MCP HubMCP Hub
SKILL·1AC839

intel-discipline-advisor

deanpeters
Обновлено 6 days ago
5,952
730
5,952
Посмотреть на GitHub
Метаgeneral

О программе

Этот навык помогает разработчикам классифицировать вопросы по рыночной аналитике, интерактивно определяя необходимые исследовательские дисциплины, периодичность и исполнительские навыки. Он проводит пользователей через три адаптивных вопроса, чтобы сопоставить решения с конкретными аналитическими каналами, такими как OSINT или TECHINT. Используйте его, когда вам нужно исследовать конкурентный вопрос, но вы не уверены, какие методы расследования применить.

Быстрая установка

Claude Code

Рекомендуется
Основной
npx skills add deanpeters/Product-Manager-Skills -a claude-code
Команда плагинаАльтернативный
/plugin add https://github.com/deanpeters/Product-Manager-Skills
Git клонированиеАльтернативный
git clone https://github.com/deanpeters/Product-Manager-Skills.git ~/.claude/skills/intel-discipline-advisor

Скопируйте и вставьте эту команду в Claude Code для установки этого навыка

Документация

Intel Discipline Advisor

Purpose

Triage a competitive or market question into the right intelligence response: which of the eight collection disciplines to run, on what cadence, feeding which artifact, executed by which skill. The intelligence-collection-disciplines compendium holds everything about every channel; this advisor answers the question a busy PM actually has — "given what's on my desk, which two or three channels matter, and where do my limited hours go?" Running every discipline on every question is the failure mode; scoping to the decision is the craft. The advisor teaches the mapping as it routes, so by your third session you won't need it. That's the goal.

Input

Works best with: the decision or question on your desk, in your words — "I think [Competitor A] is building something," "my TAM slide got shredded," "sales keeps getting surprised." Also useful: any signal you've already noticed (a job posting, a pricing change, an earnings remark), your time budget, and whether you're limited to free sources.

Anything supplied with the invocation itself — text after the skill name, a pasted context dump, or an appended ARGUMENTS: line — counts as answers already given. Use it and skip whatever it covers; don't re-ask.

Arriving empty-handed? That works too. The advisor opens by asking what's on your desk, with enumerated situations to pick from.

Example invocation: Intel discipline advisor: two of their senior engineers just followed our CTO on a preprint server, and their careers page doubled — what do I run?

Key Concepts

  • Facilitation protocol: use workshop-facilitation as the default interaction protocol (entry modes, one question per turn, progress labels, numbered recommendations). This file defines the domain logic.
  • The routing brain is the artifact-mapping table in intelligence-collection-disciplines: every PM artifact has a known discipline mix and refresh cadence. The advisor's job is matching the user's situation to a row — and showing the match, because the mapping is the lesson.
  • Signals already seen are a head start. If the user noticed a job posting surge, HUMINT has already flagged once — the recommendation starts from "1 discipline flagged" on the confidence stacking ladder and names which independent channels would corroborate (see autonomous-investigation).
  • Cadence must match evidence speed and human capacity. Pricing pages change monthly; statistics releases change annually. A watch the user can't sustain is worse than none — it produces false confidence that someone is watching.
  • The honest off-ramp. Some questions don't need an investigation: if the question is "why do customers churn," the answer is win/loss interviews and discovery, not a patent sweep. The advisor says so.

Application

This interactive skill asks 3 adaptive questions, then offers numbered, context-aware recommendations.

Question 1: What's on your desk?

"What's the situation? Pick the closest, or describe your own:

  1. Suspected competitor move — you think someone is building, entering, or repositioning
  2. An artifact to build or refresh — TAM/SAM/SOM, battle card, positioning, ICP/personas, pricing analysis
  3. A margin or market-structure puzzle — margins eroding, category shifting, entry decision
  4. Standing watch setup — you want ongoing coverage, not a one-off answer"

Question 2: Adaptive follow-up

  • If 1 (suspected move): "What tipped you off — a job posting, a pricing change, an exec's post, a patent, a customer remark? (Whatever you saw is one discipline already flagging; we'll pick the independent channels that could corroborate it.)"
  • If 2 (artifact): "Which artifact, and does a prior version exist to diff against?"
  • If 3 (structure puzzle): "Is the question about the whole industry's structure, or one company's position in it?"
  • If 4 (watch): "Honestly, how much recurring time can you or your team commit — 30 minutes a week, a half-day a month, a day a quarter?"

