Detects whether a task concerns software development or research and strategy by examining the request and project files. Workflow skills can use the result to choose agents, output formats, and review criteria suited to the work.
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Add GitHub Copilot CLI as an optional research provider in Claude Octopus workflows using an existing Copilot subscription. The skill covers authentication, model selection, and skipping Copilot when unavailable; each prompt consumes a premium request.
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Estimate remaining workflow costs from the average spend of completed steps. Show actual spending and projected totals in the status line, warn about configured budget overruns, and suggest a budget profile when estimated costs are high.
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Audit changed code by tracing execution paths and matching them to existing tests. Show coverage gaps and test quality, then generate tests for high-priority gaps using the project's current framework, helpers, and naming conventions.
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Investigate reproducible bugs by recreating symptoms, testing one possible cause at a time, and checking fixes in both a simplified test case and the original scenario. Retry limits keep unsuccessful fixes from continuing unchecked.
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Compare two to four viable approaches against your requirements and constraints. See each option’s benefits, drawbacks, effort, risk, and ease of reversal, alongside a reasoned recommendation and next steps for the option you choose.
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Turn a brief, notes, or research into a presentation tailored to the audience, length, and tone. Review the slide outline first, then export an approved version as a PowerPoint file, with optional research when needed.
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Turn Markdown research and strategy outputs into office documents for sharing or presentation. Choose formats such as DOCX, PPTX, or PDF, organize sections for the audience, and apply consistent headings, tables, and slide formatting through document-skills.
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Bring project Markdown documentation into line with code changes. Update factual references such as paths, versions, and counts, check consistency and document links, and reflect the documentation work in the pull request description.
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Diagnose Claude Octopus installation and runtime problems across 15 categories, including provider authentication, configuration, hooks, and scheduling. Get a readable or JSON report, investigate specific areas, and review proposed fixes before approving changes.
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An early-stage framework for documenting an existing product’s design and architecture. Command parsing, output setup, and metadata generation are implemented; extracting colors, components, APIs, and architecture remains in progress or planned.
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Run a build-and-evaluation pipeline from a natural-language specification. Generate scenarios, implement the project, test scenarios withheld during implementation, and report scores against a target with failures and suggested next steps.
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Sort incoming issues and pull requests, verify their claims, and assign clear triage states. Record missing information, decisions needed, and actionable handoff notes so maintainers can see which items are ready for work.
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Record the goal, success criteria, boundaries, and constraints of a complex task in a persistent document. Define human and AI responsibilities, consult the record during work, and check the final result against the original intent.
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Run repeated rounds of code fixes, performance improvements, or other refinements with defined goals and progress tracking. Evaluate each round, stop when appropriate, and optionally use numeric measurements to keep improvements or roll back regressions.
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Override automatic work-context detection when research or writing is treated as software development. Keep workflows focused on market analysis, strategy, and documents throughout a session, or switch back to development mode or automatic detection.
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Turn a rough request into a structured AI prompt with a clear goal, output format, and constraints. For complex work, add smaller tasks, separate creator and reviewer roles, and explicit checks for accuracy and uncertainty.
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Coordinates multiple AI providers to research, define, implement, and validate development tasks. It supports parallel task decomposition, comparison of proposed solutions, cross-model critique, and quality checks that feed into combined reports and final deliverables.
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Create a product requirements document for a new feature or product. Clarify users, problems, goals, and constraints, then organize prioritized requirements, acceptance criteria, implementation phases, and risks into a structured document for AI-assisted development.
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Examine an existing plan, decision, or design through one question at a time, each with a suggested answer. Clarify assumptions, contradictions, and dependencies, then summarize agreed decisions, needed changes, and unresolved blockers.
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Test one risky assumption through a prototype with an agreed deadline, hypothesis, and success signal. Record observations and the source revision, then return a keep, discard, or inconclusive verdict with the status of each artifact.
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Resume a previous workflow after a new conversation or context reset. Read saved project state and handoff notes, summarize recent progress and blockers, and identify the appropriate next action for planning, implementation, or delivery.
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Evaluate feedback from reviewers, CI bots, or other AI agents against the actual code and requirements. Apply valid fixes one at a time, verify each change, and explain disagreements using evidence from callers, tests, or existing conventions.
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Apply safeguards when analyzing external articles or posts. Validate URLs, limit fetched content, label source text as untrusted data, and clean analysis output so embedded instructions are treated as material rather than commands.
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