「pipeline」の検索結果

Native MongoDB driver (the mongodb npm package) - MongoClient lifecycle, typed collections, CRUD result shapes, cursors, aggregation pipelines, index design, transactions

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Create videos programmatically using React (Remotion) or generate mathematical/conceptual animations (Manim). Use when the user asks to make a video, animation, product demo, tutorial, social clip, or branded video pipeline. Triggers: /remotion-video, /video-animation, /video-toolkit

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Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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Broad, pre-curation evidence reconnaissance for a declared Gaia skill, intake batch, upstream repository, or proposed generic capability. Run before choosing a discovery strategy or mapping topology, to give the curator independent research leads and counterevidence. Context only: never scores, grades, ratifies, ingests, or mutates the registry. Later ev-discovery and ev-pipeline phases validate/promote any selected leads.

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Write Prisma Next queries for Postgres, SQLite, or Mongo — pick a lane (Postgres/SQLite `db.orm.<Model>` + `db.sql.<table>`; Mongo `db.orm.<root>` + `db.query.from(...)` pipeline builder), filter / project / sort / paginate, eager-load with `.include(...)`, Postgres/SQLite `db.transaction(...)`, Postgres/SQLite ORM `.aggregate(...)`, Mongo aggregations via query builder, namespace-aware accessors (`db.orm.<ns>.<Model>`, `db.sql.<ns>.<table>`). Triggers: query, where, match, select, project, orderBy, take, skip, include, lookup, first, all, count, aggregate, group, create, update, delete, upsert, returning, transaction, db.close, script teardown, variant, polymorphism, drizzle-style, kysely-style. Notes: `.all()` is a Thenable (just `await` it), iterators are single-use (`RUNTIME.ITERATOR_CONSUMED`), Postgres `count` is `number` while sum/avg/min/max are `number | null`, ranges use chained `.where()` or `and(...)` (no `.between(...)`).

日本語の概要は準備中です。原文の説明を表示しています。

Generate interactive, animated, responsive HTML-based terminal simulators to showcase CLI commands, scripts, pipelines, or interactive workflows. Use this whenever you need to visually showcase a command line sequence, mock interactive CLI tools, or simulate code executions.

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Phase 1 of the Gaia evidence verification pipeline. Use this skill whenever you need to gather, consolidate, or refresh raw evidence for named skills in the registry. Trigger phrases: "collect evidence", "populate the data lake", "gather sources", "run ev-collection", "Phase 1", "compile the evidence index", "refresh the unified lake", "aggregate skill evidence", "build the evidence database". Also invoke as the first step before running ev-star-verification, ev-adversarial-audit, or ev-link-validation — nothing downstream is meaningful without a fresh, compiled index. Covers GitHub repo links, stargazer signals, YouTube showcases, arXiv papers, peer reviews, benchmark results, blog/newsletter posts, and self-attestation artifacts.

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Phase 3 of the feature-pipeline suite. Run this after /fp-implement has pushed all commits and printed the M2 stop hook. Spawns a sandboxed sub-agent (HEAVIER) in an isolated worktree to run RED/GREEN tests against the PR diff and post a structured review comment. Use when you need an independent agent to verify correctness of implementation changes before CI runs — especially for schema mutations, CLI surface changes, or doc-touching commits. Triggers on: "review the PR", "run sandbox review", "fp-review", "Phase 3", "check the implementation", "validate the changes", "run tests on the PR", or any instruction to verify what /fp-implement just pushed.

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Phase 2 of the evidence verification pipeline. Validates GitHub star counts in registry skill files against live GitHub API data and flags stale or inflated metrics without repartitioning evidence by rank. Use this after /ev-collection has compiled the unified data lake and before /ev-adversarial-audit begins. Trigger phrases: "verify stars", "check star counts", "refresh stargazer metrics", "run star verification", "ev-star-verification", "Phase 2", "live star check".

