SkillAtlasSkill 详情

competitive-intel-watch

GitHub stars License: CC BY-NC-SA 4.0 PRs Welcome Version Claude Code Plugin Skills

审核状态:已审核Quality 80Security 88

复制安装命令

用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。

复制前请先查看来源、License 和安全提示。

项目 README

来源文件:README.md

抓取于 2026年8月2日

Product Manager Skills

GitHub stars License: CC BY-NC-SA 4.0 PRs Welcome Version Claude Code Plugin Skills

╔════════════════════════════════════════════════════════════════════╗
║                                                                    ║
║   ██████╗ ███╗   ███╗    ███████╗██╗  ██╗██╗██╗     ██╗     ███████╗
║   ██╔══██╗████╗ ████║    ██╔════╝██║ ██╔╝██║██║     ██║     ██╔════╝
║   ██████╔╝██╔████╔██║    ███████╗█████╔╝ ██║██║     ██║     ███████╗
║   ██╔═══╝ ██║╚██╔╝██║    ╚════██║██╔═██╗ ██║██║     ██║     ╚════██║
║   ██║     ██║ ╚═╝ ██║    ███████║██║  ██╗██║███████╗███████╗███████║
║   ╚═╝     ╚═╝     ╚═╝    ╚══════╝╚═╝  ╚═╝╚═╝╚══════╝╚══════╝╚══════╝
║                                                                    ║
║   70 battle-tested skills + 6 command workflows                    ║
║   Claude Code • Cursor • Codex  • n8n • OpenClaw • and more ...    ║
║                                                                    ║
║   v0.83 • July 17, 2026 • CC BY-NC-SA 4.0                          ║
╚════════════════════════════════════════════════════════════════════╝

70 battle-tested PM frameworks, ready for Claude, Codex, ChatGPT, and any agent that can read structured knowledge.


Why This Exists

Generic AI output is a PM's worst enemy. When you tell your agent "write a PRD" without shared context, you get a generic document that no stakeholder trusts and no engineer can act on.

This library gives both you and your AI agent the same professional foundation: the why behind each framework, the failure modes to avoid, and the judgment to apply them correctly. You stop repeating yourself. Your agent stops guessing. The work gets better.

The goal is dual — functional and pedagogic in equal measure. Skills equip agents to do PM work at a professional level, and they teach the human PM the reasoning behind each framework — so you can explain it, adapt it, and pass it on. Neither is a byproduct of the other.


What You Can Get Done

Navigate by what you're actually trying to accomplish:

Framing and strategy

  • problem-framing-canvas — MITRE's Look Inward / Look Outward / Reframe sequence; stops teams from solving the wrong problem
  • positioning-statement — Geoffrey Moore's template for defining who you serve, what you solve, and how you're different
  • product-strategy-session — full strategy arc: positioning → problem framing → solution exploration → roadmap (2-4 weeks)

Stakeholder alignment

  • stakeholder-identification — map every stakeholder before engaging anyone: broad brainstorm → allies/audiences/influencers → R/P/D marking → equity lens → narrow to priority targets
  • stakeholder-mapping — run two complementary grids (Power × Interest for engagement strategy; Impact × Power for whose voice to elevate) and compare to find the gaps
  • stakeholder-engagement-advisor — per-stakeholder engagement planning: diagnoses their profile and context, then delivers tailored message framing, medium, cadence, and a named next action

Customer discovery and research

Prioritization and roadmapping

  • prioritization-advisor — asks 3-5 questions about your context, then recommends RICE, ICE, Kano, or the right alternative
  • epic-breakdown-advisor — splits large epics using Richard Lawrence's 9 patterns
  • roadmap-planning — gather inputs → define epics → prioritize → sequence → communicate (1-2 weeks)

Writing PM deliverables

  • user-story — Mike Cohn format + Gherkin acceptance criteria, with anti-patterns
  • prd-development — structured PRD: problem → personas → solution → metrics → stories (2-4 days)
  • press-release — Amazon Working Backwards: clarify product vision before writing a line of spec

