「surface」の検索結果

Design agent tools and CLI surfaces—schemas, naming, errors, idempotency, and discoverability for LLM callers. Use when defining tools for agents, SDKs, or AI-native CLIs.

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。

Builds and audits a concept-ontology for a regelrecht corpus to decide and verify reference types — cross-law source-binding vs intra-law source-binding vs open-norm leaf vs external-fact leaf — and to catch concept conflation across laws. Core principle: a value's reference type is fixed by WHO derives it, and a binding is sound only when producer and consumer denote the SAME concept; the lexical surface (the word in the text) is not the concept. Detects false friends (one term, different concepts — e.g. a register-based vs a factual "naar de omstandigheden"-based residence/ingezetene concept), orphan plain-params (a value a regulation actually derives, modeled as a brute input), negation/complement re-entry (¬X modeled as an independent leaf next to X), and duplication (one concept re-entered as several independent leafs, losing the single-source-of-truth invariant). Produces a law-level glossary and a stelsel-level concept map with sound same-concept binding edges and flagged lexical-match-but-concept-mismatch edges. Use when deciding whether a value should be cross-law/intra-law/leaf, when the same term means different things across laws, or when a binding might silently conflate concepts.

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。

Guides building and deploying Atlassian Forge Teamwork Graph connector apps that ingest external data into Atlassian's Teamwork Graph, making it searchable in Rovo Search and surfaced in Rovo Chat. Use when the user wants to build a Forge connector, ingest external data into Atlassian, connect a third-party tool (e.g. Google Drive, ServiceNow, Salesforce) to Atlassian, make external content searchable in Rovo, build a graph:connector module, use the @forge/teamwork-graph SDK, or implement onConnectionChange / validateConnection functions.

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。

Deep OAuth 2.0 / OpenID Connect security assessment. Covers the full attack surface: redirect_uri validation bypass (path traversal, open redirect chains, subdomain confusion, URL parsing tricks, parameter pollution, response mode switching), missing/broken state parameter CSRF, PKCE downgrade and absent-challenge attacks, implicit grant token leakage (Referer, browser history, XSS fragment theft), authorization code injection, scope escalation, client confusion attacks, mutable-claims account takeover (iss+sub confusion, email-keyed identity merging), pre-account takeover via unverified registration, OpenID Connect dynamic client registration SSRF (logo_uri, jwks_uri, sector_identifier_uri, request_uri), nonce replay, ID token validation failures, Device Code phishing flow, mobile custom URI scheme hijacking, refresh token persistence, token introspection enumeration, consent screen clickjacking, host header injection, and cross-IdP mix-up attacks. Uses KOAuth, jwt_tool, nuclei oauth templates, and manual http(action="request", ...) payloads. Every technique includes actual request payloads and verification logic. Chains from /pentester or /api-security when OAuth endpoints are discovered. Chains into /web-exploit for open redirect, XSS, and SSRF chaining. Chains into /post-exploit when full account takeover is achieved. Chains into /credential-audit when access tokens or refresh tokens are recovered.

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。

Identify and map the external corporate footprint of a target organization. Use this skill at the absolute beginning of an engagement (Reconnaissance) to identify all registered domains, subdomains, IP ranges, and Autonomous System Numbers (ASNs) owned by the target. This skill forms the foundation for all subsequent external penetration testing and attack surface management.

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。

Cloud security posture assessment for AWS, Azure, and GCP. Tests IAM privilege escalation paths, public storage exposure, serverless attack surface, database exposure, logging gaps, container registry security, and cloud-specific attacks. Both authenticated (with cloud credentials) and unauthenticated (external) modes. Uses nuclei cloud templates, Prowler, ScoutSuite, manual IMDS/metadata probing, and deep AWS/Azure/GCP CLI enumeration. Produces: cloud architecture diagram, attack path map, findings per category, compliance mapping (SOC 2, PCI DSS 4.0, HIPAA, CIS), PoCs for confirmed exploits. Chains into /gh-export for issue filing.

