feat(project-management): add meeting-analyzer and team-communications skills
Based on PR #438 by maximcoding. Enhanced with anti-patterns, cross-references, attribution, and renamed examples/ → references/. meeting-analyzer (254 lines): - Transcript analysis: speaking dynamics, conflict detection, filler words, decision patterns, facilitation quality, active listening - Supports .txt, .md, .vtt, .srt, .docx, .json formats - Trend tracking across multiple meetings team-communications (67 lines + 4 reference templates): - Internal comms: 3P updates, newsletters, FAQ roundups, general comms - 4 reference templates with exact formatting guides - MCP integration (Slack, Gmail, Drive, Calendar) when available Co-Authored-By: maximcoding <maximcoding@users.noreply.github.com> Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Reza Rezvani
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---
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title: "Project Management Skills — Agent Skills & Codex Plugins"
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description: "7 project management skills — project management agent skill and Claude Code plugin for sprints, Jira, and Confluence. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."
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description: "9 project management skills — project management agent skill and Claude Code plugin for sprints, Jira, and Confluence. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."
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---
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<div class="domain-header" markdown>
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# :material-clipboard-check-outline: Project Management
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<p class="domain-count">7 skills in this domain</p>
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<p class="domain-count">9 skills in this domain</p>
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</div>
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@@ -41,6 +41,12 @@ description: "7 project management skills — project management agent skill and
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Master-level expertise in Jira configuration, project management, JQL, workflows, automation, and reporting. Handles ...
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- **[Meeting Insights Analyzer](meeting-analyzer.md)**
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---
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> Originally contributed by maximcoding(https://github.com/maximcoding) — enhanced and integrated by the claude-skill...
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- **[Project Management Skills](project-management.md)**
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---
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@@ -59,4 +65,10 @@ description: "7 project management skills — project management agent skill and
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Strategic project management for enterprise software, SaaS, and digital transformation initiatives. Provides portfoli...
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- **[Internal Comms](team-communications.md)**
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---
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> Originally contributed by maximcoding(https://github.com/maximcoding) — enhanced and integrated by the claude-skill...
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</div>
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266
docs/skills/project-management/meeting-analyzer.md
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266
docs/skills/project-management/meeting-analyzer.md
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---
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title: "Meeting Insights Analyzer — Agent Skill for PM"
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description: "Analyzes meeting transcripts and recordings to surface behavioral patterns, communication anti-patterns, and actionable coaching feedback. Use this. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."
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---
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# Meeting Insights Analyzer
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<div class="page-meta" markdown>
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<span class="meta-badge">:material-clipboard-check-outline: Project Management</span>
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<span class="meta-badge">:material-identifier: `meeting-analyzer`</span>
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<span class="meta-badge">:material-github: <a href="https://github.com/alirezarezvani/claude-skills/tree/main/project-management/meeting-analyzer/SKILL.md">Source</a></span>
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</div>
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<div class="install-banner" markdown>
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<span class="install-label">Install:</span> <code>claude /plugin install pm-skills</code>
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</div>
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> Originally contributed by [maximcoding](https://github.com/maximcoding) — enhanced and integrated by the claude-skills team.
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Transform meeting transcripts into concrete, evidence-backed feedback on communication patterns, leadership behaviors, and interpersonal dynamics.
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## Core Workflow
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### 1. Ingest & Inventory
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Scan the target directory for transcript files (`.txt`, `.md`, `.vtt`, `.srt`, `.docx`, `.json`).
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For each file:
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- Extract meeting date from filename or content (expect `YYYY-MM-DD` prefix or embedded timestamps)
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- Identify speaker labels — look for patterns like `Speaker 1:`, `[John]:`, `John Smith 00:14:32`, VTT/SRT cue formatting
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- Detect the user's identity: ask if ambiguous, otherwise infer from the most frequent speaker or filename hints
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- Log: filename, date, duration (from timestamps), participant count, word count
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Print a brief inventory table so the user confirms scope before heavy analysis begins.
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### 2. Normalize Transcripts
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Different tools produce wildly different formats. Normalize everything into a common internal structure before analysis:
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```
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{ speaker: string, timestamp_sec: number | null, text: string }[]
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```
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Handling per format:
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- **VTT/SRT**: Parse cue timestamps + text. Speaker labels may be inline (`<v Speaker>`) or prefixed.
