SkillAtlasSkill 详情

professional-communication

Essays and writing behind this toolkit live at vexjoy.com.

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项目 README

来源文件:README.md

抓取于 2026年8月31日

VexJoy Agent

VexJoy Agent

Essays and writing behind this toolkit live at vexjoy.com.

AI agents skip steps.

"Looks correct" replaces running tests. "Trivial change" replaces verification. The agent confidently ships broken code because nothing structurally prevented it from skipping the work.

Harnesses have a second problem: given only a skill list, they do not route eagerly enough, or correctly enough. Good skills sit unused. So this toolkit connects the skills, agents, and workflows we want directly into the harness, automatically. You don't have to understand what is here. Say what you want in plain English and you get all the value we have put into it: the right specialist with the right methodology, behind gates that demand exit codes, not assertions.

44 domain agents, 122 workflow skills, 78 hooks, 136 scripts. Agents carry knowledge, skills enforce methodology, hooks block incomplete work, scripts handle determinism.

Works across Claude Code (/do), Codex ($do), Factory (/do), Reasonix (/do).

What It Looks Like

$ claude

> /do debug this Go test

  Routing: go-engineer + systematic-debugging
  Phase 1/4: Reproduce: running test, capturing failure...
  Phase 2/4: Hypothesize: 3 candidates from stack trace...
  Phase 3/4: Verify: isolated root cause in connection pool timeout
  Phase 4/4: Fix: patch applied, test passing, PR opened

  ✓ Delivered: PR #847, fix connection pool timeout in health check

The router reads intent, picks a Go agent paired with a debugging skill, and runs the full lifecycle. You typed one sentence. The system did the rest.

The Pipeline

  ROUTE        PLAN         EXECUTE      VERIFY       DELIVER      RECORD
 ┌──────┐    ┌──────┐    ┌──────┐    ┌──────┐    ┌──────┐    ┌──────┐
 │ /do  │───▶│ Task │───▶│Agent │───▶│Tests │───▶│  PR  │───▶│Route │
 │Router│    │ Plan │    │+Skill│    │Gates │    │Branch│    │Result│
 └──────┘    └──────┘    └──────┘    └──────┘    └──────┘    └──────┘

Anti-Rationalization

This is the single thing that separates it from "agent with a system prompt."

Agent SaysWhat Happens
"Code looks correct, skip tests"Exit gate requires test output. Blocked.
"Trivial change, no verification"Hook blocks completion without evidence.
"Similar to before"Skill demands case-specific proof.
"User is in a hurry"Protocol overrides time pressure.
"I'm confident"Gate demands exit code, not assertion.

Hooks fire automatically. Gates block completion. Skills encode counter-arguments at every skip-worthy step. The agent verifies or it doesn't finish.

For what I do, the difference is enormous. If you're doing simple single-file edits, maybe less so.

Knowledge Work Is First-Class

The same routing serves knowledge work. The content engine researches, drafts in a calibrated voice, validates against 397 AI patterns, and repurposes finished pieces for each platform. /html turns any request into a single self-contained HTML file: report, slide deck, prototype, data viz, diagram. Non-engineers who try the toolkit consistently name the HTML artifacts as the thing they love. No code, no setup beyond the installer.

It Proves Its Own Changes

Changes to the toolkit itself ship with evidence. New skills get blind A/B tests against a no-skill baseline before merge. Routing and writing-standard decisions carry measured verdicts; PHILOSOPHY.md cites the numbers. Experiments that lost go into the negative-results registry, what-didnt-work.md; the registry now covers routing reversals, unvalidated A/B citations, and disabled lint rules alongside the original program refutations.

The automated nightly evolution loop (/evolve, writes to evolution-reports/) ran regularly through mid-May 2026. It is currently dormant; recent evidence has come from manual PRs instead.

Installation

git clone https://github.com/notque/vexjoy-agent.git ~/vexjoy-agent
cd ~/vexjoy-agent
./install.sh

Links into ~/.claude/ and mirrors into ~/.codex/, ~/.factory/, ~/.reasonix/ — each mirror only when that runtime is detected (its command on PATH or its home dir already exists). The installer asks symlink (live updates via git pull) or copy (stable snapshot).

Want only part of the toolkit? Run ./install.sh --configure to pick which skills, agents, and hooks install, or copy .local.example/profile.yaml to .local/profile.yaml and edit. No profile file = full install, unchanged behavior. Credit: @thomasvan. Details: .local.example/README.md.

