“call graph”的搜索结果

Assemble the FREE steps of the product-hypermotion + kinetic-typography video format — dice ONE Seedance 2.0 hypermotion clip into 5-6 segments and intercut them with PIL kinetic-typography spec/CTA cards (italic skew, 1.08x outline echo, 3D extrusion, slam-with-shake, inversion flash) plus a real-logo PIL end card (base64-decoded from the brand SVG), center-crop 1:1 to 9:16, and explicit-map mux a music bed. Deterministic, FREE (PIL + FFmpeg), no paid calls, the real logo and spec typography stay pixel-crisp. The paid steps (the ONE Seedance i2v, the music) are separate capabilities; the recipe orchestrates them. Use for the product-hypermotion format.

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Package an existing talking-head / interview / podcast video with timed, designed GRAPHIC OVERLAY cards — kinetic titles, lower-thirds, data callouts, quotes, side panels, picture-in-picture — synced to the transcript, on a 16:9 / 9:16 / 4:5 canvas of your choice; the clip plays untouched underneath. Trigger on "graphic overlays", "on-screen graphics", "package / dress up my video". Not plain subtitles (/embedded-captions). Unclear → /hyperframes.

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Diagrams and checkable docs from a codebase. Draws ERDs, C4 context/container/component views, API endpoint catalogues, lifecycle/state machines, sequence diagrams, and service-to-service call maps as a validated JSON spec plus a standalone HTML viewer, with Mermaid export. Imports OpenAPI, GraphQL SDL and Prisma; otherwise reads the code (NestJS, TypeORM, Express) and writes the spec. Use for: database diagram, ERD, data model, table relationships, C4 or architecture diagram, system context, API map, endpoint list, "show me the endpoints", status flow, state machine, allowed transitions, "what happens after X is approved", sequence diagram, request flow, how services call each other, microservice map, Mermaid diagram. Also writes documentation as a fact graph: each statement carries its source and a computed confidence, and a drift check fails CI when the code moves. Use to document a system, write architecture or onboarding docs, or explain how a system works.

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Build, inspect, audit, and refactor Blender Geometry Nodes systems for procedural models, instancing, modular effects, curves, scattering, flocks, data visualization, fields, simulation zones, and node-graph cleanup. Use whenever a Blender task specifically calls for Geometry Nodes, reusable procedural node graphs, node connections/layout, or a scalable procedural asset.

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Think and work like an expert Geographic Information Scientist (GIS). Use when a task calls for Geographic Information Scientist (GIS) judgment. Reasons from location, topology, scale, and positional uncertainty through PostGIS/GDAL pipelines, explicit EPSG/datum choices, kriging with cross-validated variograms, and ISO 19115/FGDC metadata while treating MAUP and ecological fallacy, Web Mercator area statistics, floating-point slivers and broken topology, and spatial-autocorrelation-inflated significance as first-class failure modes.

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Think and work like an expert Crystallographer. Use when a task calls for Crystallographer judgment. Reasons from reciprocal-space diffraction data, Bragg's law, and space-group symmetry through XDS/DIALS scaling, Phaser/SHELX phasing, Coot/Olex2 building, and MolProbity/checkCIF validation while treating merohedral twinning, wrong space groups, model-bias density unsupported by omit/polder maps, and R_free overfitting as first-class failure modes.

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Think and work like an expert Cryptographer. Use when a task calls for Cryptographer judgment. Reasons from IND-CCA/EUF-CMA games and tight reductions through AES-GCM/RSA-OAEP/ECDSA, ML-KEM/ML-DSA (FIPS 203/204), ProVerif/Tamarin/EasyCrypt, dudect constant-time, CAVP/ACVP and FIPS 140-3 CMVP—not pure number theory or vuln fuzzing.

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Think and work like an expert Cryptography Engineer. Use when a task calls for Cryptography Engineer judgment. Reasons from explicit threat models, vetted primitives, key hierarchy, and constant-time secret handling through STRIDE threat modeling, standards (RFC 8446 TLS 1.3, FIPS 203/204, Ed25519), test vectors (Wycheproof, NIST CAVP), and protocol verifiers (Tamarin, ProVerif) while treating nonce reuse in AEAD, padding/Bleichenbacher oracles, timing side channels, and weak-RNG keys as first-class failure modes.