Validation and experimentation

  • pol-probe-advisor — recommends which prototype type to run based on your hypothesis and risk level
  • pol-probe — template for documenting lightweight validation experiments before building

Finance and growth

  • business-health-diagnostic — diagnoses SaaS health across growth, retention, efficiency, and capital using your real metrics
  • organic-growth-advisor — McKinsey Growth Pyramid triage: diagnoses whether your constraint is in new segments, geographies, channels, or products
  • feature-investment-advisor — build / don't build recommendation using revenue impact, cost, ROI, and strategic value

Market and competitive intelligence

Career and leadership transitions

AI product work


Get Started

Choose your setup:

I use...Get thisNotes
Claude Desktop or Claude Webpm-skills-starter-pack.zipUnzip, then upload the individual skill ZIPs to Claude Skills
Claude CodePlugin marketplaceclaude /plugin marketplace add deanpeters/Product-Manager-Skills
Codexpm-skills-codex.zipInstalls .agents/skills and AGENTS.md
Not surepm-skills-starter-pack.zipStart here

All downloads: GitHub Releases

Themed packs for Claude Desktop / Web

Each pack below is a ZIP of upload-ready skill ZIPs — unzip, then upload individuals to Claude Skills:

PackDownloadWhat's inside
Starterpm-skills-starter-pack.zipCore skills across all categories
Discovery02-discovery-pack.zipResearch, interviewing, synthesis
Strategy03-strategy-pack.zipPositioning, roadmapping, prioritization
Delivery04-delivery-pack.zipPRDs, stories, epics
AI PM05-ai-pm-pack.zipContext engineering, orchestration, readiness
Market Intel06-market-intel-pack.zipThe full Market Intelligence Suite: disciplines, investigation chain, frameworks, monitors
All skills99-all-skills-pack.zipAll 70 skills

Install guides


Try It First — Streamlit (beta)

Not ready to wire skills into your agent setup? Run the local playground first and kick the tires in your browser.

pip install -r app/requirements.txt
streamlit run app/main.py

What you can do:

  • Learn — browse setup and integration paths without leaving the app
  • Find My Skill — describe your situation in plain English and get recommended skills
  • Run Skills — run a skill with your own scenario once you know what you want

Multi-provider support: Anthropic, OpenAI, Ollama. API keys via environment variables only (no in-app key entry).

Docs: app/STREAMLIT_INTERFACE.md · app/.env.example

Feedback welcome via GitHub Issues or LinkedIn.


70 Skills, 3 Types

Skills are organized in three tiers that build on each other:

┌────────────────────────────────────────────────────────┐
│  WORKFLOW SKILLS (19)                                  │
│  Complete end-to-end PM processes (days to weeks)      │
│  Example: run a full discovery cycle or write a PRD    │
└────────────────────────────────────────────────────────┘
                       ↓ orchestrates
┌────────────────────────────────────────────────────────┐
│  INTERACTIVE SKILLS (27)                               │
│  Guided discovery — 3-5 questions, then recommendations│
│  Example: "Which prioritization framework fits here?"  │
└────────────────────────────────────────────────────────┘
                       ↓ uses
┌────────────────────────────────────────────────────────┐
│  COMPONENT SKILLS (24)                                 │
│  Templates for specific PM deliverables (30-90 min)    │
│  Example: write a user story with acceptance criteria  │
└────────────────────────────────────────────────────────┘

Interactive skills use an Adaptive Decision Ladder. Instead of dumping a framework at you, an interactive skill asks 3-5 targeted questions about your specific context, then offers numbered recommendations — each with a clear "use this when" rationale. You pick a path. The skill executes it and explains the why as it goes. If you want to just learn the framework without doing the work, you can ask that too — the skill coaches you either way. This is ABC — Always Be Coaching — in practice.

Full catalog: catalog/INDEX.md — all 70 skills with descriptions, or browse skills/ directly.


