「then」の検索結果

Clerk managed authentication - ClerkProvider, middleware, pre-built components, hooks, server-side auth, organizations, webhooks

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。

Detect and rewrite AI writing patterns to make content sound authentically human. Supports voice calibration from the author's own writing samples. Use when asked to humanize text, remove AI patterns, calibrate voice, audit content for AI detectability, or check if writing sounds like ChatGPT. Triggers: /humanize, /voice-calibrate, /audit-ai

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。

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。

Bootstrap a new standalone skill repo under gaia-research/ from the canonical template set at gaia-research/gaia-research/templates/skill-repo/. Handles the full flow: interactive prompts for all placeholders, fetches templates via the GitHub API, substitutes values, creates the new repo (gaia-research/skill-<name>), writes README.md / SKILL.md / install.sh / .gitignore / LICENSE / powered-by-gaia.svg, makes the initial commit and pushes. Also supports update mode: re-applies the template structure to a pre-existing skill repo and opens a draft PR with the drift. Use when the user says "new skill repo", "bootstrap a skill repo", "/skill-template", "create skill-foo", "spin up a gaia-research skill repo", "template a new skill", "align skill-fuse to the template", or "/skill-template update <repo>". Requires: gh CLI (authenticated with gaia-research org access), python3, git.

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。

Chart a too-big effort as a shared map of decision tickets on the Gaia headquarters issue tracker, then resolve them one at a time until the way to the destination is clear. Use when someone says: "this is too big for one session", "chart a map", "wayfinder map", "plan this effort", "what do we need to decide first", "open a wayfinder", "work the map", "what's on the frontier", or /wayfinder. Covers any gaia-research org repo — gaia-skill-tree, gaia-research, gaia-skill-heaven and beyond — but every map and every ticket lives on ONE tracker: gaia-research/gaia-skill-tree. This is cartography (planning an effort as decisions), NOT triage of an existing backlog — for that use /gaia-triage.

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 1 of the feature-pipeline suite — stress-test a CLI command, feature, flag, or module as a developer seeing it for the first time, then file GitHub issues for every distinct finding. Use when someone says "explore X", "test X", "find issues with X", "what's wrong with X", or after /feature-pipeline init. Also triggers standalone as /fp-explore <feature> when you want just the exploration phase without the full pipeline. Reads the target feature from .fp-state.json (or the argument if provided). Completes in one bounded turn and prints the M1 stop hook so the user decides whether to continue to /fp-plan.

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.

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).

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。

Discovery-only Gaia curation for one manually selected source page. Fetches and normalizes up to five real SKILL.md candidates, deduplicates and maps them for human L4 review, then stops without evidence scoring or registry mutation.

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。

Use this skill whenever the user wants to see how their branch will look on the live Gaia website before merging — "preview this branch", "show me what this looks like", "deploy a preview", "trigger a design preview", "can I see the site with these changes", "preview the skill profile", "check how this renders on the site", "spin up a preview deployment". This skill dispatches a Cloudflare Worker preview deployment for the current branch via GitHub Actions — no local build tooling required. Ideal for containerized environments, design reviews, and confirming that newly curated skills or profile pages render correctly before a PR is merged to main. The preview does NOT regenerate docs; it deploys `docs/` from the branch as-is. If your change depends on regenerated Class S artifacts, run `gaia dev docs` and commit those first — the preview then reflects them.

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 5 of the feature-pipeline suite. Use this after /fp-iterate prints the M4 stop hook confirming CI is green. Fetches origin/main, runs gaia dev diff to surface any skill-registry changes the PR introduced that are unrelated to its stated purpose (accidental drift), then prints the final pipeline summary including a CI churn report (via /ci-churn). Also invoke standalone whenever you want to audit whether a branch has unexpected registry drift — e.g. before merging any review/meta or cli/ branch, or when a reviewer asks "did this PR touch anything it shouldn't?". Triggers: "check for drift", "drift check", "final summary", "pipeline done", "wrap up the pipeline", "fp-drift", "Phase 5".

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。

Regenerate and commit Class S site-served artifacts after registry changes, then sync documentation across the main repo and the adjacent wiki. Use this skill when: you've changed registry/nodes/, registry/named/, or named-skills.json and need to regenerate docs/graph/* so the live website reflects the update; CI Guard E (docs-cohesion.yml) is failing because Class S artifacts are out of date; someone says "sync the docs", "regenerate docs", "run gaia dev docs", "update the site graph", "commit the Class S artifacts", "website is stale", or "update the wiki"; or you're finishing a registry PR and need to ensure docs/graph/gaia.json, docs/graph/gaia.gexf, docs/graph/gaia.svg, and docs/graph/named/index.json are committed alongside the source change. Also covers updating README.md, docs/index.html, and mirroring changes to the adjacent wiki repo at ../gaia-wiki.