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- **Plain text**: Look for `Name:` or `[Name]` prefixes per line. If no speaker labels exist, warn the user that per-speaker analysis is limited.
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- **Markdown**: Strip formatting, then treat as plain text.
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- **DOCX**: Extract text content, then treat as plain text.
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- **JSON**: Expect an array of objects with `speaker`/`text` fields (common Otter/Fireflies export).
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If timestamps are missing, degrade gracefully — skip timing-dependent metrics (speaking pace, pause analysis) but still run text-based analysis.
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### 3. Analyze
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Run all applicable analysis modules below. Each module is independent — skip any that don't apply (e.g., skip speaking ratios if there are no speaker labels).
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---
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#### Module: Speaking Dynamics
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Calculate per-speaker:
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- **Word count & percentage** of total meeting words
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- **Turn count** — how many times each person spoke
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- **Average turn length** — words per uninterrupted speaking turn
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- **Longest monologue** — flag turns exceeding 60 seconds or 200 words
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- **Interruption detection** — a turn that starts within 2 seconds of the previous speaker's last timestamp, or mid-sentence breaks
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Produce a per-meeting summary and a cross-meeting average if multiple transcripts exist.
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Red flags to surface:
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- User speaks > 60% in a 1:many meeting (dominating)
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- User speaks < 15% in a meeting they're facilitating (disengaged or over-delegating)
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- One participant never speaks (excluded voice)
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- Interruption ratio > 2:1 (user interrupts others twice as often as they're interrupted)
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---
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#### Module: Conflict & Directness
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Scan the user's speech for hedging and avoidance markers:
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**Hedging language** (score per-instance, aggregate per meeting):
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- Qualifiers: "maybe", "kind of", "sort of", "I guess", "potentially", "arguably"
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- Permission-seeking: "if that's okay", "would it be alright if", "I don't know if this is right but"
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- Deflection: "whatever you think", "up to you", "I'm flexible"
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- Softeners before disagreement: "I don't want to push back but", "this might be a dumb question"
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**Conflict avoidance patterns** (requires more context, flag with confidence level):
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- Topic changes after tension (speaker A raises problem → user pivots to logistics)
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- Agreement-without-commitment: "yeah totally" followed by no action or follow-up
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- Reframing others' concerns as smaller than stated: "it's probably not that big a deal"
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- Absent feedback in 1:1s where performance topics would be expected
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For each flagged instance, extract:
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- The full quote (with surrounding context — 2 turns before and after)
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- A severity tag: `low` (single hedge word), `medium` (pattern of hedging in one exchange), `high` (clearly avoided a necessary conversation)
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- A rewrite suggestion: what a more direct version would sound like
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---
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#### Module: Filler Words & Verbal Habits
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Count occurrences of: "um", "uh", "like" (non-comparative), "you know", "actually", "basically", "literally", "right?" (tag question), "so yeah", "I mean"
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Report:
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- Total count per meeting
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- Rate per 100 words spoken (normalizes across meeting lengths)
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- Breakdown by filler type
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- Contextual spikes — do fillers increase in specific situations? (e.g., when responding to a senior stakeholder, when giving negative feedback, when asked a question cold)
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Only flag this as an issue if the rate exceeds ~3 per 100 words. Below that, it's normal speech.
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---
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#### Module: Question Quality & Listening
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Classify the user's questions:
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- **Closed** (yes/no): "Did you finish the report?"
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- **Leading** (answer embedded): "Don't you think we should ship sooner?"
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- **Open genuine**: "What's blocking you on this?"
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- **Clarifying** (references prior speaker): "When you said X, did you mean Y?"
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- **Building** (extends another's idea): "That's interesting — what if we also Z?"
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Good listening indicators:
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- Clarifying and building questions (shows active processing)
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- Paraphrasing: "So what I'm hearing is..."
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- Referencing a point someone made earlier in the meeting
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- Asking quieter participants for input
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Poor listening indicators:
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- Asking a question that was already answered
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- Restating own point without acknowledging the response
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- Responding to a question with an unrelated topic
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Report the ratio of open/clarifying/building vs. closed/leading questions.
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---
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#### Module: Facilitation & Decision-Making
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Only apply when the user is the meeting organizer or facilitator.
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Evaluate:
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- **Agenda adherence**: Did the meeting follow a structure or drift?