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Think and work like an expert Computer Graphics Researcher. Use when a task calls for Computer Graphics Researcher judgment. Reasons from the rendering equation, Monte Carlo bias/variance, sampling theory, and BSDF energy conservation through pbrt-v4/Mitsuba 3 references, MIS/ReSTIR/path guiding, DXR 1.2 real-time stacks, 3DGS and NerfBaselines protocols, FLIP/ColorVideoVDP evaluation, OpenUSD/MaterialX/OpenPBR interchange, and ACES 2/OCIO color while treating unconverged references, unequal-time comparisons, denoiser and temporal-reuse bias, scene- vs display-referred color errors, and white-furnace energy failures as first-class failure modes.

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Think and work like an expert Biological Oceanographer. Use when a task calls for Biological Oceanographer judgment. Reasons from light-nutrient-grazing coupling, the microbial loop, and size-structured export through CTD/MOCNESS sampling, 14C and O2/Ar production with 234Th export flux, imaging and flow cytometry enumeration, and SILVA/PR2 metabarcoding while treating spatial patchiness, diel-migration tow aliasing, CDOM-biased chlorophyll algorithms, and eDNA-detection-as-abundance as first-class failure modes.

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Think and work like an expert Chemical Oceanographer. Use when a task calls for Chemical Oceanographer judgment. Reasons from seawater thermodynamics, carbonate-system coupling (DIC, TA, pH, pCO2), redox hierarchies, and tracer conservation on density surfaces through CO2SYS/seacarb with Dickson CRMs, Winkler oxygen, IRMS isotopes, GO-FLO clean trace-metal sampling, and GLODAP/SOCAT/GEOTRACES synthesis while treating organic alkalinity, headspace equilibration, pCO2-mooring biofouling, and trace-metal contamination as first-class failure modes.

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Automate Adobe After Effects workflows. Use when a user asks to script After Effects with ExtendScript or CEP, batch render compositions, automate motion graphics templates (MOGRTs), build render pipelines with aerender, create expressions for animations, manage project files programmatically, automate text and image replacements in templates, build data-driven motion graphics, integrate After Effects with CI/CD, or control AE via command line. Covers ExtendScript, CEP panels, expressions, aerender CLI, and template automation.

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Index a repository (local path or git URL) into Cognee's code graph and answer exact structural queries with no LLM calls: callers, dependencies, impact of changing a symbol, call paths, endpoints, re-index changes.

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Use whenever the user wants to find, rank, or shortlist directories and listing sites where they can submit an AI product — an AI tool, AI app, AI agent, or agent skill / plugin — to get backlinks, referral traffic, and discovery. Triggers on "where can I list my AI tool", "directories to submit my AI agent", "agent-skills directories", "best AI tool directories for backlinks", "where do I get my GPT/Claude app discovered", or "pull submission details for these AI-directory domains", even when described indirectly (we built an AI agent, where do we get it in front of people). Drives the ServiceGraph API (api.servicegraph.co) — a catalog of 1,000+ product directories enriched with Domain Rating, backlinks, and organic traffic. Defer to find-mcp-directories for MCP-server listings specifically, and to find-product-directories for general SaaS/software/app launches with no AI angle. Skip finding an AI consultancy/agency to hire (use find-ai-consultancy), comparing AI products ("ChatGPT vs Claude"), building an AI tool (do-the-work), and AI link-building *services*.

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Recover from stale RFDB nodes that survive `commit_batch` cleanup despite having their `file` field listed in `changed_files`. Use when: (1) re-running an enricher/orchestrator step but old data with the same file field stays in the graph, (2) `commit_batch(changed_files=[X], ...)` reports success but a query later still returns nodes with `file = X`, (3) you re-pointed structural nodes (e.g., DIRECTORY/FILE) from a synthetic file path to real file paths and the old synthetic-path nodes won't go away, (4) graph-stream / find_by_type returns a mix of "stale" and "new" nodes for the same logical entity. Root cause: `handle_commit_batch` calls `engine.find_by_attr({file: X})` to enumerate nodes-to-delete, but that query path returns only a PARTIAL set after compaction (L1 segments and the file→nodes index can desync). Workaround: enumerate stale nodes via the TS rfdb client `queryNodes({file: X})` (different code path that finds all of them) and call `deleteNode(id)` per node, then re-commit the intended state. Related: rfdb-manifest-l1-carryforward (same L1 family).