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。

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.

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。

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".

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。

Produce the rendered evidence a human-gated frontend PR owes its reviewer: capture each changed surface (plus the before state for anything modified, plus mobile width), then generate one self-contained local HTML page the founder can open and review without checking anything out. Use when a PR is gated by the "Frontend changes are HUMAN-GATED" section of CLAUDE.md, or when the user says "/design-gate", "screenshot evidence for this PR", "prep this for founder review", "build the design evidence page", "what does this look like before and after". The page comes from a template script, not hand-written markup. Output is session-local and never committed. Do NOT use for non-gated changes: typo/grammar/factual fixes in an unchanged block, dead link targets, alt/ARIA fixes with no visual change, cache-bust bumps, or refactors with no rendered diff.

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。

Clones a STATIC IMAGE ad into finished ads for your own product, into a reusable prompt TEMPLATE, or both — the template is what makes the ads and the ads are what prove the template. Round-trips the frame through gpt-image-2, nano-banana-pro or reve-2.1 until it reproduces, replaces every brand-specific with a {placeholder}, then fills it with your product pinned to a real photo. Use for "clone this ad for my product", "rebuild this competitor's ad for us", "make me ads like this", "reverse engineer this ad", "make this ad reusable", "add this to my prompt library", or "clone my competitors' ads" with NO file attached — it sources one via spy-competitor-ads rather than asking which. **Among cloners the source's medium decides**: a still, or nothing attached, lands here; "clone this ad" plus a VIDEO is clone-video-ad. NOT for generating an ad from a brief (chatgpt-image-ad, nano-banana-image-ad), nor animating a still as-is (image-to-motion). Refuses to render your product without a real photo of it.

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。

Prepare or open a GitHub or Gitea pull request with an explicit AI-authorship disclosure, change classification, reproducible reviewer verification steps, and optional Mermaid diagram. Use whenever the user asks to prepare, write, open, create, push, ship, or get changes ready for a PR or review. Unless the user explicitly asks for a draft-only result, create or reuse a dedicated branch, verify the change, commit scoped files, push the branch, and then create the PR with gh or tea.

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。

Classify a proposed code change as Leaf Node or Core Code to decide how much AI usage and review rigor is appropriate. Use this skill whenever the user asks "is this leaf or core", "what kind of change is this", "should I vibe code this", "can AI write this", "how rigorous should the review be", or before starting any non-trivial change. Also useful as a sub-step inside other workflows (planning, PR prep, code review) when classification matters. Asks 6 diagnostic questions about propagation range, change frequency, tech-debt tolerance, examples, failure cost, and review intensity, then outputs a clear classification with the recommended approach. Trigger even when the user describes a change without explicitly asking for classification — the answer changes how they should proceed.

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。

Hunts malicious PowerShell using script-block (EID 4104) and module logging: scoring encoded commands, download cradles, AMSI/logging bypass, and in-memory execution, then decoding payloads for triage. Activates for requests to hunt malicious PowerShell, analyze script-block logs, or detect encoded command abuse.

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。

Manually unpacks a runtime-packed Windows binary by finding the original entry point (OEP) through tail-jump and entropy analysis, then guiding a memory dump at OEP. Activates for requests to manually unpack a sample, find the OEP, or unpack a custom/unknown packer that generic tools cannot handle.

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。

Extracts indicators of compromise from raw analysis artifacts: parsing strings dumps, sandbox reports, PCAP summaries, and logs for URLs, domains, IPs, hashes, mutexes, and file paths, then deduplicating and typing them. Activates for requests to extract IOCs from analysis output, pull indicators from a report, or harvest atomic indicators.

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。

Identifies and bypasses anti-debugging and anti-analysis checks in malware: PEB flags, debugger-detection APIs, timing checks, and exception tricks, then neutralizes them to continue analysis. Activates for requests to identify anti-debugging, bypass anti-debug checks, or analyze evasion that blocks a debugger.

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。

Runs a sample in an instrumented sandbox to observe behavior: process tree, file and registry changes, network activity, and persistence, then summarizes the behavioral report into capabilities and IOCs. Activates for requests to detonate a sample, do dynamic or behavioral analysis, or interpret sandbox output.

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。

Analyzes a memory image with Volatility 3 to find malware: rogue processes, injected code, suspicious network connections, loaded modules, and persistence, then extracts artifacts for further analysis. Activates for requests to do memory forensics, analyze a RAM dump, or hunt malware in memory with Volatility.

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。