「reports」の検索結果

Distill the current conversation into a structured note (decisions made, open questions, file pointers with line numbers, next 1–3 actions) and save to `quality_reports/session_logs/` before auto-compression. Differs from `/checkpoint` (explicit stop-point snapshot) and from auto-compaction (which truncates rather than distills). Use when context is approaching auto-compact threshold, when a long pipeline has accumulated many decisions, or when the user says "compress", "distil this session", "before we hit auto-compact", "structured handoff before context resets".

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Save a structured state snapshot before stopping or handing off. Captures the active plan, recent decisions, file pointers (with line numbers), open questions, and the next 1–3 actions into a checkpoint file under `quality_reports/checkpoints/`. Optionally proposes `[LEARN]` entries to add to MEMORY.md. Use when user says "checkpoint", "save state", "snapshot before I stop", "where am I", "wrap up the session for handoff", or before a long break / model switch / collaborator handoff. Companion to (NOT replacement for) the narrative session-log workflow.

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Stress-test a finding against the choices you did not make. Enumerates the discrete forks a competent analyst could have taken (measure definition, sample filter, control set, clustering level, weighting, functional form), runs the specification grid, and reports the distribution rather than a point estimate — then attacks the identifying assumption with named, computable sensitivity statistics. Use when the user says "is this robust", "challenge this result", "specification curve", "multiverse", "how sensitive is this", "what if I'd used a different measure", "stress-test my estimate", or before a result becomes a headline claim. NOT a reviewer of prose or code — it challenges the CLAIM.

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Use when someone asks to audit their AIOS, score the Four Cs, find stale paths or unlinked projects, compare AGENTS.md and CLAUDE.md, check Claude/Codex skill compatibility, or assess migration readiness. Automatically saves dated reports and tracks evidence-backed improvements across runs.

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Assess and migrate cross-cloud workloads to Azure with reports and code conversion. Supports Lambda→Functions, Beanstalk/Heroku/App Engine→App Service, Fargate/Kubernetes/Cloud Run/Spring Boot→Container Apps. WHEN: migrate Lambda to Functions, AWS to Azure, migrate Beanstalk, migrate Heroku, migrate App Engine, Cloud Run migration, Fargate to ACA, ECS/Kubernetes/GKE/EKS to Container Apps, Spring Boot to Container Apps, cross-cloud migration.

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Turn a user-owned coverage CSV and reviewed press-clip captures into an honest, source-linked earned-media dashboard and a motion-designed highlight reel (MP4) that scrolls each real article to the client's sentence and highlights it. Use for coverage reports, earned-media dashboards, campaign recaps, or coverage videos; requires local files and composes press-clip instead of scraping articles itself.

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Performs systematic root cause analysis to identify the true source of bugs, errors, and unexpected behavior through structured investigation phases — not just treating symptoms. Use when a user reports a bug, crash, error, or broken behavior and needs to debug, troubleshoot, or investigate why something is not working; especially for complex or intermittent issues across multiple components. Applies the Five Whys method, hypothesis-driven testing, stack trace analysis, git blame/log evidence gathering, and causal chain documentation to isolate and confirm root causes before applying any fix.

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Full-sweep mode: runs a unified analysis across all quality dimensions — code decay, architecture, tech debt, and test quality — then applies fixes directly to the codebase. Safe changes are auto-applied; risky changes are confirmed before execution. Drawing on twelve classic engineering books. Triggers when: user wants to "fix everything", "sweep the codebase", "auto-fix all issues", "clean up the whole project", or asks for a single command that both diagnoses and remediates quality problems. Do NOT trigger for: read-only audits or health reports where the user only wants findings without code changes; single-dimension reviews (use the focused skill instead: brooks-review / brooks-audit / brooks-debt / brooks-test); server health checks, HTTP /health endpoints, Kubernetes probes, database health, or application uptime.

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Creates source-grounded internal or external weekly engagement status reports with optional Outlook draft creation.

日本語の概要は準備中です。原文の説明を表示しています。

Gangtise (岗底斯投研) OpenAPI skill suite installer and diagnostic tool. One-click install 19 official skills (data, research, utility), configure accessKey/secretAccessKey, run health diagnostics. Trigger when user mentions Gangtise, 岗底斯, any gangtise-* skill, credential setup, or reports errors like 'token is invalid' / '接口地址错误'.

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Migrates Claude Code personal memory (the per-project memory/ directory) into tool-agnostic reference docs so other AI CLIs that auto-load AGENTS.md (Codex primarily) can read the same user profile and preferences. Use when the user says "migrate my memory", "my memory is locked to Claude Code", "make Codex/Cursor read my profile", or reports memory has grown bloated with content that should be shared across tools. Also use it to retire a project's auto memory entirely (turn it off, move everything into documents, archive the directory).

