Results for “poi”

Create an end-to-end customer journey map with stages, touchpoints, emotions, pain points, and opportunities to identify friction points and improve user experience.

Convert input into clean, structured, hierarchical bullet points for summarization, note-taking, and structured thinking.

Designs a points account system supporting multiple point types, independent expiration times, and FEFO (first-expired-first-out) consumption logic, including database schema, data flow, balance display, and partial consumption handling.

Exploit web cache mechanisms to serve malicious content to other users by poisoning cached responses through unkeyed headers and parameters during authorized security tests.

System Audit — entry point

分析故事情节点，识别关键情节与转折点。适用于深度分析情节结构、评估情节发展有效性

Write efficient C code with proper memory management, pointer handling, and POSIX compliance, including debugging and testing guidance.

Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.

Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.

Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.

Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.

Write efficient C code with proper memory management, pointer arithmetic, and systems programming best practices.

Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.

Runs a Trailmark summary analysis on a codebase to auto-detect languages, count entry points, and list dependencies.

Write efficient C code with proper memory management, pointer safety, and POSIX compliance, including debugging and testing guidance.

Write efficient C code with proper memory management, pointer handling, and POSIX compliance, including debugging and testing guidance.

Test vector stores for embedding inversion, cross-tenant leakage, and poisoning.

Process data with high-performance DataFrames using Polars' expression-based API, lazy evaluation, and parallel execution for ETL, analytics, and pandas migration.

PUA Pro extensions: self-evolution notes, compaction state continuity, KPI-style summaries, flavor switching, and feedback tools.

Personal investigator / people lookup skill. Deep background research on any person using public records, court documents, property records, social media, corporate filings, and web OSINT. Use when asked to look up, investigate, research, or find information about a person — including court records, traffic infractions, property ownership, career history, social media profiles, corporate affiliations, family connections, and contact details. Also use for "find everything about [person]", "background check", "dig up info on", "what can you find on", or any people-search request.

Provides C programming guidance for systems programming, covering memory management, pointer arithmetic, POSIX compliance, and debugging with valgrind and gdb.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

PUA Shot — compact all-in-one PUA reference for explicit injection into sub-agents or short sessions. Strong flavor, same evidence-first behavior.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Process tabular data with Polars' expression API, lazy evaluation, and parallel execution for fast in-memory analysis and pandas migration.

Use to check whether a conversation export, dataset or AI pipeline is leaking personal data that should have been redacted, and to measure how well the redaction actually works. Trigger for "is this export safe to share", "check our redaction", "can we use support transcripts for training", sending transcripts to a vendor or model, "is there PII in this dataset", or before opening support data to a wider audience.

Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.

Process tabular data with Polars' expression API, lazy evaluation, and parallel execution for faster pandas-style workflows.

Fine-tune and serve Physical Intelligence OpenPI models (pi0, pi0-fast, pi0.5) using JAX or PyTorch backends for robot policy inference across ALOHA, DROID, and LIBERO environments. Use when adapting pi0 models to custom datasets, converting JAX checkpoints to PyTorch, running policy inference servers, or debugging norm stats and GPU memory issues.

Give a decisive, project-grounded point of view in the subject's own shape: a graded verdict on an external-adoption question, a holistic take on a document, or a position on a user-supplied approach set. Use for a solo POV, a mid-session second opinion, a named-peer cross-check, any request to consult other models or reconcile their opinions, an `oracle` panel, or a correction-cost-gated proactive cross-check offer. Not for findings review (use ce-doc-review), neutral explainers, or generating options (use ce-ideate or ce-brainstorm).