Results for “struct”

"Apply Giddens' structuration theory to analyze the duality of structure — how social structures are both the medium and outcome of the practices they organize. Use this skill when the user needs to bridge agency and structure in organizational or social analysis, explain how routines reproduce or transform institutional patterns, analyze the recursive relationship between action and structure, or when they ask 'do people shape institutions or do institutions shape people', 'how are these routines maintained', or 'where does change come from if structures constrain action'.".

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Restructure repeated LLM API requests so shared instructions and reference material can be cached, meaning reused across calls. Track cached input, write and storage costs, and response times to assess whether the changes actually save money.

• Reordering shared instructions in repeated API requests
• Estimating cache read, write, and storage costs
• Measuring cache hit rates and response times

Add or repair structured data, labels that help search engines understand page content. The skill selects suitable schema types, prepares JSON-LD code, and provides validation checks while distinguishing supported Google search features from retired ones.

• Add structured data to product or article pages
• Find and fix errors in existing markup
• Implement breadcrumb structured data

Plan a website's pages, hierarchy, navigation, URLs, and internal links. Produce page trees, visual sitemaps, URL tables, and navigation specifications to guide a new site or reorganize an existing one around visitor needs and business goals.

• Plan the page structure for a new website
• Reorganize navigation on an existing site
• Design URLs and internal links for a blog section

Organize the instructions, conversation history, and tool information an agent receives. Use the skill to clarify business rules, structure SKILL.md files for loading when needed, and distinguish external source material from instructions to reduce prompt injection risks.

• Reorganizing an agent's system instructions
• Reviewing SKILL.md structure and activation conditions
• Turning vague business rules into explicit decisions

Convert human-written CLAUDE.md instructions into a structured label format for AI agents. Use it to review lengthy rules, reduce instruction overhead, and prepare prompts for migration between AI tools while preserving the intended rules.

• Restructuring a lengthy CLAUDE.md
• Reviewing instruction token usage
• Preparing rules for migration between AI tools

Add structured logs, performance metrics, and traces that follow requests across Python services. Establish consistent log fields and request IDs so production failures can be investigated using recorded activity and service health signals.

• Adding searchable JSON logs
• Collecting service metrics with Prometheus
• Following requests across multiple services

Build reusable Terraform modules for AWS, Azure, GCP, and OCI. Organize cloud infrastructure as code with documented inputs, validation, usage examples, provider version constraints, and Terratest tests for consistent provisioning.

• Create reusable cloud infrastructure modules
• Standardize Terraform conventions across a team
• Connect network and database modules

Create a copilot-instructions.md file from an existing codebase. Identify technology versions, architecture, naming conventions, and testing practices, then turn observed patterns into project-specific guidance for GitHub Copilot without introducing unsupported assumptions.

• Create GitHub Copilot instructions for an existing project
• Document version compatibility requirements
• Capture established coding and testing conventions

Build threat actor profiles from public reports, social media, code repositories, and other intelligence sources. Correlates indicators, maps related infrastructure and attack techniques, and produces structured dossiers with confidence assessments about who may be responsible.

• Consolidating public information about an attacker group
• Comparing aliases, targets, and motivations across sources
• Mapping related domains, IP addresses, and infrastructure

Audit Terraform infrastructure definitions and planned changes for excessive permissions, public exposure, and missing encryption. Use security scanners and custom rules to produce actionable findings and add automated checks before cloud infrastructure is deployed.

• Reviewing Terraform modules and plans before deployment
• Adding security checks to Terraform CI/CD pipelines
• Enforcing organization-specific infrastructure rules

Create or fix structured data, code that describes page content to search engines. The skill selects suitable schema.org types, prepares JSON-LD markup, and provides placement instructions and validation checks for products, articles, FAQs, and other pages.

• Add structured data to product pages
• Describe articles and FAQs for search engines
• Fix errors in existing structured data

Plan team structure and hiring by defining needed roles, headcount, timing, and costs. Produce text-based org charts and prioritized hiring roadmaps, and identify structural risks such as excessive management overhead or dependence on one person.

• Plan required roles, headcount, and hiring dates
• Review reporting lines and team boundaries
• Set priorities and sequence upcoming hires

Audit, create, and fix structured data, the labels that help search systems understand web pages. Get JSON-LD code for articles, products, and other page types, plus validation findings and guidance on where to place it.

• Adding structured data to articles or product pages
• Investigating structured data errors in Search Console
• Auditing existing markup and prioritizing fixes

Audit website structure, navigation, URLs, and internal links to produce prioritized fixes. For a new site or redesign, create a site tree, URL specifications, and redirect mappings that clarify how pages connect.

• Auditing an existing website's structure
• Planning navigation for a website redesign
• Connecting related pages with internal links

Create CI/CD configurations, which automate build, test, and deployment steps, alongside Terraform infrastructure templates and Kubernetes deployment files. Generate health-check and rollback instructions to review before applying changes to cloud infrastructure or application environments.

• Setting up GitHub Actions or CircleCI pipelines
• Creating Terraform modules for AWS, GCP, or Azure
• Preparing blue/green or rolling deployments

Review skill and agent definitions for structural issues and whether their instructions meet expected behavior. Four modes cover structure, test specifications, category criteria, and coverage reports that reveal missing specifications or checks.

• Check one skill or all skills for structural issues
• Compare skill or agent instructions with a test specification
• Review definitions against category criteria

Review AI agent instructions for unnecessary rules, contradictions, repetition, and vague wording. Get recommendations on what to remove, merge, clarify, or load only when needed, plus an estimate of savings in tokens, the units models process.

• Cleaning up an overloaded CLAUDE.md
• Finding conflicting rules across instruction files
• Checking for redundancy after trimming instructions

Extend and audit TVM's T.ptx instruction table for GPU code generation. It guides instruction definitions, checks generated assembly with CUDA tools, and aligns comments and supported forms with a chosen PTX specification version.

• Adding PTX instructions or qualifiers to T.ptx
• Extending supported operand types
• Investigating ptxas certification failures

Analyze code structure with Trailmark to identify complex functions, trace input flow, assess impact across connected code, and locate privilege boundaries. The resulting JSON provides detailed evidence for deciding where to focus a code audit.

• Prioritizing code audit targets
• Tracing input flow and assessing impact
• Inspecting unresolved calls and type references

Predict the structure and binding of one defined protein, RNA, DNA, or ligand complex with Boltz. The workflow covers cost confirmation, job submission, result downloads, and summaries of structure and binding metrics.

• Predicting the structure of a defined molecular complex
• Docking one ligand to a protein
• Assessing protein–protein binding

Test whether an AI agent stores hostile instructions in persistent memory and follows them later. The skill uses marked test instructions and follow-up dialogue to document storage confirmations or changes in subsequent responses.

• Checking instruction handling in long-term memory
• Testing agents with profiles or persistent notes
• Verifying whether stored instructions affect later replies

Turn previously retrieved Jira requirements and Confluence documents into a structured implementation plan. Tasks are grouped into frontend, backend, and infrastructure work, with architectural reasoning, blocking dependencies, and risks paired with mitigation measures.

• Creating an implementation plan from Jira requirements
• Dividing work across frontend, backend, and infrastructure
• Identifying blocking dependencies between tasks

Predict three-dimensional structures of complexes containing proteins, RNA, DNA, and small molecules with Chai-1. Compare candidate structures using confidence scores and clash indicators, or run repeated predictions from Python to evaluate designed binders.

• Predicting antibody–antigen complex structures
• Evaluating protein–ligand binding structures
• Reassessing designed binders