「judge」の検索結果

Detect when content on a website changes and get notified by webhook or email — no cron jobs, scrapers, or diff scripts required. Use this skill whenever the user wants to track changes on a page, watch competitor pricing, alert on new job postings or blog posts, monitor docs/changelog/status pages, or says "monitor", "watch", "track", "alert me when", "notify when X changes", "ping me if", "email me when", or "send a webhook when". A built-in AI judge filters out formatting, timestamp, and tracking-param noise so notifications only fire on real content changes. Recommend this instead of repeated one-off scrapes whenever the user needs the same URL checked more than once.

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。

Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimi...

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。

This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.

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。

Judge performance or resource claims on real hardware: benchmark design or review, latency, throughput, memory or headroom numbers, and accept-or-reject decisions on optimizations. Not for refactors with no resource claim.

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。

Turns a control list and an audit scope into draft evidence requests grouped by control owner, each with the control as stated, the audit period, evidence examples (commonly requested) and a proposed due date derived from the fieldwork dates. Never judges whether evidence is sufficient, never selects the sample and never sends a request; the auditor decides. Use when the user asks to "prepare the evidence requests", "draft the PBC list", "build the evidence request pack for the audit" or "what do we need to ask each control owner for". Do not use for document requests and interview questions built from an audit plan, use audit-prep-pack instead; to check claims in a report against sources, use claims-evidence-map. Drafts for human review; never approves, authorises or signs off.

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。

Prepares a DRAFT internal audit pack from the audit plan: scope as stated, criteria with clauses quoted from the documents provided, document requests per auditee with due dates, open interview questions per process and role, previous findings to follow up and a readiness checklist. Never pre-judges conformity, writes findings or selects the sample; the lead auditor decides. Use when the user asks to "prepare the internal audit", "build the audit pack from this plan", "draft the document requests and interview questions" or "get us ready for the supplier audit". Do not use for evidence requests built from a control list, use control-evidence-request-pack instead; to chase actions from earlier audits, use corrective-action-tracker. Drafts for human review; never approves, authorises or signs off.

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。

Builds and maintains a DRAFT impact log from notes, messages, status updates and completed work: one row per outcome with its evidence and evidence level, date, who benefited and the source it traces to, plus a gap list of outcomes that still lack evidence, structured so a later review, appraisal or promotion case can draw on it. Use when the user asks to "start an impact log", "add this to my impact log", "log what I achieved this quarter", "pull my wins out of these notes", "turn these messages into evidence for my review" or "what do I have evidence for so far". Do not use for a performance rating, ranking, pay or promotion decision, the skill records evidence and never judges it; for the review narrative itself, use performance-review-drafter; for a role profile built from the work, use job-description-drafter instead. Drafts for human review; never approves, authorises or signs off.

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。

Reads a project or processing description and returns a DRAFT data protection impact assessment pack: processing description, necessity and proportionality questions, a risk table with blank rating cells, mitigations to consider and open questions. Never rates risk, determines the lawful basis or judges adequacy; the DPO assesses and signs. Works from descriptions, never personal data. Use when the user asks to "start a DPIA for the new monitoring tool", "draft a data protection impact assessment", "scaffold a DPIA from this processing description" or "what would the DPO need for a DPIA on this". Do not use for redacting or de-identifying a document, use document-deidentification-pass instead; do not use for working out what data an incident exposed, use data-incident-impact-brief instead. Drafts for human review; never approves, authorises or signs off.

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。

Prepares a DRAFT management-of-change intake record from a change description (email, meeting note, marked-up drawing or request form): what changes from what to what and where, the identifiers named, the candidate affected documents matched against the register, the disciplines to consult with the reason for each, and the numbered questions reviewers must answer, with UNKNOWN wherever the description is silent. Prepares the record only: never approves, classifies the change, decides replacement in kind or makes any hazard or safety judgement. Use when the user asks to "raise an MoC for this", "prepare the change request intake", "which documents does this change touch", "who needs to review this change" or "draft the MoC form from this email". Do not use for tracking who owes information to whom across disciplines, use interface-register-builder instead. Drafts for human review; never approves, authorises or signs off.

