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cccskills

「outcome」の検索結果

523 件 ・ 関連度順

概要と使いどころ

Record one authorized non-remediation terminal outcome in Proto UI's autonomous-maintenance state. Use after a supported no-finding result, an independently rejected finding, or a blocked mission whose terminal evidence is complete.

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

Fires after fixing any non-trivial bug or regression. Asks: could the graph have caught this as a guarantee? Pairs with reflection-in-and-on-action — picks up after "earliest catchable signal" and asks the next question: was that signal expressible in graph? Triggers: (1) after any non-trivial bug fix is verified working, (2) after a regression report (something used to work, broke), (3) during step 6 (knowledge extraction) of the workflow, (4) when reflection-on-action surfaces a "would have been catchable" signal. Outcome is a triage decision (graph-reachable? rule expressible? rule sound?) and either a draft Linear issue + guarantee proposal, or a recorded "graph capability gap" note. Never auto-creates guarantees.

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。

Disentinel/grafema362026年8月24日 更新

msw

無料

Apply the Minimum Sufficient Work (MSW) principle through the MSW Kernel to scope, execute, verify, and stop agent work. State the requested outcome and smallest proof, admit a claim only when deleting it would leave the contract unmet or unproven, do and prove each necessary claim, and halt at the fixed point. Use for implementation, debugging, review, research, planning, documentation, or any task where scope control, proportional evidence, or avoiding overwork matters. Also use when the user says MSW, Minimum Sufficient Work, do only what is necessary, avoid over-engineering, or stop when the result is proven.

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。

transcendr/slopware-skills362026年10月13日 更新

Fetch the team's shared skills — reset each disposable team clone to origin/main — and show the outcome per team as a Markdown board from the terum-skills CLI. Use when the user wants the newest catalogue, receipts or roster before listing, searching or installing.

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。

Terum-Inc/terum-skills282026年10月9日 更新

Use when building durable AI agents or agentic workflows with Inngest and AgentKit, including model calls, tool calls, multi-agent networks, human approval, realtime progress, provider rate limits, crash-safe execution, and Agent Evals handoff. Covers AgentKit, `step.ai`, `step.run`, `step.waitForEvent`, native realtime, and when to use lower-level Inngest primitives instead of an in-memory agent loop. Use `inngest-agent-evals` with this skill when the user wants scoring, sessions, experiments, deferred scorers, or outcome-based evaluation for the agent.

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。

inngest/inngest-skills282026年9月29日 更新

Use when creating /goal directives, reusable testable outcome-oriented success standards for agentic workflows. Use whenever the user asks to create a goal, write a /goal directive, define what good looks like, set success criteria for an agent, define a reusable instruction, create a quality standard, write acceptance criteria for an agent workflow, or specify done conditions.

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。

zebbern/skills272026年6月28日 更新

Expert prompt engineer specializing in designing, optimizing, and managing prompts for large language models. Masters prompt architecture, evaluation frameworks, and production prompt systems with focus on reliability, efficiency, and measurable outcomes.

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。

majiayu000/claude-skill-registry-data262026年10月13日 更新

Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.

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。

majiayu000/claude-skill-registry-data262026年10月13日 更新

Run a reusable opportunity-to-artifact workflow: discover unmet needs, set up workspace factories, schedule recurring commander/worker/reporter prompts, batch-refine many items, optionally use SQLite state, build small artifacts, review quality, and track outcomes. Use when the user wants to repeatedly create apps, games, products, content, or experiments from market/user needs.

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。

aktsmm/Agent-Skills262026年10月13日 更新

"Apply Giddens' structuration theory to analyze the duality of structure — how social structures are both the medium and outcome of the practices they organize. Use this skill when the user needs to bridge agency and structure in organizational or social analysis, explain how routines reproduce or transform institutional patterns, analyze the recursive relationship between action and structure, or when they ask 'do people shape institutions or do institutions shape people', 'how are these routines maintained', or 'where does change come from if structures constrain action'.".

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。

charlieviettq/awesome-agent-skill262026年7月20日 更新

"Apply Upper Echelons Theory (Hambrick and Mason, 1984) to analyze how top management team characteristics — demographics, experiences, values — shape strategic choices and organizational outcomes. Use this skill when the user needs to evaluate TMT composition effects on strategy, predict strategic direction from leadership profiles, assess whether managerial discretion enables or constrains executive influence, or when they ask 'does leadership background matter for strategy', 'how does TMT composition affect decisions', or 'why did this management team make that choice'.".

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。

charlieviettq/awesome-agent-skill262026年7月20日 更新

"Apply public choice theory to analyze political decision-making as rational self-interested behavior. Use this skill when the user needs to evaluate government policy failures, rent-seeking costs, voting outcomes, or bureaucratic incentives, especially when the assumption of benevolent government is questionable.".

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。

charlieviettq/awesome-agent-skill262026年7月20日 更新

"Apply Difference-in-Differences (DID) to estimate causal treatment effects by comparing changes in outcomes between treatment and control groups. Use this skill when the user evaluates policy interventions, natural experiments, or regulatory changes, needs to test parallel trends, or when they ask 'did this policy work', 'how do I identify causal effects without randomization', or 'what is the treatment effect'.".

