Results for “iteration”

Synthesizes actionable feedback from validation results, confidence scores, and iteration triggers. Creates structured improvement guidance for re-execution. Activate on 'synthesize feedback', 'improvement suggestions', 'actionable feedback', 'iteration guidance', 'feedback generation'. NOT for iteration detection (use dag-iteration-detector) or convergence tracking (use dag-convergence-monitor).

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Synthesizes evidence-linked feedback from validation results, confidence evidence, and iteration triggers. Proposes bounded revision guidance for a stated acceptance failure. Activate on 'synthesize feedback', 'improvement suggestions', 'actionable feedback', 'iteration guidance', 'feedback generation'. NOT for iteration detection (use dag-iteration-detector) or convergence tracking (use dag-convergence-monitor).

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Analyze agent runs that fail before any work begins. Check iteration counts, tool use, logs, and outputs to identify startup failures, then direct investigation toward environment setup, input formatting, permissions, or resource limits.

• Investigating failed runs with zero iterations
• Checking startup errors across multiple agents
• Recording failures that require system review

Tracks iteration progress toward task completion goals. Monitors quality trends, detects plateauing, and recommends when to stop iterating. Activate on 'convergence tracking', 'iteration progress', 'quality trend', 'stop iterating', 'progress monitoring'. NOT for iteration detection (use dag-iteration-detector) or feedback synthesis (use dag-feedback-synthesizer).

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Identifies when task outputs require iteration based on quality signals, unmet requirements, or explicit feedback. Triggers appropriate re-execution strategies. Activate on 'needs iteration', 'retry needed', 'not good enough', 'try again', 'refine output'. NOT for feedback generation (use dag-feedback-synthesizer) or convergence tracking (use dag-convergence-monitor).

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Identifies when task outputs require iteration based on quality signals, unmet requirements, or explicit feedback. Triggers appropriate re-execution strategies. Activate on 'needs iteration', 'retry needed', 'not good enough', 'try again', 'refine output'. NOT for feedback generation (use dag-feedback-synthesizer) or convergence tracking (use dag-convergence-monitor).

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Develop applications through separate planning, building, and evaluation agents. The workflow tests the running app, scores its design and functionality, and feeds specific issues back into repeated development cycles with configurable quality thresholds and iteration limits.

• Turning a brief idea into an application specification
• Refining frontend design through separate evaluation
• Testing and improving full-stack application features

Run one iteration of a BMad unattended development loop, with optional route and review selections. The skill follows a generated workflow and reports a halt reason or command failure when execution cannot continue.

• Running one unattended development iteration
• Selecting the oneshot or full route
• Choosing none, quick, or thorough review

Review a sprint or milestone by comparing planned work with actual results. Summarize completion, estimation gaps, and blockers, then produce a retrospective with specific improvement actions, owners, and deadlines for the next iteration.

• Reviewing completed work at the end of a sprint
• Investigating estimation gaps and carried-over tasks
• Checking progress on previous improvement actions

Identify agent failures that happen before any work starts by checking iteration counts, tool use, artifacts, and logs. Classify these incidents as pre-execution failures and guide investigation toward environment setup, initialization, and resource limits.

• Investigating agent sessions with zero completed iterations
• Classifying failures before the first tool call
• Routing incidents to infrastructure or platform teams

Performs end-of-iteration review with quality grading, metrics, and trend analysis. Use at the end of each development iteration or sprint.

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🇺🇸 Your dev team ships features nobody asked for while user-reported bugs pile up for months. Operations blames engineering for ignoring users; engineering blames operations for not understanding technical constraints. This gives you the complete Product × Engineering × Operations alignment SOP — from unified backlog to 10-day sprint cadence to veto power rules. What's inside: • Dual-layer Kanban system (master backlog + sprint board with unified tagging) • 10-day sprint standard process (Day 1 dev → Day 6 testable build → Day 10 ship) • Issue template with reproducibility requirements (3x reported = auto-severe) • Tri-party alignment meetings (daily standup / sprint planning / sprint review) • Operations veto power on releases (P0 bug = block shipping) • User feedback → product iteration closed loop (beta testing + interview SOP) • Core metrics framework (acquisition → activation → retention → monetization → referral) • Technical debt management (20-30% sprint capacity reserved) • Ready-to-use templates: Bug Report, Sprint Planning, Responsibility Matrix Built from: Real product strategy meetings + beta testing frameworks. References Supabase sprint model, Manus/DeepSeek commercialization alignment. By @WeiYipei. 🇨🇳 你的研发团队在做没人要的新功能，用户反馈的 Bug 堆了三个月没人动。运营觉得研发不听用户，研发觉得运营不懂技术。这份 SOP 给你从统一看板到 10 天迭代节奏到一票否决权的完整产研运协同框架。 🇯🇵 開発チームは誰も求めていない機能を作り、ユーザーから報告されたバグは何ヶ月も放置。このSOPは、統一バックログから10日スプリント、リリース拒否権まで、プロダクト×エンジニアリング×オペレーションの完全な連携フレームワークを提供します。 🇰🇷 개발팀은 아무도 요청하지 않은 기능을 만들고, 사용자가 보고한 버그는 몇 달째 방치됩니다. 이 SOP는 통합 백로그부터 10일 스프린트, 릴리스 거부권까지 제품×개발×운영 완전 협업 프레임워크를 제공합니다. Triggers: "product ops" | "engineering operations" | "product development SOP" | "sprint planning" | "iteration management" | "cross-functional alignment" | "product engineering ops" | "dev ops collaboration" | "产研运协同" | "迭代管理" | "产品研发运营" | "プロダクト開発運営" | "제품개발운영"

