multi-request daemon mode fails; (4) `IO.binread(:stdio, N)` returns `{:error, {:no_translation, :unicode, :latin1}}` despite the "bin" prefix suggesting it should be encoding-agnostic. Root cause is the escript default `:standard_io` encoding — it's `:unicode`, and `IO.binread` still routes through the io_server, which translates bytes to codepoints and errors when raw binary frames contain invalid UTF-8 sequences.

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Fix GraphSnapshot tests blocking CI on every feature PR. Use when: (1) every PR fails CI with "Snapshot mismatch" despite correct behavior, (2) fixing snapshots requires build → regen → commit → wait CI cycle per PR, (3) snapshot test in test/unit/*.test.js glob breaks on any intentional change, (4) pre-push hook runs pnpm build + snapshots:update on every push (2-3min overhead). Solution: move GraphSnapshot.test.js to test/unit/snapshots/ so it's excluded from the *.test.js glob. Run manually via pnpm snapshots:update when needed.

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Fix node query issues in Grafema tests when nodes have numeric IDs instead of human-readable IDs, or when `type` field is undefined. Use when: (1) queryNodes returns nodes with numeric IDs like "52710336597754872375318185843222727675" instead of semantic IDs like "net:request#__network__", (2) node.type is undefined but node.nodeType has a value, (3) metadata is a JSON string instead of parsed object, (4) tests fail with "Cannot read property 'length' of undefined" after queryNodes. Covers RFDBServerBackend vs RFDBClient distinction and async generator handling.

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Analyze codebases using a graph database instead of reading source files. Use when understanding code architecture, finding functions or call patterns, tracing data flow, checking dependencies, or answering "where is X used?" questions. Grafema builds a queryable code graph from static analysis — prefer querying the graph over reading files manually.

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Verify which process actually owns a TCP port before assuming your fresh restart succeeded. Use when: (1) you killed an old server and started a new one but behaviour matches the OLD code/data, (2) `pkill -f pattern` returned 0 but old behaviour persists, (3) you embedded a new asset/binary but the served version is stale, (4) any "I just restarted X but I'm getting old results" situation. `pkill -f` matches against the process command line — if the live old process was started with `--port 0` (auto-assigned) and got the port you now want, the pattern won't match it. Always verify with `lsof -i :PORT` before debugging deeper.

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Fix Node.js CLI tools crashing inside Docker containers when host-installed node_modules require a newer Node version than the container provides. Use when: (1) "SyntaxError: Invalid regular expression flags" with /v flag in string-width or similar packages, (2) node_modules installed on host with Node 20+ but container has Node 18, (3) `npm install` with file: protocol creates symlinks that break inside Docker, (4) pnpm workspace packages become broken symlinks in containers. Covers version detection, Node binary mounting, and npm install strategies for cross-version compatibility.

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Fix docker exec hanging when starting background processes (servers, daemons) inside containers. Use when: (1) docker exec never returns despite using & or nohup, (2) background server started in container causes docker exec to hang indefinitely, (3) env_startup_command in SWE-bench or similar frameworks times out, (4) setsid/disown needed for proper process detachment in Docker. Root cause: docker exec tracks ALL processes in the exec session, not just the top-level PID.

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Verify task completion by demonstrating real value: run the new code on real data, show visible results, find gaps between plan and reality. Not about tests/builds — about proving the feature WORKS end-to-end.

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SWE-bench pipeline for A/B testing Grafema with Claude Code. Use when: (1) running SWE-bench experiments, (2) comparing baseline vs grafema conditions, (3) evaluating results, (4) debugging container issues.

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Build all packages, reinstall VS Code extension, commit and push. Use when: user says "ship", or wants to build+install+commit+push in one go.

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Force `rust-embed` to re-embed assets from `$GRAFEMA_UI_DIST` (or any env-driven path) when cargo's incremental compilation skips the macro re-expansion. Use when: (1) you rebuilt the GUI bundle but the rust-server binary still serves the OLD bundle, (2) `cargo build --release` finishes in seconds (incremental hit) and `strings target/release/binary | grep <new-hash>` finds nothing, (3) any rust-embed pipeline where assets live outside the cargo source tree and are picked up via env var or symlink. Cargo only re-runs the proc macro when the rust file declaring `#[derive(RustEmbed)]` changes — env var changes alone don't trigger it.

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Speed up Rust development iteration when `cargo build --release` takes 10+ minutes even for one-line edits. Use when: (1) every release rebuild takes minutes despite tiny edits, (2) Cargo.toml has `lto = "fat"` and/or `codegen-units = 1` in `[profile.release]`, (3) you want a production- shaped build for testing without paying the LTO cost on every iteration, (4) you suspect cargo is re-linking the whole binary instead of doing incremental work, (5) developing rfdb/grafema-orchestrator/large Rust binaries where full LTO is enabled for shipped builds. Adds a `fast` profile that inherits release but disables LTO, raises codegen-units, enables incremental compilation — first build still slow because it populates a fresh `target/fast/` dep cache, but every subsequent rebuild drops from ~13 min to ~13 s (≈60×).

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Fires after fixing any non-trivial bug or regression. Asks: could the graph have caught this as a guarantee? Pairs with reflection-in-and-on-action — picks up after "earliest catchable signal" and asks the next question: was that signal expressible in graph? Triggers: (1) after any non-trivial bug fix is verified working, (2) after a regression report (something used to work, broke), (3) during step 6 (knowledge extraction) of the workflow, (4) when reflection-on-action surfaces a "would have been catchable" signal. Outcome is a triage decision (graph-reachable? rule expressible? rule sound?) and either a draft Linear issue + guarantee proposal, or a recorded "graph capability gap" note. Never auto-creates guarantees.

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RFDB server becomes unresponsive (60s+ timeouts) during enricher addEdges write storms. Use when: (1) RFDB CPU spikes to 60-90% after addEdges calls; (2) subsequent reads time out at 60s; (3) server stays catatonic for 5-15 min after a write storm; (4) Tokio main thread parked (write-lock contention). Root cause: add_edges() calls maybe_auto_flush() which has a memory-pressure path that fires on NODE count — not edge count — and holds the exclusive write lock during disk I/O. Fix: separate maybe_auto_flush_edges() uses byte-limit only.

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Grafema release procedure for publishing new versions to npm. Covers happy path, pitfalls, rfdb binary lifecycle, and rollback. Use when user says "release", "publish", "bump version".

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