CLIEntry Point
Claude Code/do
Codex$do
Factory/do
Reasonix/do

Full setup: docs/start-here.md

Codex CLI Parity

Mirrors agents, skills, and supported hooks into ~/.codex/. The original six-hook allowlist was correct for Codex v0.114, when tool hooks only intercepted Bash. Current support requires Codex v0.144.1+ and classifies the 74 Claude hook registrations as 26 native, 35 adapter-backed, and 13 unsupported (61 supported). These are registration counts, not unique hook files. The installer also preserves explicit per-subagent model routing for GPT-5.6 Sol by setting the MultiAgent V2 compatibility keys documented in openai/codex#31814.

Codex now exposes apply_patch to tool hooks. VexJoy's adapter converts each patch operation into the Write/Edit payload expected by existing guards, but it cannot intercept writes performed through unified_exec, unmatched MCP tools, WebSearch, or other unsupported tool paths. PreCompact and Stop adapters also receive less telemetry than Claude Code: Codex does not provide Claude's conversation_history or session_data. This is expanded compatibility, not full Claude parity.

After install or any hook-definition change, run /hooks in Codex and review the new definitions before trusting them. Codex hash-trusts hook commands and skips changed, unreviewed definitions.

Gemini CLI / Antigravity CLI Support (removed)

Gemini CLI support removed (deprecated upstream, transitioned to Antigravity CLI); Antigravity support pending CLI maturity. Per Google's transition announcement, Gemini CLI stops serving requests on 2026-06-18 for Google AI Pro / Ultra and free Gemini Code Assist for individuals. Gemini API integrations (image-gen backends, sprite pipeline, GEMINI_API_KEY) are unaffected and stay in the toolkit.

If a prior install mirrored into ~/.gemini/, remove the stale mirrors with:

rm -rf ~/.gemini/skills ~/.gemini/agents ~/.gemini/hooks ~/.gemini/scripts ~/.gemini/antigravity/plugins/vexjoy-agent
Factory CLI Support

Mirrors agents (as "droids"), skills, and all hooks into ~/.factory/. Hook config merges into ~/.factory/settings.json with paths rewritten.

Reasonix Support

Mirrors skills, scripts, and the allowlisted hooks (scripts/reasonix-hooks-allowlist.txt) into ~/.reasonix/ (no agent or custom-command surface, so neither is installed; the /do router rides in as a skill). Reasonix fires only 4 events (PreToolUse, PostToolUse, UserPromptSubmit, Stop), so only hooks for those events are allowlisted. Hook config is written to the hooks key of ~/.reasonix/settings.json in Reasonix's native flat shape (one entry per hook, match regex over the tool name); the generator builds absolute python3 commands, so no path rewrite is applied. MCP/model/permissions in ~/.reasonix/config.json are user-owned and left untouched.

Token-saving mode

The toolkit supplies its own routing, domain knowledge, methodology, and enforcement. The default system prompt duplicates most of that.

claude --system-prompt "."

Strips built-in tool-use instructions. The toolkit's agents, skills, hooks, and CLAUDE.md provide equivalent coverage.

Four Layers

LayerCountDoes
Agents44Domain knowledge: idiom tables, failure mode catalogs, error-to-fix mappings
Skills122Phased methodology with gates. Can't skip steps. Each phase has exit criteria requiring evidence.
Hooks78Fire on lifecycle events. Block incomplete work. Zero LLM cost.
Scripts136Determinism: test runners, linters, validators. No LLM judgment.

Full skill catalog: docs/skills.md.

┌─────────────────────────────────────────────────┐
│  SKILL.md                                       │
│  ┌─ Frontmatter ─────────────────────────────┐  │
│  │ triggers, pairs_with, success-criteria     │  │
│  └────────────────────────────────────────────┘  │
│  Reference Loading Table (conditional imports)   │
│  Phased Instructions (numbered, with gates)      │
│  Verification (evidence requirements)            │
└─────────────────────────────────────────────────┘

Built with the Toolkit

A game built entirely by Claude Code using these agents, skills, and pipelines:

Choose Your Path

I just want to use it Install, learn /do, done.

I do knowledge work Writing, research, data analysis, moderation, HTML artifacts. No code.

I'm a developer Architecture, extension points, adding agents and skills.

I'm an AI power user Routing tables, pipelines, hooks, telemetry DB.

I'm an AI agent Machine-dense inventory. Tables, paths, schemas.

I'm on LinkedIn 🚀 Thought leadership. Agree? 👇

Philosophy

  • Zero-expertise operation. Say what you want. The system classifies, dispatches, enforces, delivers.
  • LLMs orchestrate, programs execute. Deterministic work belongs to scripts. LLM judgment handles design decisions, diagnosis, review.
  • Density. Every word carries instruction, rule, or decision. Cut everything else.
  • Breadth over depth. Right context ensures correctness. Unfocused context adds cost.
  • Structural enforcement. Exit codes enforce what instructions can't. Quality gates are automated, not advisory.
  • Everything pipelines. Complex work decomposes into phases. Phases have gates. Gates prevent cascading failures.