Question 3: Constraints

"Two quick constraints: free sources only or is paid tooling available, and any geographic focus? (Region changes which registries and statistics bureaus apply.)"

Then: Recommend

Synthesize and offer 3-5 numbered recommendations, each naming: discipline mix → cadence → executing skill → artifact fed, with one line on when it's the right choice. Always show why the disciplines were chosen (the mapping-table logic), and include the off-ramp when it's honest. Handle single selection, combinations ("1 and 3"), and custom directions per the facilitation protocol.

Routing quick-reference (from the artifact-mapping table):

SituationDiscipline mixExecuting skill
Suspected moveCorroborate the seen signal: TECHINT + HUMINT + SIGINT + FININT, fusedintelligence-collection-disciplines fusion template, then competitive-intel-watch
Battle cardSIGINT + OSINT + HUMINTbattle-card-builder, kept fresh by the watch
TAM/SAM/SOMGEOINT/DEMOINT + FININT capture ratestam-sam-som-calculator Mode 3
Positioning / ICPOSINT + GEOINT/DEMOINT (+ VoC)voice-of-customer-minerpositioning-statement
Industry structureFININT + OSINTporters-five-forces
One company's positionOSINT + FININT + HUMINTswot-analysis or company-intel
Pricing questionSIGINT + FININTpricing-packaging-tracker
Macro exposureGEOINT/DEMOINT + regulatory FININTpestel-delta-monitor
Standing watchSIGINT weekly, OSINT+HUMINT monthly, FININT+TECHINT quarterly — scaled to stated capacitycompetitive-intel-watch
The full pictureAll of the above, sequencedcompetitive-analysis-process

Close by offering the one-page triage card (template.md) filled in from the session — the route, its "because," and a review date, as a handoff artifact.

Examples

Sample flow (fictional):

Q1 → User: "1 — I think [Competitor A] is building a data-platform play." Q2 → User: "Their careers page doubled, mostly data engineers." Q3 → User: "Free sources, US only."

"Your hiring observation means HUMINT has already flagged once — one discipline is an anecdote, so the job is corroboration from independent channels. Recommendations:

  1. TECHINT sweep this week (patents.google.com + their GitHub org + arXiv affiliations, free) — a paper-or-patent cluster in the same specialty as the hiring surge is the strongest fusion pair available. Pick this first: highest corroboration value per hour.
  2. SIGINT check, 30 minutes (crt.sh for new subdomains, Wayback diff on their product pages) — catches launch staging if this is further along than hiring suggests.
  3. FININT pass at their next earnings call — listen for capex dodges and segment-language shifts; free via their IR page. Slower, but turns hypothesis into briefable intelligence.
  4. Set the watch instead — if this can't get hours this quarter, wire [Competitor A] into competitive-intel-watch monthly and let the cadence catch it.

Reply 1, 2, 3, 4, a combination like '1 and 2', or tell me more. (Two agreeing disciplines = working hypothesis; three = brief your leadership.)"

The off-ramp in action: user picks "artifact: ICP refresh," but Q2 reveals the real question is "why did our last three enterprise deals stall?" The honest recommendation leads with win/loss interviews (HUMINT's ground-truth layer) and discovery-interview-prep — "no public-web sweep answers a question your own churned prospects can answer better."

See examples/conversation-flow.md for a full end-to-end session: inline input crediting two of the three questions, a capacity answer that gets believed, a combination selection, and a "tell me more" that earns a teaching answer. examples/conversation-flow-industrial.md shows the routing shift for a physical-world signal — permits and customs data instead of site diffs.