How a Skill File Works

Every SKILL.md follows the same structure:

SectionWhat it contains
Frontmattername, description, type, intent, best_for, scenarios
PurposeWhat this skill does and when to reach for it
InputWhat you can bring (with example invocations) — inline input is used, not re-asked, and arriving empty-handed is fine: the skill walks you through it
Key ConceptsFrameworks, definitions, anti-patterns — with vocabulary explained
ApplicationStep-by-step instructions an agent (or human) can follow
ExamplesReal-world cases showing both good and bad versions
Common PitfallsNamed failure modes with consequences and corrections
ReferencesRelated skills and external frameworks

The best_for frontmatter field lists 3-5 specific scenarios where the skill is most useful — helpful for quickly scanning whether a skill fits your situation.

Why no $ARGUMENTS templating? Other skill libraries use Claude Code's $ARGUMENTS substitution for input. We deliberately don't: it only expands in Claude Code (it renders as literal syntax in Claude Desktop/Web, Codex, and the Streamlit playground), and it teaches the human reader nothing. Instead, every skill has a plain-language ## Input section that works on every runtime — and makes clear you can show up with full context, partial context, or nothing at all and be guided through the rest. Full rationale in CONTRIBUTING.md.


Works With

Claude Code · Claude Desktop · Claude Web · OpenAI Codex · ChatGPT · Cursor · Windsurf · n8n · LangFlow · CrewAI · Gemini · any agent that reads structured markdown

See docs/Platform Guides for PMs.md for platform-specific setup.


Docs

DocumentPurpose
Using PM Skills 101Beginner-friendly orientation — setup without technical overload
Platform Guides for PMsTool-by-tool setup chooser for every supported platform
Using PM Skills with ClaudeClaude Code + GitHub ZIP upload for Claude Desktop/Web
Using PM Skills with CodexLocal workspace + GitHub-connected Codex on ChatGPT
Using PM Skills with ChatGPTGitHub app, Custom GPT Knowledge, and Project-based usage
Using PM Skills with Slash Commands 101Turn skills into reusable slash commands like /pm-story
Add-a-Skill Utility GuideEnd-to-end guide for generating and validating new skills
Market Intelligence Suite SummaryThe 14-skill competitive/market research suite: disciplines, chain, and which skill to run when
Building PM SkillsHow raw PM content gets distilled into agent-ready skills
START_HERE.md60-second onboarding for local repo users

What's New

v0.83 — July 17, 2026 · The Market Intelligence Suite

v0.82 — July 8, 2026

  • Added incoming-request-advisor (Interactive) — drop in a Slack ping, email, mandate, or escalation and get a structured breakdown that separates the literal ask from the real job-to-be-done, reads sender power and stake, and points you toward a reply. Ships with a copy/paste template so you can run it by hand too
  • New: a browsable download shelf at /dist — no terminal, no Releases tab. Read the plain-language README, scan the CATALOG, and download any skill or pack straight from the repo. Built for PMs who just want the skills
  • Library now at 70 skills

v0.81 — July 4, 2026

  • Every skill now has a required ## Input section: what to bring, what happens to context you supply up front (it's used, not re-asked), and reassurance that arriving empty-handed is fine — the guided flow covers the rest
  • Added argument-hint autocomplete for Claude Code users; deliberately no $ARGUMENTS templating — it breaks on every other runtime and teaches the reader nothing (why)
  • Validator now enforces the convention: skills fail without an Input section or with bare $ARGUMENTS in the body
  • Streamlit playground shows each skill's "What to bring (all optional)" before you start a session
  • Restored agent-orchestration-advisor (Interactive) — the multi-agent workflow design skill was referenced everywhere but only existed on an orphaned commit; recovered from git history and brought up to current standards

v0.80 — June 19, 2026

  • Added stakeholder-identification (Component) — comprehensive stakeholder brainstorm using allies/audiences/influencers, R/P/D marking, equity lens, and bias check; narrows to priority targets
  • Added stakeholder-mapping (Component) — two complementary grids (Power × Interest + Impact × Power); comparing outputs reveals who you're under-engaging relative to how much the product affects them
  • Added stakeholder-engagement-advisor (Interactive) — per-stakeholder engagement planning via Adaptive Decision Ladder: three questions on profile, power/impact, and context deliver tailored message framing, medium, cadence, and a named next action