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End-to-end plan → implement → review pipeline that takes one triaged Gaia issue to a merged-ready PR, with Kill Criteria on the issue and zero follow-up debt. Use when someone says: "resolve this issue", "take #N end-to-end", "work the P0 queue", "fix and ship this issue", "run the resolver", "close out this issue properly", or /gaia-issue-resolver. Works any gaia-research org repo — gaia-skill-tree, gaia-research, gaia-skill-heaven — while the issue itself lives on the headquarters tracker, gaia-research/gaia-skill-tree. Assumes the issue is already triaged and carries a P0–P4 label; if it does not, run /gaia-triage first.

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Atomically ingest one already-verified evidence row into one named Gaia skill using the CLI, then appraise Trust Magnitude and propose—never silently apply—a calibration. Use after /ev-pipeline has verified an approved intake source, or whenever a curator says "ingest evidence", "add verified evidence", "gaia-ingest", or "turn this source into registry evidence".

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Post-review intake closing skill. After an intake is resolved (whether accepted via review/meta PR merge or rejected/deferred at triage/evidence review), run this skill to post standardized, personalized closing comments on the PR (if any) and each intake issue. Comments include: evidence pipeline findings with /trust-appraise TM output, per-row artifact scores, decisions rationale, path-to-promotion/acceptance guidance, and a mandatory badge status note including the universal Powered by Gaia badge. Use after curation completes, before or immediately after merge for accepted intakes, or immediately upon rejection.

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Curate Gaia bot crawler branches into real-skill catalog entries and clean up processed bot/* branches. Use when the user says: "process bot branches", "curate the crawl output", "clean up bot proposals", "run bot curation", "merge the crawler results", "review bot/* branches", "ingest crawler data", or explicitly types /gaia-bot-curate. Also triggers when the user asks to review pending `bot/*` branches, turn crawler JSON proposals into registry nodes, decide which crawled skills to accept vs reject, or batch-add skills from an automated crawl run. This skill handles the full pipeline: fetch remote bot branches, triage proposals, run `gaia dev` mutations, validate, open a PR, and delete consumed bot branches.

日本語の概要は準備中です。原文の説明を表示しています。

Phase 4 of the feature-pipeline suite. Use this after /fp-review has posted a sandbox review comment — it reads the outstanding checkbox items, applies fixes, then watches CI until green (or exits cleanly so you can retry). Trigger phrases: "address review items", "fix review feedback", "resolve review checklist", "watch CI", "poll CI", "check if CI is green", "iterate on PR", "fp-iterate", "Phase 4", "after review comment", "fix the review issues and watch CI". Always bounded — max 10 poll rounds, never loops forever. Exits with a clear status: green (hands off to /fp-drift), still-pending (re-invoke), or failed (diagnose before touching anything).

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Phase 2 of the feature-pipeline suite. Use this after /fp-explore has filed issues and printed the M1 stop hook — when you need to turn a set of filed GitHub issues into an approved implementation plan and a draft PR. Triggers on: "plan the fix", "create the branch and PR", "draft the implementation plan", "ready to plan", "fp-plan", "next step after explore", "convert issues to a plan", "plan phase". Reads issueNumbers from state, writes a Problem Statement, opens a feature branch + draft PR, spawns a HEAVIER sub-agent for the numbered plan, and blocks on explicit user approval before writing plan to state. Does NOT write any code — that is /fp-implement.

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Phase 3 of the feature-pipeline suite. Use this after /fp-plan has received explicit user approval and printed the M2-plan stop hook — when you need to translate an approved numbered plan into committed, pushed code. Triggers on: "implement the plan", "start coding", "commit the plan", "write the code", "fp-implement", "Phase 3", "plan is approved let's code", "next step after plan", "execute the plan", "apply the plan", "make the changes". Reads planApproved and branch from state; refuses to run if approval hasn't been recorded. Commits one atomic change per plan step, pushes after each commit, handles obstacles cleanly, and hands off to /fp-review when done. Never squashes or skips steps — the one-commit-per-step rule keeps the review history readable and rollback surgical.