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Autonomous iteration loop with dual-mode support. Standalone mode uses Stop hooks (RALPH_ACTIVE=1). Multi-agent mode uses router-managed iteration. Never traps the host/router session.

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Speed up Rust development iteration when `cargo build --release` takes 10+ minutes even for one-line edits. Use when: (1) every release rebuild takes minutes despite tiny edits, (2) Cargo.toml has `lto = "fat"` and/or `codegen-units = 1` in `[profile.release]`, (3) you want a production- shaped build for testing without paying the LTO cost on every iteration, (4) you suspect cargo is re-linking the whole binary instead of doing incremental work, (5) developing rfdb/grafema-orchestrator/large Rust binaries where full LTO is enabled for shipped builds. Adds a `fast` profile that inherits release but disables LTO, raises codegen-units, enables incremental compilation — first build still slow because it populates a fresh `target/fast/` dep cache, but every subsequent rebuild drops from ~13 min to ~13 s (≈60×).

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Integrate Iteration Layer APIs for document, website, image, and sheet processing. Composable APIs — Document Extraction, Website Extraction, Document to Markdown, Image Transformation, Image Generation, Document Generation, and Sheet Generation — share one credit pool and chain together into workflows.

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Build interface components with shadcn/ui, focusing on clear structure and accessibility so more people can use them. Pair the implementation work with the Stitch design loop to move from design iteration to working components.

• Building interface components with shadcn/ui
• Implementing components with accessibility in mind
• Pairing component development with Stitch design iterations

Run one cycle of autonomous task work in Claude Code: check progress, select and execute the next action, log the work, and schedule another cycle. Stop when all tasks are complete or the iteration limit is reached.

• Continuing work from a Claude Code task list
• Working through Markdown checklist items
• Running tasks managed through MCP

Generate 4–30 second videos with synchronized audio using ByteDance Seedance 2.5. Organize image, video, and audio references, write shot-by-shot prompts, and define continuity rules to keep characters and locations consistent across cuts.

• Generating short videos with synchronized audio
• Planning multi-shot scenes with consistent characters and locations
• Building video prompts from image, video, and audio references

Build text translation into Python applications with Azure AI Translator. Covers translation into multiple languages, language detection, transliteration to another writing system, dictionary entries, usage examples, and asynchronous requests for handling larger workloads.

• Add multilingual text translation to a Python app
• Detect the language of incoming text
• Convert text between writing systems

Guide a scoped coding task through specification, implementation, and review. Set acceptance criteria, verification checks, iteration limits, and approval gates, then correct identified gaps until the requirements pass or a stopping condition is reached.

• Build a small feature from specification through verification
• Modify a module against explicit acceptance criteria
• Repeat fixes and checks within an iteration limit

Work through GitHub pull request feedback by classifying findings, fixing code, running repository checks, and posting replies. With suitable permissions, the skill repeats Copilot reviews until the latest code is reviewed and every thread has an agent response.

• Address outstanding Copilot review comments
• Run repeated reviews on a completed pull request
• Explain declined suggestions and hand off design decisions

Evaluate a Claude Managed Agent against a written rubric, a set of checkable criteria, and guide improvements within a fixed attempt limit. After a version passes, prepare separate evaluation cases to check performance beyond the examples used for revision.

• Defining checkable criteria for agent outputs
• Improving an agent within a fixed attempt limit
• Testing a passing version on unseen cases

Plan projects that use large language models, from checking whether the task suits a model to designing processing stages. Estimate costs, choose single or multiple agents, and organize prototypes, structured outputs, and iteration.

• Checking whether a task is suitable for an LLM
• Designing a pipeline for batch analysis
• Estimating processing costs before development

Diagnose file access problems by checking directories, permissions, file headers, and line counts in parallel batches. Also reviews TypeScript imports, fixes duplicates and type-only imports, and checks module exports before retrying the failed operation.

• Investigate missing files, incorrect paths, and permission errors
• Review multiple source files in parallel batches
• Check CSS and configuration file headers and line counts