All three adapted from the MITRE Innovation Toolkit via the companion repo MITRE ITK Skills — worth a bookmark if you work in discovery, facilitation, or cross-functional product strategy.

v0.79 — May 15, 2026

  • Added organic-growth-advisor — McKinsey Growth Pyramid triage for new segments, geographies, channels, or products
  • Added pm-skill-creator — interactive skill for designing repo-compliant skills via guided conversation
  • Fixed missing .claude-plugin/plugin.json that silently blocked Claude Code skill discovery
  • Added configurable input length guard (PM_MAX_INPUT) and path traversal protection to helper scripts

→ Full changelog


Contributing

Found a gap? Have a PM framework worth formalizing? The bar is pedagogic — skills must teach the why, not just the how.

See CONTRIBUTING.md for guidelines, or open an issue to start a conversation.


License

CC BY-NC-SA 4.0 — non-commercial use with share-alike.

Everything in this repository — every skill, template, and doc — is licensed CC BY-NC-SA 4.0. There is no mix of licenses here.

Some skills note in their Provenance sections that they were adapted from product-manager-prompts, Dean's earlier prompt library. That repo has the same author, so there is no license conflict: a license grants permissions to other people, and a copyright holder is free to adapt and relicense their own work. Those Provenance lines are lineage — a breadcrumb back to where an idea started — not a license dependency. No third-party MIT-licensed text is incorporated anywhere in this library.

In plain terms:

  • ✅ Use these skills in your day job — at a for-profit company, with your team, in your agents. That's what they're for.
  • ✅ Adapt and remix them — share what you build under this same license, with credit.
  • ✅ Teach with them — workshops, brown bags, mentoring, sending the ladder down.
  • ❌ Don't sell them — no repackaging the skills themselves into a paid product, course, or service without expressed written permission.
  • 🤔 Not sure your use qualifies? Open an issue and ask. If you're using these in the spirit they were built — to get better at the craft and help others do the same — the answer is almost certainly yes.

The companion prompt library, product-manager-prompts, carries the same CC BY-NC-SA 4.0 license as of its v2.3.0, with its own plain-language permissions (stricter on commercial use) — see its LICENSING.md, which governs that repo.


Questions

DevOps 与部署

中风险

  • 来源需自行核对维护者身份。
  • 未检测到明显脚本安装指令。
  • 未检测到明显外部权限要求。
  • 未检测到高风险命令。
  • 扫描发现:2 条。

Codex — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/deanpeters/Product-Manager-Skills.git
  3. 将 "skills/competitive-intel-watch" 文件夹复制到 Codex 的 skills 目录中。
  4. 重启 Codex 让新的 skill 生效。

Codex — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Codex 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Codex 让新的 skill 生效。

Claude Code — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/deanpeters/Product-Manager-Skills.git
  3. 将 "skills/competitive-intel-watch" 文件夹复制到 Claude Code 的 skills 目录中。
  4. 重启 Claude Code 让新的 skill 生效。

Claude Code — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Claude Code 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Claude Code 让新的 skill 生效。

Cursor — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/deanpeters/Product-Manager-Skills.git
  3. 将 "skills/competitive-intel-watch" 文件夹复制到 Cursor 的 skills 目录中。
  4. 重启 Cursor 让新的 skill 生效。

Cursor — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Cursor 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Cursor 让新的 skill 生效。

GitHub Copilot — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/deanpeters/Product-Manager-Skills.git
  3. 将 "skills/competitive-intel-watch" 文件夹复制到 GitHub Copilot 的 skills 目录中。
  4. 重启 GitHub Copilot 让新的 skill 生效。

GitHub Copilot — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 GitHub Copilot 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 GitHub Copilot 让新的 skill 生效。

Windsurf — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/deanpeters/Product-Manager-Skills.git
  3. 将 "skills/competitive-intel-watch" 文件夹复制到 Windsurf 的 skills 目录中。
  4. 重启 Windsurf 让新的 skill 生效。