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Creates formatted Excel reports with openpyxl, parses complex xlsm financial models with stdlib zipfile+xml when openpyxl fails, and controls Excel windows on macOS via AppleScript. Reconstructs images or scans of paper forms as editable XLSX files with printable layouts.

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Optimizes or restructures CLAUDE.md/AGENTS.md with progressive disclosure and zero information loss. Use when the user asks to optimize, audit, 精简/瘦身/重构, or split instruction files, asks for their best practices (最佳实践), sees Memory files taking a large share of /context, reports rules in instruction files being ignored, or a task starts moving instruction sections. Not for generic task drift unless instruction files are in scope; not for moving memory entries into docs (use claude-code-ops-router).

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Gated checklist to choose or review a library, framework, storage, data format, model, build-vs-buy or architecture. Run favorites-search before external research when installed. Compare candidates and trade-offs; select within authorization or return user-owned choices. Use for 用哪个 / 选什么框架 / 要不要自建 / A 还是 B / 这个方案行不行 and before committing to one. Research reports → deep-research.

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Operates GitHub via gh CLI and REST/GraphQL — PRs, issues, Actions, repos, collaborators, org permissions, 2FA — with explicit target, authorization, and independent readback. Use when a write reports success but state didn't change, or choosing gh/REST/GraphQL/UI-only. Not for local Git recovery (use git-safety-net), maintainer PR review (use github-review-pr), or upstream contribution (use github-contributor).

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This skill should be used when comparing two videos to analyze compression results or quality differences. Generates interactive HTML reports with quality metrics (PSNR, SSIM) and frame-by-frame visual comparisons. Triggers when users mention "compare videos", "video quality", "compression analysis", "before/after compression", or request quality assessment of compressed videos.

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Creates reusable, source-traced research reports and coordinates provider/mode lanes with original exports. Use for 深度研究, 调研报告, literature reviews, market or company research, and ChatGPT/Kimi/UniFuncs research routes. Technology choice uses tech-selection; competitor code uses competitors-analysis.

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Set up and send technical status notifications through WeCom (Enterprise WeChat) webhooks. Use this skill whenever the user needs to send notifications, alerts, backup completion reports, or status updates via WeCom; when they mention 企业微信, 企微机器人, webhook, or alerting; or when a message needs to be clear, unambiguous, and technically precise rather than vague or condescending.

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Sets up QA testing processes: test strategies, Google Testing Standards test cases, P0-P4 bug tracking, quality metrics, progress reports, autonomous execution via master prompts, and OWASP security testing, with third-party QA handoff docs. Use when establishing QA infrastructure, writing test cases, executing test plans, or tracking bugs. Not for auditing an already-rendered UI (use frontend-visual-qa).

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Co-creates a personal investment-research LLM Wiki (Karpathy's pattern) by interviewing the user for THEIR OWN analysis framework, not a template — a living CLAUDE.md of pure markdown + wikilinks, no RAG in place of compilation. Use to build a compounding 投研第二大脑 / 投研知识库 / 个人投研 wiki, ingest research reports / earnings calls into an existing wiki, or run post-earnings prediction→fulfillment reviews.

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Decide which of your recurring rituals to put on autopilot — and which to keep manual. Use when asked what to automate, how to set up recurring AI runs, which reports or briefings could run on a schedule, or to design an automation charter for a team. Produces a ritual inventory with automate/assist/keep-manual calls, guardrails per ritual, and a rollout order.

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Run automatic SPICE simulations on subcircuits detected from KiCad schematic analysis — validates filter frequencies, divider ratios, opamp gains, LC resonance, and crystal load capacitance. Supports ngspice, LTspice, and Xyce (auto-detected). Generates testbenches, runs batch mode, produces structured pass/warn/fail report. Use when the user asks to simulate, verify, or validate any analog subcircuit — RC filters, LC filters, voltage dividers, opamp circuits, crystal oscillators. Also for "simulate my circuit", "run spice", "verify with simulation", "check my filter cutoff", "does this divider give the right voltage", "what's the bandwidth of this opamp stage". Consider suggesting simulation during design reviews when the schematic analyzer reports simulatable subcircuits and a SPICE simulator is available.

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Behavioral guardrails for Codex coding work based on common user complaints. Use when Codex is asked to implement, modify, debug, review, test, or operate on a codebase and should avoid unsafe scope expansion, stale edits, fake completion, brittle edits, shallow debugging, superficial patch-on fixes, one-off special-case code, short-term design choices that hurt maintainability, blindly following incorrect user assumptions, poor dependency choices, generic product or UI output, over-mocked tests, noisy approvals, verbose status reports, or leaking internal reasoning into project artifacts or user-facing UI.

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Use when a vulnerability or security report arrives for triage, when assessing a CVE/RCE/OGNL/injection claim against the code, or when drafting a reply to a security researcher — to research the claim from source without trusting the reporter and without fabricating your own facts.

日本語の概要は準備中です。原文の説明を表示しています。