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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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Builds a hand-sculpted stop-motion CLAY ad on the Novoads REST API as a STORYBOARD: five to eight beats, each rendered from its own key frame, a storyteller narration laid into the gaps, a music bed, captions burned on, assembled locally with ffmpeg. Carries the genre's arc (named protagonist, inciting moment, social beat, quiet despair, sculpted clay infographic, discovery, transformation, resolution card), and also recreates a found clay ad by reading the reference video locally with ffmpeg and Whisper. Use for ANY clay or stop-motion ask at ANY length: "claymation ad", "stop-motion ad", "clay ad", "a quick clay ad", "plasticine characters", "make an ad like this clay one", or a reference video with sculpted clay characters in it. There is no one-call tier here, so ffmpeg is required. Not for the smooth 3D animated look (use pixar-ad, which covers every Pixar-style length), talking-head UGC (novoads-api), or a static image ad.

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Identify and exploit Insecure Direct Object Reference (IDOR) or Broken Object Level Authorization (BOLA) vulnerabilities specifically within GraphQL APIs. This skill focuses on manipulating node IDs, changing variables, and utilizing aliases to access unauthorized data.

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นักเขียนอักษรประดิษฐ์ — Thai + Latin calligraphy, hand lettering, signage, wedding invitation, lettering artwork

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Data structures and algorithms for AI agent episodic memory. Covers vector stores (HNSW, IVF, PQ), temporal indexing, knowledge graphs with triple stores, hierarchical summarization, forgetting curves, working/long-term/ procedural memory, and memory consolidation. Deep analysis of MemGPT/Letta, Zep/Graphiti, Mem0, and the Stanford generative agents memory architecture. Teaches the CS fundamentals behind how agents remember, retrieve, and forget. Activate on: "agent memory", "episodic memory", "vector search algorithm", "HNSW", "memory retrieval", "forgetting curve", "knowledge graph memory", "MemGPT", "Letta", "Zep", "Mem0", "memory consolidation", "temporal retrieval", "agent long-term memory", "memory layer". NOT for: conversation protocol design (use agent-conversation-protocols), agent infrastructure selection (use agentic-infrastructure-2026), building RAG pipelines (use ai-engineer).

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Route codebase-structure questions (who calls X, where used, change-impact) to an existing code-graph first: impact, tests-for, dead cheaper, never more precise; grep routine. Also 'call graph'.

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Use when you need blast-radius analysis, dependency graphs, cross-repo impact, breaking-change diff, or architectural overview of .NET workspaces. Keywords: blast radius, dependency graph, impact analysis, cross-repo, call graph, endpoint map, EF Core lineage, breaking change, daemon, reindex.

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Per-toolkit hardening audit loop for NV oOS Pro tools. Systematically scans each addons/pro/includes/tools/<toolkit> (and its plugins/nvoos-content-graph-pro mirror) for the recurring production failure classes — unguarded shell calls that fatal on exec-disabled hosts, calls to nonexistent client methods, string-assuming parsing of provider responses that may be arrays, provider enum/service mismatches, metric/source column drift that silently returns 0, secondary-table denominator gaps, the Chart.js fixed-height loop, misleading native-source errors, and silent import truncation that reports partial writes as success — then fixes, tests (Docker PHPUnit), and validates (phpcs both standards) before moving to the next toolkit. Use when asked to audit a toolkit, review the X tools for similar issues, do the same for the other toolkits, or continue the toolkit audit loop. The first case study (document-generation) found 3 fatal bugs + 1 broken regex; the food-beverage pass added classes 5–9.

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How to read submitted JetFormBuilder form data from a custom action, transform it (including %macro% replacement of admin-typed templates), call an external HTTP API, write the response back into the form context for downstream actions to use, and dispatch JFB events based on the API outcome. Use when building a custom action that integrates with a third-party service (LLM call, webhook, CRM, payment processor, geolocation lookup) and needs the action to behave as a node in a data-flow graph rather than a one-shot leaf. Triggers on mentions of "jet_fb_context", "update_request", "has_field", "get_value", "wp_remote_post" with form data, "macro replacement", or "API call from action".

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