Windsurf — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Windsurf 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Windsurf 让新的 skill 生效。
查看 SKILL.md 原文
name: competitive-intel-watch
argument-hint: "[prior snapshot (pasted/attached), and anything specific to watch]"
description: "Scheduled delta monitoring against a prior competitive snapshot. Use when tracking competitors on a cadence: material shifts only, cited evidence, battle-card update flags, runs unattended."
intent: >-
  A competitive intelligence delta monitor: given a previous Competitive Research Snapshot, sweep for
  material shifts since the last run and report only what changed — a cited changelog plus flags naming
  which battle card or positioning sections now need updating. Designed to run unattended on a loop or
  schedule; an empty changelog is a valid, useful result.
type: workflow
theme: market-intelligence
best_for:
  - "Keeping battle cards and positioning current without regenerating research weekly"
  - "Running unattended on a schedule and reporting only changes a rep or roadmap owner would act on"
  - "Turning competitive research from a one-off deliverable into a standing capability"
scenarios:
  - "Run this against last quarter's snapshot and tell me what actually changed"
  - "Set up a monthly competitor watch that flags when our battle card goes stale"
estimated_time: "10-25 min per run (after the baseline exists)"

Competitive Intel Watch

Purpose

Monitor a competitive landscape for material shifts since the last run. Diff the world against the previous snapshot; report only what changed, with evidence; flag which downstream artifacts need updating. This is the skill that turns competitive research from a document into a cadence — the weekly SIGINT sweep and monthly OSINT digest from the fusion cadence live here. A watch reports change, not state: regenerating the same report weekly is theater, and "no material shifts this cycle" is a valid, useful result.

Input

Works best with: the previous Competitive Research Snapshot (pasted or attached) — the baseline this run diffs against — and the competitor list (defaults to those in the snapshot). Also useful: anything specific you're watching for this cycle, and a materiality bar adjustment if the default needs tightening or loosening.

Input supplied inline with the invocation — text after the skill name, a pasted context dump, or an appended ARGUMENTS: line — counts as answers already given. Use it against the question budget; don't re-ask.

Arriving empty-handed? That works too. With no prior snapshot, the skill falls back to baseline mode: it produces a first snapshot using the competitive-research-snapshot structure and stops — the delta value starts on run two.

Example invocation: Competitive intel watch — prior snapshot pasted below; this cycle I'm specifically watching for pricing moves. [snapshot]

Key Concepts

  • Governing protocol: honors the autonomous-investigation contract — question budget of 2 (this skill's tightest), search-plan gate, Fact/Inference/Assumption labels, Just Enough Mode, stable schema, 4-option Final Step.
  • Discipline mix: SIGINT first (site diffs, pricing pages, job posts — the freshest layer), with OSINT and HUMINT signals monthly and FININT on the quarterly pass — the fusion cadence in intelligence-collection-disciplines is this skill's operating rhythm.
  • The materiality bar. Report a change only if a sales rep, pricing owner, or roadmap owner would plausibly act on it: pricing/packaging changes, launches and deprecations, positioning shifts, leadership moves, funding or M&A, major customer wins/losses, credible roadmap signals. Below the bar: cosmetic site changes, routine content marketing, minor releases. Why it matters: a watch that cries wolf gets ignored by cycle three — the bar is what keeps the audience.
  • Delta discipline. Read the prior snapshot fully before searching; diff against it, never regenerate it. The empty changelog is a first-class outcome.
  • Update flags close the loop. Research is only done when it names the artifact it changes — each material shift maps to the battle card, positioning, pricing, or roadmap sections now stale.
  • Do-not-invent list: competitors, features, pricing, market share, customer wins, roadmap items, product claims. Every claimed change carries a URL and a date.
  • When NOT to use: no baseline exists and you want the full treatment → run competitive-research-snapshot first; the scope itself changed (new segment, pivot) → re-snapshot from scratch rather than diffing a stale scope.

