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cccskills

「candidate」の検索結果

660 件 ・ 関連度順

概要と使いどころ

Consolidate the td-trend-scout reports under `_workspace/hype-scout/` into one prioritized HYPE_TOOL_BACKLOG.md — dedupe trends across surfaces, vet each candidate against the real tdmcp codebase (layer fit, operator coverage, bridge work), rank by Hype × Build-Ease, and emit a 'Ready for tdmcp-pipeline' top-5. Use when a td-hype-synthesizer agent is consolidating scouts at the end of the tdmcp-hype-scout harness.

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。

Pantani/tdmcp502026年8月16日 更新

ad-recon

無料

Active Directory reconnaissance with or without credentials: user/group/computer enumeration, ACL/delegation, ADCS, modern Windows LAPS, BloodHound, Server 2025/dMSA/Ghost SPN candidates, and trust mapping. Recon only — do not exploit Kerberoast-to-DA, DCSync, or change passwords. Operator may select /ad-attack after cards are ready.

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。

pale-knight/redteam-skill502026年8月23日 更新

level-up

無料

Use weekly to find and ship one new automation. Walks the 3Ms interview — Mindset (find the candidate) → Method (scope one) → Machine (build it). Trigger on "let's level up", "what should I automate next", "find me leverage this week", or as a Friday ritual. One run = one shipped artifact.

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。

alirezarezvani/gaios492026年6月7日 更新

Use when the user says 'find old content', 'what is stale', 'what needs refreshing', or 'what should i archive'. Categorizes pages and posts as fresh, aging, stale, or archive-candidate by age, traffic signal, and internal link count, with a refresh, redirect, or archive call per item.

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。

respira-press/agent-skills-wordpress462026年9月13日 更新

Research a topic to support a decision, three ways: draft a research prompt for the user to run in their own tool (ChatGPT, Gemini, Grok, Perplexity, …), turn a finished research report into a short summary with cited sources that other skills can use directly, or run the research here with parallel web searches. Built-in research types: market, domain, technical, competitive, user-voice, academic-lit; also supports choosing between candidates, and custom types via overrides. Use when the user says "deep recon", "research this", "draft a research prompt", "process this research report", "market research", "domain research", "technical research", "competitor research", "literature review", or "help me choose between"

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。

skyf0xx/hedgehog452026年10月13日 更新

Evaluates bolt-on acquisitions for existing platforms with strategic fit, synergy quantification, and return contribution analysis. Use when screening add-on targets, building platform acquisition strategies, or modeling tuck-in economics.

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。

CaseMark/skills442026年9月9日 更新

Detect and exploit subdomain takeover via dangling DNS records pointing to deprovisioned cloud services (S3, GitHub Pages, Heroku, Azure, Shopify, AWS CloudFront, etc.). Use after subdomain enumeration to identify takeover candidates.

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。

0xGhostCAT/claude-ai-cyber-security-skills422026年6月3日 更新

Step 3 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the literature search strategy from outline.json — discover candidate papers via web search, verify them through Semantic Scholar (Levenshtein > 70 fuzzy title match, temporal cutoff, dedup by paperId), build a BibTeX file, and draft Introduction + Related Work using ≥90% of the verified pool. Runs in parallel with the plotting-agent. TRIGGER when the orchestrator delegates Step 3 or when the user asks to "find citations for my paper", "draft the related work", or "build the bibliography".

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。

woodfishhhh/EZ_math_model422026年7月28日 更新

Use when EZ_math_model model selection is unclear after the modeling decision tree, the problem spans multiple domains, or modeler needs several candidate approaches before writing modeling_plan.md.

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。

woodfishhhh/EZ_math_model422026年7月28日 更新

Audits Claude Code repositories. Two-phase workflow — Phase 1 sweeps 14 hygiene categories (permissions, hooks, CLAUDE.md bloat, Skills hygiene, process-abstraction, plus structural) and an optional 7-layer leak check. Phase 2 executes [APPROVED] markers from the report file. Use for repo cleanup, pre-distribution sanity, post-feature hygiene, environment audit, process-abstraction discovery. Trigger on "audit my CC repo," "sweep my repository for hygiene," "check this CC environment," "find process abstraction candidates," "review my CLAUDE.md," "clean up my .claude directory," "pre-distribution hygiene check," "find layer leaks in my CC setup." Routes structural findings to rootnode-cc-design REMEDIATE. Composes with rootnode-critic-gate. CC-only — does not scan Claude Projects. Do NOT use for building a Skill (use rootnode-skill-builder), compiling a prompt (use rootnode-prompt-compilation), scoring a single prompt (use rootnode-prompt-validation), or auditing a Project (use rootnode-project-audit).

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。

drayline/rootnode-skills402026年9月14日 更新

Design and execute A/B tests for ML models in production using traffic splitting, statistical significance testing, and canary/shadow deployment strategies. Measure performance differences and make data-driven decisions about model rollout. Use when validating a new model version before full rollout, comparing candidate models trained with different algorithms, measuring business metric impact of model changes, or when regulatory requirements mandate gradual rollout.

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。

pjt222/agent-almanac372026年10月13日 更新

Plan a software release cycle with milestones, feature freezes, release candidates, and go/no-go criteria. Covers calendar-based and feature-based release strategies. Use when starting planning for a major or minor version release, transitioning from ad-hoc to structured release cadence, coordinating a release across multiple teams or components, defining quality gates for a regulated project, or planning the first public release (v1.0.0) of a project.