Full design philosophy: PHILOSOPHY.md

Maintenance

One report-only script surfaces upkeep work; it prints a digest and never edits, deletes, or blocks.

  • python3 scripts/stale-skill-scan.py --top 20 ranks stale skills and agents as pruning candidates. Run it quarterly; see docs/deprecation-template.md.

Scheduled work follows the same boundary as everything else: judgment uses agents; repeatable plumbing uses scripts.

NeedUse
Run a deterministic command on a schedulescripts/agent-scheduler.py with runner: "command"
Run an agent judgment on a schedule, webhook, or file changescripts/agent-scheduler.py with the default runner: "claude"
Install or remove a user crontab entry safelyscripts/crontab-manager.py
Audit shell cron reliabilitycron-automation
Keep one interactive objective moving until criteria verifyobjective-loop

Contributing

See CONTRIBUTING.md.

License

MIT. See LICENSE.

其他

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:1 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/notque/vexjoy-agent.git
  3. 将 "skills/content/professional-communication" 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/notque/vexjoy-agent.git
  3. 将 "skills/content/professional-communication" 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/notque/vexjoy-agent.git
  3. 将 "skills/content/professional-communication" 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/notque/vexjoy-agent.git
  3. 将 "skills/content/professional-communication" 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/notque/vexjoy-agent.git
  3. 将 "skills/content/professional-communication" 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: professional-communication
description: "Draft interpersonal and meeting messages: emails, memos, status updates, structured pushback or disagreement."
user-invocable: false
allowed-tools:
  - Read
  - Write
routing:
  triggers:
    - "business communication"
    - "structured format"
    - "clear writing"
    - "write email"
    - "draft memo"
    - "executive summary"
    - "summarize for management"
    - "status update"
    - "compose email"
    - "draft response"
    - "reply to my boss"
    - "reply to manager"
    - "help me write back"
    - "work email"
    - "meeting summary"
    - "meeting notes"
    - "write a message to"
    - "pushback email"
    - "disagree professionally"
    - "difficult conversation"
  not_for: "critiquing or stress-testing a proposal's merits — that is multi-persona-critique; deciding what to prioritize or work on next — that is productivity; writing blog posts or articles with a voice profile — that is voice-writer. This drafts interpersonal messages; it does not judge ideas, set priorities, or generate content."
  category: content-creation
  pairs_with:
    - voice-writer

Professional Communication Skill

Overview

This skill transforms dense technical communication into clear, structured business formats using proposition extraction (identify all facts and relationships) and deterministic templates (apply consistent structure). It extracts every detail without loss, categorizes by business relevance, applies a standard template with professional tone, and verifies completeness before delivery.

Core principle: Transformation ≠ creation. Only restructure existing input; always extract from existing input and restructure it for executive clarity with preserved technical accuracy.


Reference Loading Table

SignalLoad These FilesWhy
transforming raw engineer notes: stream-of-consciousness debugging, blockers, crisis updatesexamples.mdLoads detailed guidance from examples.md.
drafting from section templates; phrase transformationstemplates.mdLoads detailed guidance from templates.md.

Instructions

Phase 1: PARSE

Goal: Extract every proposition from the input before structuring anything. This prevents information loss and ensures technical accuracy is preserved.

Step 1: Classify input type

Identify the communication type (this determines categorization strategy in Phase 2):

  • Technical update (progress report with embedded facts)
  • Debugging narrative (stream-of-consciousness problem-solving)
  • Status report (project state with blockers/dependencies)
  • Dependency discussion (constraints buried in defensive language)

Step 2: Extract all propositions

Parse each sentence systematically. Extract all propositions before summarizing — summarizing skips propositions and loses facts:

  1. Facts: All distinct statements of truth
  2. Implications: Cause-effect relationships
  3. Temporal markers: Past/present/future actions
  4. System references: All mentioned components
  5. Blockers: Hidden dependencies and constraints
  6. Emotional context: Frustration/satisfaction/urgency indicators (needed to transform defensive language)

Step 3: Document implicit context

Surface assumptions the author takes for granted but the audience needs stated. Non-technical audiences cannot act without this:

  • Technical acronyms or project names the audience may not know
  • Timeline context (when things happened relative to milestones)
  • Organizational context (team relationships, reporting structures)

Step 4: Count and validate propositions

## Parsing Result
Input type: [technical update | debugging narrative | status report | dependency discussion]
Proposition count: [N distinct facts/claims]
Emotional markers: [frustration | satisfaction | urgency | neutral]

Extracted Propositions:
1. [Fact/claim 1]
2. [Fact/claim 2]
... (ALL propositions - NO information loss)

Implicit Context:
- [Assumption 1]
- [Assumption 2]

Gate: ALL propositions extracted with zero information loss. Proceed only when gate passes.