Application

  1. Determine mode. Prior snapshot provided → delta mode. None → baseline mode: produce a snapshot per the competitive-research-snapshot schema and stop.
  2. Credit inline context, then ask only the unanswered questions (max 2):
    1. Do you have the previous snapshot, or should I create a baseline?
    2. Anything specific you're watching for this cycle? If unanswered, proceed: baseline mode if no snapshot, default materiality bar otherwise.
  3. Read the prior snapshot fully before searching. The diff target is the document, not your memory of the market.
  4. Show the 3-bullet search plan — what you'll check per competitor, source types (company sites, pricing pages, release notes, press, investor materials, credible news, review sites, job postings), how facts will be separated from inference. Continue unless revised.
  5. Sweep and filter through the materiality bar. When nothing clears it, say so plainly.
  6. Emit the schema below exactly — runs must be diffable.

Output schema (do not reorder)

# Competitive Watch Report

## 1. Run Header
**Scope (from prior snapshot):** | **Prior snapshot date:** | **This run date:** | **Competitors checked:**

## 2. Changelog (Material Shifts Only)
For each material shift:
### [Competitor] — [4 to 8 word change summary]
- **What changed:** [1-2 bullets, labeled Fact/Inference]
- **Evidence:** [URL, date]
- **So what:** [why it clears the materiality bar]
- **Confidence:** [high / medium / low]

If nothing cleared the bar: "No material shifts this cycle." List
anything on the watchlist for next run.

## 3. Update Flags
| Downstream artifact | Sections needing update | Driven by |
|---|---|---|
| Battle card | | |
| Positioning statement | | |
| Pricing/packaging analysis | | |
| Roadmap assumptions | | |
Only rows with real updates; omit the rest.

## 4. Watchlist for Next Run
- [Signals below the bar but trending]
- [Open questions this run could not resolve]

### Assumptions to Validate
- [Assumption 1] / [Assumption 2] / [Assumption 3]

A copy/paste fill-in version of this schema, with quality checks, lives in template.md.

Final Step (offer exactly 4 options)

  1. Update the battle card sections flagged above (battle-card-builder)
  2. Deep-dive the most significant change
  3. Produce the refreshed full snapshot (new baseline)
  4. Adjust the materiality bar or competitor list for next run

Accept 1, 2, 3, 4, 1 and 2, Verbose Mode, or a custom path. On a scheduled, unattended run, file the report and stop — the options wait for a human.

Examples

A changelog entry that clears the bar (fictional):

Ledgerline — mid-tier plan removed from pricing page

  • What changed: the $49 "Team" tier no longer appears; feature list redistributed upward — Fact (pricing page vs. archived version, Jul 2 vs. Jun 1)
  • Evidence: URL + archive diff, dated
  • So what: entry price effectively doubled; our "cheaper to start" talking point is now stronger, and their SMB churn may spike — clears the bar for both sales and pricing owners
  • Confidence: high

The empty changelog done right:

No material shifts this cycle. Below-the-bar activity logged for trend: [Competitor B] published three thought-leadership posts on compliance automation (watchlist: possible positioning shift if their product pages follow), and two senior-engineer job posts mention a language we haven't seen in their stack before (watchlist: TECHINT corroboration needed before this means anything).

See examples/sample.md for a complete worked run (fictional FSM-software market) that diffs against the competitive-research-snapshot example's baseline — including an assumption from that baseline getting confirmed by the diff. examples/sample-industrial.md shows the quarterly-cadence industrial version, where a top risk gets demoted and that's reported as material.

Common Pitfalls

  • Regeneration theater. Producing a fresh full report each run and calling it a watch. The reader's question is "what changed?" — answer only that.
  • Materiality inflation. Reporting blog posts and minor releases to seem productive. Every below-bar item reported costs credibility the real alerts will need later.
  • Fear of the empty changelog. Padding a quiet cycle with noise. "No material change" backed by a real sweep is exactly what a healthy watch produces most cycles.
  • Undated evidence. A change claim without both URL and date can't be verified or diffed next run. The date is half the evidence.
  • Diffing a stale scope. The market pivoted, you entered a new segment — and the watch keeps diffing the old frame. Re-baseline when the scope changes; say so in the run header.
  • Orphaned intelligence. A changelog with no update flags. If no artifact needs updating, the shift probably didn't clear the bar — flags are how research becomes action.

References

发现问题?提交给管理员复核

评分:

评论 (0)

暂无评论,成为第一个评论者吧!