Use when the user reports a bug they can't reproduce, asks where to start debugging, or mentions a Heisenbug / production-only failure. Drives the observe→hypothesize→predict→test→iterate scientific method.
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概要と使いどころ
Use when the user reports a bug they can't reproduce, asks where to start debugging, or mentions a Heisenbug / production-only failure. Drives the observe→hypothesize→predict→test→iterate scientific method.
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。
Audit a skill by running a paired probe — the same task once with the skill loaded and once without — segment both traces into goal-directed phases, align phases, and emit a SIP report (surface anchoring, template copy, excess planning, task recovery, off-task artifact). Use whenever a skill is created, modified, or proposed for retirement. Pass-rate is BLIND to most skill effects: CTA (arxiv 2605.11946v1) shows a single skill can produce 522 measurable behavioural changes across 49 tasks while pass-rate moves only +0.3%. Triggers: "audit this skill", "is this skill helping", "retire skill", "before shipping skill", "behavioural impact of skill X", or any skill review event.
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。
Use when parallel agents in a convoy or across git worktrees hit a write conflict on shared state — a git tree, a config, or a shared document — and you must decide whether the conflict is semantically real. Classifies each conflicting hunk as independent (keep both), redundant (pick one), or a genuine clash (escalate), instead of blind locks, abort-and-retry, or escalate-everything. Sits ABOVE refinery-merge and NEVER blind auto-merges: it wraps an LLM judgment, defaults to escalate on any uncertainty, and unconditionally escalates any hunk touching .planning/, config, credentials, or safety-critical paths. Backed by CoAgent (arxiv 2606.15376v1). Triggers on write conflicts between parallel agents on shared repo state.
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。
Comprehensive gh CLI reference — issues, tasks, PRs, repos, branches, Actions, search, and project board. Use whenever interacting with GitHub.
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。
Bootstrap and sync GitHub labels and milestones idempotently. Use when setting up a new repository or syncing label definitions.
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。
Audit code changes against Karpathy's 4 principles (Think Before Coding, Simplicity First, Surgical Changes, Goal-Driven Execution). Auto-called after Phase 5 IMPLEMENT; can also be invoked manually. Produces scored compliance report and blocks advancement if threshold not met.
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Run ship-safe security and quality audit on the current project. Executes npx ship-safe audit . and reports findings by severity. Use before shipping any feature or PR.
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Audit a MaaFramework/Maa-series project's Git history to learn how Pipeline JSON, interface options, Python AgentServer CustomAction code, and related data tables evolved. Use when asked to review a Maa project from initial commit through a target commit, map `action: Custom` pipeline nodes to `@AgentServer.custom_action(...)` implementations, find pipeline/custom/option patterns or breakages, and produce a report plus skill-improvement recommendations.
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Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.
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Interact with Bitbucket repositories and pull requests using the BITBUCKET_TOKEN environment variable. Use when working with code hosted on Bitbucket or managing Bitbucket resources via API.
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Interact with Azure DevOps repositories, pull requests, and APIs using the AZURE_DEVOPS_TOKEN environment variable. Use when working with code hosted on Azure DevOps or managing Azure DevOps resources.
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。
Persist and retrieve repository-specific knowledge using AGENTS.md files. Use when you want to save important information about a codebase (build commands, code style, workflows) for future sessions.
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。
Claim the AI bounty on tDVV by delegating to the canonical repo SKILL and its branch docs; this public skill is AA/CA only and requires explicit write confirmation.
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。
Retired. Reporting feedback and sharing a session are documented by the CLI itself: run `deepline feedback send --help` and `deepline sessions send --help`. Kept only so installed CLIs that still list this skill keep syncing.
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Deprecated alias. This skill was renamed to `deepline-scoring`. Use when a user or script still invokes `/niche-signal-discovery`: immediately load and follow the `deepline-scoring` skill instead. Triggers: ICP analysis, niche signals, won vs lost analysis, differential signals, signal discovery, ICP signal report, account scoring signals, lead scoring, first-party signals, buyer signals.
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ACCESS-GATED beta. Deepline Monitors are provider event feeds (job posts, email replies, funding, intent) that stream into your warehouse and trigger plays. Only use if you have monitor access: run `deepline monitors status` first; if it reports no access, do NOT use this recipe — tell the user to contact the Deepline team.
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DRAFT. Build anonymizable host-prep one-pagers for must-meet guests at an in-person event: rank, enrich, light research, warm-intro angles, PDF pack. Not installed by deepline skills. No real customer data in repo samples.
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This skill should be used when validate-chunk reports test failures specifically, when the user says "tests are failing", "figure out what's wrong with the tests", "fix the failing tests", or when test assertions don't match expected output after chunk implementation. Triages whether the test or the implementation is wrong and fixes the correct one.
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This skill should be used when validate-chunk reports errors or failures, when the user asks to "fix these errors", "resolve validation issues", "refine this chunk", or when specific build, lint, or type errors need surgical fixes. Makes precise, targeted edits to resolve specific validation issues without over-engineering.
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Opens a deliverable (talk, course module, paper, book chapter, or referee report) for AI-assisted work across sessions. Interviews the author for the manifest, then scaffolds deliverable.yml, an append-only HANDOFF.md, a numbered planning/ wiki with open questions, an inbox/ for dictated braindumps, a gitignored checks/, and the house deck template for talks. Use when starting deadline-driven work that spans sessions, or when asked to open a deliverable, set up a talk, paper, or module for the pipeline, or make a manifest. Not for one-off tasks.
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Use when working in a repository that uses bd or Beads for durable project task tracking, issue dependencies, blocker management, multi-session handoff, or shared work memory. Trigger when the user asks to find ready work, claim or close tasks, create follow-up work, inspect blockers, recover project context, or choose between local planning and persistent project tracking.
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Use when the primary outcome is creating a new portable Agent Skill directory from one local documentation file, documentation directory, or Git repository, including mixed text and capability-gated binary sources that require exhaustive source-to-output accounting.
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Start a local Git rebase when the user explicitly requests replay of a named source ref, or of the current branch, onto a named target, including a rebase-then-push request, which carries exact-lease publication to the branch's own remote destination, or continue or abort an active rebase. Use only when local history replay will start or is active; do not use for merge-based branch updates, repository merge settings, pull-request or merge-request merging, or push-only requests.
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。
Use when debugging software, investigating incidents, diagnosing flaky tests, or analyzing performance regressions — enforces structured observation recording with evidence IDs, causality validation, and verification gates to prevent correlation-causation pollution. Use when an agent might otherwise summarize or speculate instead of reporting observed evidence.
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。