Phase 2: STRUCTURE

Goal: Categorize and prioritize all extracted propositions by business relevance. This prevents unsolicited sections and keeps output focused on what matters most.

Step 1: Categorize propositions

Organize by type (categorization determines template section placement):

Status:   [items with current state]
Actions:  [completed, in-progress, planned]
Impacts:  [business and technical consequences]
Blockers: [dependencies, constraints]
Next:     [required actions]

Step 2: Priority order

Rank by impact to executive decision-making, not completeness:

  1. Business Impact (revenue, customer, strategic)
  2. Technical Functionality (core operation)
  3. Project Timeline (schedule implications)
  4. Resource Requirements (personnel, infrastructure)
  5. Risk Management (potential issues)

Only the highest-priority categories go into the output. Lower-priority items are preserved in Technical Details but not emphasized.

Step 3: Identify information gaps

Flag any propositions that need clarification before transformation. Ask for specifics only when severity classification is ambiguous:

  • Ambiguous severity (could be GREEN or YELLOW — default to YELLOW if unclear)
  • Missing ownership for action items (block on clarity, ask for clarity)
  • Undefined technical terms critical to business impact (ask for definition)

Gate: All propositions categorized and prioritized. Proceed only when gate passes.

Phase 3: TRANSFORM

Goal: Apply standard template with professional tone. This ensures consistent, executive-ready formatting without speculative sections.

Step 1: Apply standard template

Include only the sections in the standard template (Risk Assessment, Historical Context, Mitigation Strategies). Use ONLY this structure:

**STATUS**: [GREEN|YELLOW|RED]
**KEY POINT**: [Single most important business takeaway]

**Summary**:
- [Primary accomplishment/issue]: [Business impact]
- [Current focus/blocker]: [Expected outcome/resolution need]
- [Secondary consideration]: [Implications]

**Technical Details**:
[2-3 sentences maximum preserving technical accuracy]

**Next Steps**:
1. [Specific action with timeline if available]
2. [Secondary action with ownership implications]
3. [Follow-up considerations]

Step 2: Tone adjustment

The transformation rules are deterministic (apply all):

  • Strip hedging language: "I think we might need to..." → "Deploy X to address Y"
  • Transform defensive tone: "We had to rollback because..." → "Rolled back to [previous version] due to [root cause]"
  • Preserve urgency markers and severity indicators (needed for status classification)
  • Keep technical terms intact (oversimplification loses information; non-technical audiences still need accuracy)
  • Maintain causal chains and specific metrics (specific > generic)

Step 3: Status classification

Apply criteria consistently (inconsistency confuses stakeholders and erodes trust):

  • GREEN: Fully complete with no follow-up, all verification done
  • YELLOW: Resolved with follow-up needed, blocked on dependencies, partial completion
  • RED: Active critical issues, production impact, urgent intervention needed

Always document reasoning: "Status: YELLOW (deployment successful but monitoring pending)" not just "Status: YELLOW"

Step 4: Action item specificity

Vague action items cannot be executed. Every next step MUST include:

  • Specific action verb (investigate, deploy, coordinate, document) — "fix" is too vague
  • Clear scope (what exactly needs doing) — define the boundary
  • Ownership implication (who or which team) — someone must be accountable
  • Timeline marker when available (IMMEDIATE, by EOW, this sprint) — explicit > implied

Gate: Output follows template structure with professional tone and all specificity rules applied. Proceed only when gate passes.

Phase 4: VERIFY

Goal: Confirm transformation quality before delivery. All gates must pass; proceed only when complete.

Step 1: Compare output against extracted propositions — NO information loss allowed. If a fact from Phase 1 doesn't appear in output, it belongs in Technical Details.

Step 2: Verify technical accuracy — terms, metrics, causal chains preserved exactly. Preserve exact technical terms ("database issues" for "Redis cluster failover") — specificity is required.

Step 3: Confirm status indicator matches actual severity. Check reasoning against actual criteria (GREEN ≠ YELLOW vs YELLOW ≠ RED boundaries).