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。

pjt222/agent-almanac372026年10月13日 更新

Grade a trading card using PSA, BGS, or CGC standards. Covers observation-first assessment (adapted from meditate's unbiased observation), centering measurement, surface analysis, edge and corner evaluation, and final grade assignment with confidence interval. Supports Pokemon, MTG, Flesh and Blood, and Kayou cards. Use when evaluating a card before professional grading submission, pre-screening a collection for high-grade candidates, settling condition disputes between buyers and sellers, or estimating the grade-dependent value spread for a card.

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。

pjt222/agent-almanac372026年10月13日 更新

Form a coherent gestalt — the whole that is more than the sum of its parts — from the panoramic perception produced by expand-awareness. Maps tensions and resonances between domains, identifies the emergent figure from the ground of multiple perspectives, tests the candidate whole for premature closure, and articulates the insight in a single sentence no single domain could have produced. Use after expand-awareness has surfaced raw multi-domain perception and before express-insight communicates the result.

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。

pjt222/agent-almanac372026年10月13日 更新

Create a Work Breakdown Structure (WBS) and WBS Dictionary from project charter deliverables. Covers hierarchical decomposition, WBS coding, effort estimation, dependency identification, and critical path candidates. Use after a project charter is approved, when planning a classic or waterfall project with defined deliverables, breaking a large initiative into manageable work packages, or establishing a basis for effort estimation and resource planning.

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。

pjt222/agent-almanac372026年10月13日 更新

Select an OCR/HTR engine by benchmarking candidates on the same labelled samples — source ground truth from open datasets (e.g. Hugging Face PAGE-XML corpora) or hand-transcription, wrap every engine behind a transcribe(image_path) -> str adapter (vision-LLMs via any OpenAI-compatible endpoint, dedicated HTR REST APIs, cloud OCR), and score with zero-dependency raw CER, lenient CER, WER, and a critical name/date token diff. Use when choosing an engine for handwriting or historical-document transcription, when published accuracy claims need honest verification on your own material, or when a records workflow must surface confident-but-wrong names and dates that a low aggregate CER hides.

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。

pjt222/agent-almanac372026年10月13日 更新

Estimate how likely a protein therapeutic is to provoke an anti-drug antibody response, and locate the sequence regions responsible. Use this skill to tile a sequence into peptides, predict class II MHC presentation across a population-representative allele panel, aggregate predicted binders into a per-region and whole-molecule risk score, compare a candidate against its closest human germline, and decide which liabilities are worth deimmunising. Also trigger on immunogenicity, anti-drug antibody, ADA, T-cell epitope, MHC class II, HLA-DRB1, NetMHCIIpan, NetMHCpan, deimmunisation, tregitope, or population coverage.

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。

K-Dense-AI/drug-discovery-agent-skills372026年10月12日 更新

Design small interfering RNA and antisense oligonucleotide sequences against a transcript, and screen them for the failure modes specific to nucleic-acid drugs. Use this skill to tile a target transcript, apply positional and thermodynamic selection rules including duplex asymmetry and nearest-neighbour melting temperature, scan candidates for seed-region complementarity to off-target transcripts, and lay out a chemical modification pattern — gapmer architecture, 2'-O-methyl and 2'-MOE wings, locked nucleic acid, and phosphorothioate placement. Also trigger on siRNA, antisense oligonucleotide, ASO, gapmer, RNase H, seed region, duplex asymmetry, 2'-MOE, locked nucleic acid, phosphorothioate, or GalNAc conjugate.

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。

K-Dense-AI/drug-discovery-agent-skills372026年10月12日 更新

Plan synthetic routes and judge whether a proposed molecule can actually be made, using AiZynthFinder's Monte-Carlo tree search over template-derived reactions and a purchasable building-block stock. Use this skill to configure expansion and filter policies, choose a stock file, run route search over a candidate set, and read the returned trees — solved fraction, route depth, and which building blocks a route bottoms out in. Also trigger on AiZynthFinder, retrosynthetic tree search, synthetic accessibility, SAscore, RAscore, building-block stock, reaction template, or route scoring.

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。

K-Dense-AI/drug-discovery-agent-skills372026年10月12日 更新

worktree

無料

Use when work needs an isolated git worktree: new work, an existing ref, a gated feature workspace, a manifest-tracked loop run, or a candidate patch captured without touching the current checkout (`capture-isolated-patch`). Not for plain branches: use create-branch. Not for remote, credential, publish, deploy, or irreversible changes.

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。

OutlineDriven/odin-claude-plugin372026年9月29日 更新

Use when asked to audit comments in code files and propose structural replacements or deletions with per-candidate approval. Not for deterministic commented-out-code removal: use deslop.

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。

OutlineDriven/odin-claude-plugin372026年9月29日 更新

pui-issue

無料

Inspect one bounded Proto UI Issue queue slice and route ready governed work toward claim and implementation. Use for intake health, readiness, ownership, claim conflicts, stale state, or a candidate task search. This evidence leaf is read-only; authorized claim and implementation continue in their registered leaves.

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。

Proto-UI/Proto-UI362026年10月14日 更新

Independently attempt to falsify one Proto UI autonomous-maintenance finding in a fresh non-mutating context. Use after pui-observe produced a candidate finding and route the result directly to remediation or closure when authority is clear.

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。

Proto-UI/Proto-UI362026年10月14日 更新

Freeze one eligible Proto UI autonomous-maintenance candidate into a bounded mission packet and lease. Use before observation when a current request or governed queue supplies scope, oracle, baseline, capability, risk, budget, completion, and stop conditions. Do not observe, verify, repair, or invent a mission.

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。

Proto-UI/Proto-UI362026年10月14日 更新