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。

charlieviettq/awesome-agent-skill262026年7月20日 更新

"Apply Granovetter's embeddedness theory to analyze how economic behavior is embedded in ongoing social relations, avoiding both over-socialized and under-socialized accounts. Use this skill when the user needs to explain why market transactions deviate from pure economic rationality, analyze how trust and social ties shape business dealings, evaluate structural vs relational embeddedness in inter-firm networks, or when they ask 'why do firms prefer existing partners over cheaper alternatives', 'how do social relationships shape economic outcomes', or 'is this market truly arms-length'.".

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。

charlieviettq/awesome-agent-skill262026年7月20日 更新

"Analyze market structures across perfect competition, monopolistic competition, oligopoly, and monopoly to predict firm behavior and market outcomes. Use this skill when the user needs to classify a market's competitive structure, predict pricing behavior, evaluate antitrust implications, or understand why an industry behaves the way it does — even if they say 'why can they charge so much', 'is this market competitive', or 'will prices come down'.".

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。

charlieviettq/awesome-agent-skill262026年7月20日 更新

"Apply Complex Adaptive Systems theory to analyze phenomena exhibiting emergence, self-organization, co-evolution, and edge-of-chaos dynamics. Use this skill when the user needs to understand why a system behaves unpredictably despite known components, model agent-based interactions that produce emergent outcomes, analyze fitness landscapes, or when they ask 'why does this system behave in ways no one designed', 'how do local interactions create global patterns', or 'why do small changes sometimes cause massive system shifts'.".

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。

charlieviettq/awesome-agent-skill262026年7月20日 更新

"Implement Elo rating system to rank items or players from pairwise comparison outcomes. Use this skill when the user needs to rank items from head-to-head matchups, build a competitive rating system, or evaluate relative quality from comparison data — even if they say 'player rating', 'ranking from comparisons', or 'competitive scoring 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。

charlieviettq/awesome-agent-skill262026年7月20日 更新

Audits whether a machine-readable regelrecht law model is faithful to the LETTER of the wettekst — and strictly separates the wettekst (leading) from the toelichting (Nota/Memorie van Toelichting; explanatory, not a norm). Runs in critical passes per article/lid and detects four deviation classes: toelichting-bleed (a modeled criterion that the letter only states as an open norm, or not at all), missing verbatim elements (a word/condition such as a "tenzij" or a qualifier dropped from the model), wrong legal_basis anchoring (an endpoint hung on a "kapstok"-article while the operative norm lives elsewhere), and verbatim-drift in text: (an ingetrokken/older redaction). Also detects positief-lid vs uitsluitings-lid conflicts and checks the chapeau for an explicit derogation rule ("zo nodig in afwijking van het eerste lid") before judging precedence. Classifies every finding as modelfout (fix), wettekst-gevolg (report, do not fix), or letter-vs-toelichting-question (jurist decides what is leading + revision signal). Use when the user wants to know if a model is "dicht bij de letter", mentions letter vs toelichting/bedoeling, fidelity, "natuurgetrouw", or before trusting feature outcomes.

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。

NederlandseDigitaleDienst/regelrecht252026年10月14日 更新

servotab

無料

Use for hands-on repository work when a quiet, risk-scaled engineering method can improve design, implementation, debugging, review, delegation, workspace lifecycle, or verification. Keep clear local changes direct, preserve the complete requested outcome, and add method only where risk or uncertainty justifies it. Do not use for general technical explanations, simple file lookup, casual discussion, or non-engineering writing.

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。

IndelibleVivi/servotab252026年10月12日 更新

delegate

無料

Choose responsibility for substantial work before deep execution: keep one responsibility's coupled parts in a single lane, and hand a bounded or independent lane to a worker when clean context, an unknown cause, independent review, or coordinator attention materially improves the outcome.

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。

IndelibleVivi/servotab252026年10月12日 更新

Write and cascade OKRs (Objectives and Key Results) for company, department, team, or project level. Ensure objectives are inspiring and key results are measurable outcomes. Includes weekly check-in template. Use at the start of each quarter or when aligning strategy to execution. Do not use for KPI performance reviews or daily task tracking.

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。

hoavdc/CodexKit252026年10月11日 更新

Translate strategy into a balanced scorecard, strategy map, OKR bridge, and executive initiative portfolio with clear measures, targets, and owners. Use when leadership needs strategic alignment, portfolio prioritization, or a management dashboard tied to outcomes. Do not use for ad-hoc brainstorming with no strategic horizon.

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。

hoavdc/CodexKit252026年10月11日 更新

Prepare customer or executive business reviews with outcome tracking, adoption health, ROI narrative, risks, commitments, and next-quarter plan using customer success and CX frameworks. Use when teams need QBRs, success plans, churn-risk conversations, or executive account reviews. Do not use for generic slide beautification or cold outreach prospecting.

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。

hoavdc/CodexKit252026年10月11日 更新

status

無料

Read every application.yaml in the workspace and report the state of the search — the ranked queue, what is waiting on you, what has gone quiet, and the regression of the pipeline's own predictions against actual outcomes. Writes the calibration findings back into job_search.md and preferences.yaml.

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。

VonTerraProject501c3/slushpile242026年8月17日 更新