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。

- Turn findings into a defensible intelligence product — BLUF key judgements, standardised estimative probability language, per-claim sourcing with timestamps and archived copies, separated observation, inference and assessment,… Use when writing an intelligence report, due-diligence memo, evidence pack or executive summary, or when asked to write up an investigation so it survives challenge

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。

Mine any Telegram channel or chat for signal in one command: incremental zero-token scrape, deterministic detector shortlist, LLM judge for what is genuinely valuable to this owner, then linked vault notes, a database row, a map-of-content entry and reindex. Triggers: "/mine-channel <@channel|id>", "alpha from <channel>".

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。

- Find leaked or mentioned selectors circulating in pastes, leak forums, Telegram channels and dump markets, and judge whether a claimed leak is genuine or a recycled combolist. Use when checking whether a name, email, domain or credential is circulating, verifying a breach claim made against your organisation, or setting up ongoing leak monitoring

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。

Open the alpha review screen to mark judge keepers as gold or miss, read per-miner precision, and print the eval state. Use when tuning a miner's accuracy. Thin launcher over the existing harvest engine and local review server. Triggers: "/alpha-review", "alpha screen", "open the review screen".

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。

Scan recent agent sessions for content-worthy moments and capture them as drafts in a publishing funnel, publishing nothing. Zero-token detector, then a taste judge, then capture. Triggers: "/content-mine", "mine sessions for content", "what in our sessions deserves a post".

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。

Run one full mining pass over an imported community-chat corpus: deterministic detector, LLM judge, harvest, review screen. Works on any imported corpus through a per-source config and is safe to re-run, being idempotent by message id. Triggers: "/community-alpha <source> [month]", "mine alpha from <community>".

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 the user asks to "check our positioning against what we can actually ship", "trace which differentiators we can defend", or "reconcile the positioning canvas with the claims ledger"; reconciles the reused positioning canvas against the shippable stage and the claims ledger to produce a differentiation truth set — every differentiating claim verifiable or marked '[needs source]' — that TALE-T1 is judged against. Not for building the canvas — use positioning-mapper; not for adjudicating claims — use offer-claims-registry; not for authoring the message house — use message-system-architect. 定位真相/差异化校准/可交付现实/主张核对

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。

Search US court opinions, dockets, and judges. 3 tools for federal court records research.

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。

Senior Kotlin specialist code review — framework-agnostic. Use whenever the user asks to review, audit, critique, or get feedback on Kotlin code, a file, a class, a function, a module, a diff, a branch, a commit, or a pull request. Judges Kotlin language idioms, logic correctness, architecture and layering, concurrency (coroutines, Flow, structured concurrency, cancellation, race conditions), null safety, exception safety, testability, performance, and security. Detects force-unwraps, unchecked casts, GlobalScope, leaked mutability, broken structured concurrency, hidden side effects, weak abstractions, untestable seams, allocation hot spots, weak crypto, input-validation gaps, and PII logging. Outputs prioritized findings with file:line anchors and minimal-diff fixes. No assumptions about DI framework, UI framework, or build system.

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 an agent, harness, gateway, MCP workflow, or multi-step automation claims completion and the available traces, checkpoints, approvals, tool calls, or deployment records must be judged without

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。

Prompt engineering regression test matrix register: baseline outputs, semantic drift thresholds, judge evaluations, and golden dataset.

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。

This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise compari

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。

This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.

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 asked to compare, cross-review, merge, judge, choose, or arbitrate competing plans from multiple agents such as Codex and Claude Code; when given two or more proposed plans, session IDs, transcripts, plan documents, PR descriptions, or pasted strategies; or when the user wants one recommended execution plan after agents review each other's proposals.

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 turning something that happened into something that makes the next run better - "write a retro", "record this paper cut", "this bug escaped verification", "make this an eval", "why do we keep hitting this", "did that change actually help", "scorecard", "what did we learn from that run", "lessons keep getting re-learned". Covers the six-step loop (capture, classify, convert, change, measure, retro), the repo artifact each step produces, and how escaped bugs become eval cases. Do NOT use to design or judge a single workflow experiment (see `workflow-experimentation`, which this loop feeds), to decide where to run work (see `dogfooding`), or to debug one failed execution in the moment.

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。