日本語の概要は準備中です。原文の説明を表示しています。

Skippable Phase 0 of the Gaia evidence verification pipeline. Use only on declared need for higher-quality Stage-2 evidence: a promotion candidate, or a skill that gaia-meta-sweep flagged as under-evidenced. Given a skill id, source repo/context, and needed evidence types (benchmark-result, arxiv, peer-review, social-signal), it runs Firecrawl searches, scrapes top hits to markdown, and appends discovered sources into Phase 1 inputs. Missing benchmark evidence is recorded as benchmark-source candidates first, not direct scoring rows. Trigger phrases: "discover evidence", "find new evidence", "Phase 0", "run ev-discovery", "search for benchmarks/papers", "under-evidenced", "promotion candidate needs stronger proof". This is the ONLY ev-* skill that searches the web for NEW evidence; other ev-* skills aggregate or verify known sources. Requires Firecrawl to be usable (`firecrawl --status` authenticated OR FIRECRAWL_API_KEY set); skips gracefully when neither holds.

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Batch wrapper for /gaia-ingest. Ingests a bounded set of already-verified evidence rows through CLI-only writes, uses --no-build on every row, appraises Trust Magnitude for every affected named skill, then runs exactly one build and validation pass. Use for an L4-approved intake after /ev-pipeline; benchmark-result rows also require a Phase 2B report and explicit human gate approval.

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This skill provides comprehensive guidance for setting up and configuring test environments for VS Code extension projects. Use when initializing a new test infrastructure, configuring test runners (Vitest), setting up CI/CD test pipelines, integrating coverage tools (v8/c8), or troubleshooting test configuration issues.

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Prove a UI or generation feature actually works before asking a human to look at it. Covers A/B-ing an imported design against its source render, driving controls headlessly so a dead button cannot ship, proving the generator really spawns, and launching the real host (VCV Rack, a DAW). Use before any "take a look" on imported UI, plugin shells, or prompt-to-artifact pipelines.

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The measurement surface for ALL Pulp DSP and audio-pipeline work — read it BEFORE writing or gating DSP, not only when something already sounds wrong. Covers the C++ harness (signal generators, metrics, assertions, RenderScenario, contracts), the offline Audio Doctor (magnitude/frequency response, THD/THD+N, phase/group delay), and their Python sibling the Audio Quality Lab (tools/audio/quality-lab — null residual + alignment, LTAS log-spectral distance, spectral flux/centroid, HNR, Theil-Sen drift slope, Kaiser-sinc resampling, license-guarded corpus, regression-net ratchet). TRIGGER on AUTHORING work — "build/design an oscillator/filter/synth/effect", "add a DSP module", "what should the acceptance gate be", "how do I measure aliasing / anti-aliasing / alias floor", "null against a reference", "is this DSP correct", "choose a tolerance", "golden/regression corpus for audio", "measure drift or jitter", "A/B two renders" — AND on DEBUGGING work — "is there sound / no audio / I hear nothing", "does this filter/compressor/synth/delay produce the right signal", "prove the DSP / prove the contract", "measure the frequency response", "what's the THD / is it distorting", "what's the group delay / phase response / measured latency", "magnitude response curve", "render a test tone and assert", "audio regression", "64-frame works but 128 is silent", "sample-rate change pitch-shifted it", "describe what's in this buffer", "audio doctor", "compare before/after a DSP refactor". Reach for this BEFORE hand-rolling any FFT, null test, alias measurement, pitch tracker, or golden-render script — most of it already exists in one of the two lanes. Test/tool layer over HeadlessHost — deterministic, no audio device, no speakers. Off the realtime thread entirely.

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Plan and promote events — conferences, trade shows, webinars-as-events, and field marketing that drives pipeline.

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Use esbuild for extreme-speed builds: bundling, transforming, plugins, and integration into larger pipelines. Use when build speed is the bottleneck.

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Building robust document ingestion — chunking, metadata, and multi-format pipelines for search and RAG.

日本語の概要は準備中です。原文の説明を表示しています。