Step 4: Validate action items are specific — check each next step for (verb, scope, owner, timeline). "Fix the issue" fails; "Complete Redis failover testing in staging (DevOps, by EOW)" passes.

Step 5: Check appropriate detail level for target audience. If audience is non-technical, Technical Details should bridge jargon with plain explanations without losing precision.

Step 6: Document transformation summary to prove gate passage:

## Transformation Summary
Input type: [type]
Propositions extracted: [N]
Status assigned: [GREEN|YELLOW|RED] ([reasoning])
Information loss: None
Template applied: standard

Gate: All verification checks pass. Transformation is complete. Complete all 6 steps before delivering.


Examples

Example 1: Multi-Propositional Sentence

User says: "I fixed the database issue but then the API started failing so I had to rollback and now we're investigating the connection pool settings which might be related to the recent Kubernetes upgrade." Actions:

  1. Extract 5 propositions: DB fix, API failure, rollback, pool investigation, K8s link (PARSE)
  2. Categorize: Status=rollback done, Blockers=pool+K8s, Actions=investigating (STRUCTURE)
  3. Apply template with YELLOW status, specific next steps (TRANSFORM)
  4. Verify no facts lost, technical terms preserved (VERIFY) Result: Structured update with clear status and actionable next steps

Example 2: Defensive Blocker Communication

User says: "I can't make progress because the API team hasn't responded in 3 days and my sprint is at risk" Actions:

  1. Extract urgency, duration, dependency, impact propositions (PARSE)
  2. Categorize: Blocker=API spec, Impact=sprint risk, Timeline=3 days (STRUCTURE)
  3. Apply template with YELLOW status, escalation-focused next steps (TRANSFORM)
  4. Verify urgency preserved, defensive tone neutralized (VERIFY) Result: Neutral status report with clear escalation path

Example 3: Crisis Communication

User says: "The latest deploy broke checkout completely, users are getting 500 errors, we rolled back but some orders might be lost" Actions:

  1. Extract severity, system affected, user impact, rollback status, data risk (PARSE)
  2. Categorize: Status=rolled back, Impact=orders lost, Blocker=data recovery (STRUCTURE)
  3. Apply template with RED status, IMMEDIATE/URGENT tiered next steps (TRANSFORM)
  4. Verify crisis severity reflected, no false reassurance in tone (VERIFY) Result: RED status report with tiered emergency response actions

Error Handling

Error: "Missing Context in Input"

Cause: Technical terms or acronyms critical to business impact are undefined.

Solution:

  1. Ask user for clarification on terms critical to status classification — speculation causes wrong status assignments
  2. Make reasonable inferences only for minor details; flag all assumptions explicitly in Technical Details section
  3. Complete transformation while waiting — provide output with a note: "Status classification assumed X because Y was undefined"

Error: "Ambiguous Status Classification"

Cause: Input contains mixed signals (e.g., issue resolved but monitoring incomplete).

Solution:

  1. Default to YELLOW when unclear between GREEN/YELLOW — YELLOW preserves urgency for follow-up without false reassurance
  2. Default to RED only with clear critical indicators: production impact (users affected), data loss (unrecoverable), or ongoing crisis (not yet mitigated)
  3. Document reasoning in parenthetical: "Status: YELLOW (deployment successful but monitoring pending)" — transparency prevents misinterpretation

Error: "Multi-Thread Update Contamination"

Cause: Input contains multiple unrelated topics that could cross-contaminate status classifications.

Solution:

  1. Process each thread as separate proposition set (Phase 1 extraction per thread)
  2. Apply template independently to each thread (Phase 2-3 per thread)
  3. Combine with clear thread identification in final output (use headers: "Thread A: Deployment", "Thread B: Data Recovery")
  4. Ensure status indicators are thread-specific (Thread A may be GREEN while Thread B is RED) — separate outcomes, separate classifications

Error Handling Principles

Constraint distribution in error handling:

  • Summarizing before extracting = loses facts. Complete Phase 1 fully before proceeding.
  • Status is "obvious" = assumption. Apply classification criteria consistently, document reasoning.
  • Technical details not needed for non-technical audience = false. Always include Technical Details; bridge jargon with explanation.
  • Action items are implied = stakeholders cannot execute implied work. Write explicit (verb, scope, owner, timeline) for every next step.
  • Professional tone is "close enough" = defensive language still embedded. Apply ALL transformation rules: hedging → direct, emotional → neutral, vague → specific.

References

Reference Files

  • ${CLAUDE_SKILL_DIR}/references/templates.md: Status-specific templates, section formats, phrase transformations
  • ${CLAUDE_SKILL_DIR}/references/examples.md: Complete transformation examples with proposition extraction

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