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。

Deep API security assessment beyond surface scanning. Covers the full OWASP API Security Top 10 (2023): Broken Object Level Authorization (BOLA / IDOR), Broken Authentication, Broken Object Property Level Authorization (mass assignment + excessive data exposure), Unrestricted Resource Consumption, Broken Function Level Authorization (BFLA / vertical privilege escalation), Unrestricted Access to Sensitive Business Flows, Server-Side Request Forgery via API parameters, Security Misconfiguration, Improper Inventory Management (shadow/zombie/deprecated endpoints, v1/v2 drift), and Unsafe Consumption of third-party APIs. Works across REST, GraphQL, gRPC, SOAP, and MCP servers. Discovers APIs from OpenAPI/Swagger specs, GraphQL introspection, gRPC reflection, .well-known endpoints, JS bundles, and traffic capture. Uses kiterunner, ffuf, schemathesis, restler-fuzzer, openapi-fuzzer, graphql-cop, clairvoyance, batchql, inql, jwt_tool, postman, mitmproxy, and manual http(action="request", ...) payloads. Every technique includes actual payloads, commands, and verification logic. Chains from /pentester or /codebase when API endpoints are discovered, chains into /web-exploit when classic injection points are found in API parameters, chains into /post-exploit when RCE is achieved, and chains into /ai-redteam when an LLM/AI endpoint is discovered (chat APIs, completion endpoints, RAG search, agentic tool-use, MCP servers).

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。

Systematically discover hidden Application Programming Interfaces (APIs), uncover undocumented endpoints (Shadow APIs), and fuzz parameters. Use this skill as the pivotal first step in API Bug Hunting, transforming a basic frontend application into a vast mapped attack surface.

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。

API reconnaissance and documentation review playbook. Use when discovering endpoints, schemas, versions, OpenAPI specs, hidden docs, and surface area for API testing.

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 when building 2D games in Python with pygame - game loop and delta time, sprites and groups, collision detection, drawing and surfaces, events and input, sound and fonts, camera, or performance optimization

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。

Interview the user to surface experience that is real but undocumented, mapped against a specific role's requirements, then update the profile. Use when a fit assessment or an adversarial review flags a section as thin.

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。

Extract real brands (Wayback for rebuilds). Copy system, headline/CTA rules, trust surfaces, legal pages, SEO+structured data, anti-AI-slop, microcopy, DESIGN.md, W3C DTCG tokens, pSEO 5 types, GEO/AI search.

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。

Copy + discoverability requirements every delivered app must meet — real-brand extraction, anti-slop voice, per-page SEO/JSON-LD, pSEO, GEO/AI-search, truth/citations, competitor floor, i18n, trust surfaces.

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。

Frappe backend guidance for Python and backend-adjacent JavaScript surfaces such as client interaction patterns, hooks, APIs, patches, scheduler logic, reports, and server-side review. Use when implementing or reviewing Frappe backend behavior.

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。

Frappe-specific search and discovery guidance for finding benches, apps, remotes, sites, ports, hooks, DocTypes, builder DocTypes, and frontend surfaces quickly. Use when the task starts with locating or classifying Frappe context.

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。

Frappe customization-surface guidance covering Custom Field, Property Setter, Client Script, Server Script, Workspace, Web Page, Page, Print Format, Report, Dashboard, Workflow, Role, Notification, Webhook, and related builder/admin DocTypes. Use when choosing or changing Frappe customization layers.

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。

End-to-end Frappe and ERPNext implementation guidance spanning backend Python, backend JavaScript surfaces, Vue or React frontends, customizations, and bench-aware delivery. Use when the task crosses multiple Frappe layers.

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。

CLI specification planning frameworks. Use when a spec touches a command surface, an interactive flow, config precedence, exit codes, or output modes. Covers flag contracts, prompt flow design, precedence tables, exit-code taxonomy, TTY/piped/JSON output, error text, signals, and cross-platform concerns.

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 a prioritized review queue of registry skills and catalog items that need attention. Use this skill whenever someone asks: "what needs review?", "what's overdue for audit?", "where are the weak spots in the registry?", "what should I audit next?", "run a health check on the registry", "show me flagged skills", "find problems in the registry", "what skills need fixing?", or "triage the registry". This is the triage layer — it surfaces candidates ranked P0–P4 so that focused work (via /gaia-audit) targets the right things first. Run this before any audit pass. Also invoke proactively when a PR changes registry/named/ at scale, or before a release, to catch regressions early.

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。

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。

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.

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。

Detects command-and-control beacons in network logs by analyzing connection timing: measuring inter-arrival intervals, accounting for jitter, and scoring regularity per source/destination pair to surface periodic callbacks. Activates for requests to hunt C2 beaconing, find periodic callbacks, or analyze connection-interval regularity.

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 for Windows persistence across autostart locations: Run keys, services, scheduled tasks, WMI event subscriptions, and startup folders, baselining them to surface anomalous or recently added entries. Activates for requests to hunt persistence, audit autostart extensibility points, or find malware autoruns on Windows.

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。