Common Pitfalls

  • Prescribing the full eight. Recommending every discipline is refusing to triage. Two or three channels matched to the decision beats coverage theater — the mapping table exists so you can skip.
  • Ignoring the seen signal. The user's tip-off is a free head start on the stacking ladder. Recommending channels that re-detect the same signal type adds no corroboration; independence is what stacks.
  • Cadence fantasy. Designing a weekly watch for a team with a quarterly attention span. Ask the capacity question and believe the answer.
  • Routing without teaching. Handing over a recommendation without the "because" strips the lesson. Every recommendation shows its mapping-table logic — the user should leave better at triage, not just triaged.
  • No off-ramp. Forcing every question into an investigation. Discovery, win/loss, and support tickets answer some questions better than any public-web sweep; say so when it's true.

References

GitHub репозиторий

deanpeters/Product-Manager-Skills
Путь: skills/intel-discipline-advisor
0
ai-agentsai-product-managementclaude-skillspm-frameworksproduct-management
FAQ

Часто задаваемые вопросы

Что такое Skill intel-discipline-advisor?

intel-discipline-advisor — это Claude Skill от deanpeters. Skills объединяют инструкции и ресурсы, которые Claude загружает по мере необходимости, чтобы выполнять задачи, связанные с intel-discipline-advisor, без дополнительных запросов.

Как установить intel-discipline-advisor?

Используйте команды установки на этой странице: добавьте intel-discipline-advisor в Claude Code как плагин или клонируйте репозиторий в каталог skills, затем перезапустите Claude, чтобы загрузить Skill.

К какой категории относится intel-discipline-advisor?

intel-discipline-advisor относится к категории Мета.

Можно ли использовать intel-discipline-advisor бесплатно?

Да. intel-discipline-advisor размещён на AIMCP и доступен для бесплатной установки.

Похожие навыки

content-collections
Мета

Этот навык предоставляет проверенную в продакшене настройку для Content Collections — TypeScript-ориентированного инструмента, который преобразует файлы Markdown/MDX в типобезопасные коллекции данных с валидацией Zod. Используйте его при создании блогов, сайтов документации или контентных приложений на Vite + React для обеспечения типобезопасности и автоматической проверки содержимого. Он охватывает всё: от настройки плагина Vite и компиляции MDX до оптимизации развертывания и валидации схем.

Просмотреть навык
polymarket
Мета

Этот навык позволяет разработчикам создавать приложения на платформе прогнозных рынков Polymarket, включая интеграцию с API для торговли и получения рыночных данных. Он также обеспечивает потоковую передачу данных в реальном времени через WebSocket для отслеживания текущих сделок и рыночной активности. Используйте его для реализации торговых стратегий или создания инструментов, обрабатывающих обновления рынка в реальном времени.

Просмотреть навык
creating-opencode-plugins
Мета

Этот навык помогает разработчикам создавать плагины OpenCode, которые подключаются к более чем 25 типам событий, таким как команды, файлы и операции LSP. Он предоставляет структуру плагина, спецификации API событий и шаблоны реализации для модулей на JavaScript/TypeScript. Используйте его, когда вам нужно перехватывать, отслеживать или расширять жизненный цикл ассистента OpenCode AI с помощью пользовательской событийно-ориентированной логики.

Просмотреть навык
sglang
Мета

SGLang — это высокопроизводительный фреймворк для обслуживания больших языковых моделей (LLM), специализирующийся на быстрой структурированной генерации JSON, regex и рабочих процессов агентов с использованием кэширования префиксов RadixAttention. Он обеспечивает значительно более высокую скорость вывода, особенно для задач с повторяющимися префиксами, что делает его идеальным для сложных структурированных результатов и многократных диалогов. Выбирайте SGLang вместо альтернатив, таких как vLLM, когда вам требуется ограниченное декодирование или вы создаете приложения с интенсивным совместным использованием префиксов.

Просмотреть навык