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- **Time management**: How long did each topic take vs. expected?
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- **Inclusion**: Did the facilitator actively draw in quiet participants?
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- **Decision clarity**: Were decisions explicitly stated? ("So we're going with option B — Sarah owns the follow-up by Friday.")
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- **Action items**: Were they assigned with owners and deadlines, or left vague?
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- **Parking lot discipline**: Were off-topic items acknowledged and deferred, or did they derail?
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---
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#### Module: Sentiment & Energy
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Track the emotional arc of the user's language across the meeting:
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- **Positive markers**: enthusiastic agreement, encouragement, humor, praise
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- **Negative markers**: frustration, dismissiveness, sarcasm, curt responses
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- **Neutral/flat**: low-energy responses, monosyllabic answers
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Flag energy drops — moments where the user's engagement visibly decreases (shorter turns, less substantive responses). These often correlate with discomfort, boredom, or avoidance.
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---
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### 4. Output the Report
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Structure the final output as a single cohesive report. Use this skeleton — omit any section where data was insufficient:
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```markdown
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# Meeting Insights Report
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**Period**: [earliest date] – [latest date]
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**Meetings analyzed**: [count]
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**Total transcript words**: [count]
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**Your speaking share (avg)**: [X%]
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---
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## Top 3 Findings
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[Rank by impact. Each finding gets 2-3 sentences + one concrete example with a direct quote and timestamp.]
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## Detailed Analysis
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### Speaking Dynamics
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[Stats table + narrative interpretation + flagged red flags]
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### Directness & Conflict Patterns
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[Flagged instances grouped by pattern type, with quotes and rewrites]
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### Verbal Habits
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[Filler word stats, contextual spikes, only if rate > 3/100 words]
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### Listening & Questions
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[Question type breakdown, listening indicators, specific examples]
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### Facilitation
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[Only if applicable — agenda, decisions, action items]
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### Energy & Sentiment
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[Arc summary, flagged drops]
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## Strengths
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[3 specific things the user does well, with evidence]
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## Growth Opportunities
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[3 ranked by impact, each with: what to change, why it matters, a concrete "try this next time" action]
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## Comparison to Previous Period
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[Only if prior analysis exists — delta on key metrics]
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```
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### 5. Follow-Up Options
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After delivering the report, offer:
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- Deep dive into any specific meeting or pattern
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- A 1-page "communication cheat sheet" with the user's top 3 habits to change
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- Tracking setup — save current metrics as a baseline for future comparison
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- Export as markdown or structured JSON for use in performance reviews
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---
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## Edge Cases
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- **No speaker labels**: Warn the user upfront. Run text-level analysis (filler words, question types on the full transcript) but skip per-speaker metrics. Suggest re-exporting with speaker diarization enabled.
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- **Very short meetings** (< 5 minutes or < 500 words): Analyze but caveat that patterns from short meetings may not be representative.
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- **Non-English transcripts**: The filler word and hedging dictionaries are English-centric. For other languages, note the limitation and focus on structural analysis (speaking ratios, turn-taking, question counts).
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- **Single meeting vs. corpus**: If only one transcript, skip trend/comparison language. Focus findings on that meeting alone.
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- **User not identified**: If you can't determine which speaker is the user after scanning, ask before proceeding. Don't guess.
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## Transcript Source Tips
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Include this section in output only if the user seems unsure about how to get transcripts:
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- **Zoom**: Settings → Recording → enable "Audio transcript". Download `.vtt` from cloud recordings.
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- **Google Meet**: Auto-transcription saves to Google Docs in the calendar event's Drive folder.
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- **Granola**: Exports to markdown. Best speaker label quality of consumer tools.
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- **Otter.ai**: Export as `.txt` or `.json` from the web dashboard.
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- **Fireflies.ai**: Export as `.docx` or `.json` — both work.
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- **Microsoft Teams**: Transcripts appear in the meeting chat. Download as `.vtt`.
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Recommend `YYYY-MM-DD - Meeting Name.ext` naming convention for easy chronological analysis.
