Results for “patching”

Investigate how transformer language models produce predictions with TransformerLens. This skill guides inspection of intermediate values and attention patterns, plus experiments that replace internal values to test their effects and identify components involved in model behavior.

• Inspecting attention patterns and intermediate values
• Testing output changes by replacing internal activations
• Analyzing attention head contributions to predictions

Investigate why a PyTorch model behaves a certain way by changing its internal values with pyvene. The skill guides experiments that swap or remove activations, train interventions, compare outputs, and save or share intervention configurations.

• Locating model components that affect an output
• Swapping activations to test behavioral hypotheses
• Training interventions to investigate causal structure

Investigate how transformer language models produce predictions with TransformerLens. This skill guides inspection of intermediate values and attention patterns, plus experiments that replace internal values to test their effects and identify components involved in model behavior.

• Inspecting attention patterns and intermediate values
• Testing output changes by replacing internal activations
• Analyzing attention head contributions to predictions

Guides experiments that change internal values in PyTorch models to test what causes their behavior. Uses pyvene to swap or remove activations, locate influential components, train interventions, and save experiments for reuse.

• Locating model components that affect an answer
• Comparing outputs after swapping internal activations
• Training interventions to investigate causal structure

Investigate how transformer language models produce predictions with TransformerLens. This skill guides inspection of intermediate values and attention patterns, plus experiments that replace internal values to test their effects and identify components involved in model behavior.

• Inspecting attention patterns and intermediate values
• Testing output changes by replacing internal activations
• Analyzing attention head contributions to predictions

Plan, implement, or review dispatching parallel agents work in an existing codebase with compatibility, security, and verification controls. Use when the user explicitly requests dispatching parallel agents work.

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Coordinate coding projects through Claude DevFleet by splitting work into dependent tasks and dispatching Claude Code agents in separate Git working directories. Monitor progress, manage automatic task sequencing, and review structured reports of changes, tests, and errors.

• Splitting a coding project into dependent tasks
• Running coding agents in separate Git working directories
• Monitoring concurrent development tasks

Implement Azure Cosmos DB document operations in Rust using its NoSQL SDK. The skill covers authentication, database and container clients, creating and reading records, replacing or patching fields, and deleting items with partition keys.

• Connecting a Rust application to Azure Cosmos DB
• Creating and reading documents
• Replacing documents or patching selected fields

Inspect executable files from the command line with radare2, starting with file details, strings, and imported functions. Trace code through disassembly, compare binaries, automate inspections, or apply explicitly requested patches with verification.

• Inspecting an unfamiliar executable file
• Finding the function that uses an error message
• Comparing two versions of a binary

Dispatches due Xiaohongshu tasks already locked in the operations dashboard to their assigned account workers. It checks task identifiers, records delivery failures, and continues dispatching other tasks without operating the browser or changing content.

• Dispatching due tasks to assigned account workers
• Continuing other deliveries when one task fails
• Checking how scheduled tasks should be executed

End-to-end methodology for reproducing AND patching publicly disclosed, already-fixed vulnerabilities: sourcing the advisory and the fix commit, reading the patch diff, rebuilding a pinned offline lab, building a vulnerable-vs-patched contrast harness with proper controls, minimizing the trigger, designing and validating the fix, and writing it up as a blog post or whitepaper. Use this skill whenever the user wants to reproduce, demonstrate, understand, teach, or write about a known vulnerability or security incident: "reproduce this CVE", "build a repro for", "how did EchoLeak / Log4Shell / the postmark-mcp package actually work", "show me how this exploit worked", "write a blog post about this vulnerability", "set up a lab for CVE-XXXX", "pull the NVD/CVE/OSV details", or "make a PoC I can publish". Use it just as eagerly for the patching half: "how should this be fixed", "is this patch correct", "what would have caught this", "review this security fix", "write a regression test for this CVE", "how do I backport this", or "what's the right fix for this bug class" - even when the user never says the word "reproduce". Reach for it on vague asks like "help me understand this security advisory", "I want to write about this incident", or "can we test whether we were vulnerable" when a disclosed vulnerability is in play. This skill only handles ALREADY-PATCHED, publicly disclosed issues and refuses zero-day discovery, live targets, and weaponization.

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Runs servers and corporate systems — patching, configuration baselines, change control, capacity, and the routine that prevents incidents. Use this to establish a patching cadence, standardize server configuration, plan a maintenance window, decide change control for infrastructure, or clean up systems that have drifted from any known state.

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Use when legacy prompts or older framework flows reference `dispatching-parallel-agents` and you need the modern runtime to resolve that capability cleanly.

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Bypass the Windows Antimalware Scan Interface (AMSI) using memory patching, reflection, and obfuscation techniques. Execute undetected PowerShell, VBScript, JScript, and .NET assemblies in-memory without triggering Microsoft Defender or third-party AV/EDR solutions. Use this skill during Red Team engagements when loading offensive tools (Mimikatz, Rubeus, SharpHound) in memory on defended Windows endpoints.

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Fornece orientação para pesquisa de interpretabilidade mecanística usando TransformerLens para inspecionar e manipular internals de transformers via HookPoints e caching de ativações. Use ao fazer engenharia reversa de algoritmos de modelos, estudar padrões de atenção ou realizar experimentos de activation patching.

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Fornece orientação para realizar intervenções causais em modelos PyTorch usando o framework de intervenção declarativa do pyvene. Use ao conduzir rastreamento causal, activation patching, treinamento de intervenção de intercâmbio ou testar hipóteses causais sobre o comportamento do modelo.

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Use multiple Claude agents to investigate and fix independent problems concurrently

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Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching experiments.

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Provides guidance for performing causal interventions on PyTorch models using pyvene's declarative intervention framework. Use when conducting causal tracing, activation patching, interchange intervention training, or testing causal hypotheses about model behavior.

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Assign independent bugs or test failures to separate agents that work at the same time. Define each agent’s scope and expected report, then check for conflicting changes and run the full test suite before integrating fixes.

• Investigating test failures with unrelated causes
• Fixing independent problems in separate subsystems
• Defining focused tasks for multiple agents

Track pull requests opened by a Paperclip instance, explain their purpose, and assess whether their latest changes are ready to merge. Dispatch preparation work for unresolved problems and publish an evidence-based report without merging anything.

• Reviewing readiness across an instance's open pull requests
• Dispatching preparation work for failing checks or conflicts
• Checking readiness again after fixes

Consult a field reference for slide JSON, the structured data behind each page. It explains where content and styling live, how edits are validated, and why a saved change may display differently or have no visible effect.

• Finding the field that controls text color or fonts
• Investigating rejected slide edits
• Diagnosing saved changes with no visible effect

Guide slide edits with concrete rules for text size, spacing, alignment, and color contrast. Use it when replacing content or adjusting individual elements to keep pages readable and consistent with their existing design.

• Replace slide text without overflowing its box
• Improve contrast between text and its background
• Align cards and adjust spacing consistently

Find and edit specific fields in OpenMAIC classroom documents. This skill maps pages, content, and playback actions to their data locations, guides small changes, and checks saved results, with references for quizzes, interactive content, and projects.

• Locate the field behind classroom text or narration
• Correct quiz options and answers
• Replace a small passage in interactive HTML