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---
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## Anti-Patterns
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| Anti-Pattern | Why It Fails | Better Approach |
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|---|---|---|
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| Analyzing without speaker labels | Per-person metrics impossible — results are generic word clouds | Ask user to re-export with speaker identification enabled |
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| Running all modules on a 5-minute standup | Overkill — filler word and conflict analysis need 20+ min meetings | Auto-detect meeting length and skip irrelevant modules |
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| Presenting raw metrics without context | "You said 'um' 47 times" is demoralizing without benchmarks | Always compare to norms and show trajectory over time |
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| Analyzing a single meeting in isolation | One meeting is a snapshot, not a pattern — conclusions are unreliable | Require 3+ meetings minimum for trend-based coaching |
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| Treating speaking time equality as the goal | A facilitator SHOULD talk less; a presenter SHOULD talk more | Weight speaking ratios by meeting type and role |
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| Flagging every hedge word as negative | "I think" and "maybe" are appropriate in brainstorming | Distinguish between decision meetings (hedges are bad) and ideation (hedges are fine) |
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---
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## Related Skills
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| Skill | Relationship |
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|-------|-------------|
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| `project-management/senior-pm` | Broader PM scope — use for project planning, risk, stakeholders |
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| `project-management/scrum-master` | Agile ceremonies — pairs with meeting-analyzer for retro quality |
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| `project-management/confluence-expert` | Store meeting analysis outputs as Confluence pages |
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| `c-level-advisor/executive-mentor` | Executive communication coaching — complementary perspective |
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78
docs/skills/project-management/team-communications.md
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78
docs/skills/project-management/team-communications.md
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@@ -0,0 +1,78 @@
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---
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title: "Internal Comms — Agent Skill for PM"
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description: "Write internal company communications — 3P updates (Progress/Plans/Problems), company-wide newsletters, FAQ roundups, incident reports, leadership. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."
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---
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# Internal Comms
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<div class="page-meta" markdown>
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<span class="meta-badge">:material-clipboard-check-outline: Project Management</span>
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<span class="meta-badge">:material-identifier: `team-communications`</span>
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<span class="meta-badge">:material-github: <a href="https://github.com/alirezarezvani/claude-skills/tree/main/project-management/team-communications/SKILL.md">Source</a></span>
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</div>
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<div class="install-banner" markdown>
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<span class="install-label">Install:</span> <code>claude /plugin install pm-skills</code>
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</div>
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> Originally contributed by [maximcoding](https://github.com/maximcoding) — enhanced and integrated by the claude-skills team.
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Write polished internal communications by loading the right reference file, gathering context, and outputting in the company's exact format.
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## Routing
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Identify the communication type from the user's request, then read the matching reference file before writing anything:
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| Type | Trigger phrases | Reference file |
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|---|---|---|
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| **3P Update** | "3P", "progress plans problems", "weekly team update", "what did we ship" | `references/3p-updates.md` |
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| **Newsletter** | "newsletter", "company update", "weekly/monthly roundup", "all-hands summary" | `references/company-newsletter.md` |
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| **FAQ** | "FAQ", "common questions", "what people are asking", "confusion around" | `references/faq-answers.md` |
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| **General** | anything internal that doesn't match above | `references/general-comms.md` |
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If the type is ambiguous, ask one clarifying question — don't guess.
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## Workflow
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1. **Read the reference file** for the matched type. Follow its formatting exactly.
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2. **Gather inputs.** Use available MCP tools (Slack, Gmail, Google Drive, Calendar) to pull real data. If no tools are connected, ask the user to provide bullet points or raw context.
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3. **Clarify scope.** Confirm: team name (for 3Ps), time period, audience, and any specific items the user wants included or excluded.
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4. **Draft.** Follow the format, tone, and length constraints from the reference file precisely. Do not invent a new format.
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5. **Present the draft** and ask if anything needs to be added, removed, or reworded.
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## Tone & Style (applies to all types)
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- Use "we" — you are part of the company.
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- Active voice, present tense for progress, future tense for plans.
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- Concise. Every sentence should carry information. Cut filler.
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- Include metrics and links wherever possible.
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- Professional but approachable — not corporate-speak.
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- Put the most important information first.
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## When tools are unavailable
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If the user hasn't connected Slack, Gmail, Drive, or Calendar, don't stall. Ask them to paste or describe what they want covered. You're formatting and sharpening — that's still valuable. Mention which tools would improve future drafts so they can connect them later.
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---
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## Anti-Patterns
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| Anti-Pattern | Why It Fails | Better Approach |
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|---|---|---|
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| Writing updates without reading the reference template first | Output won't match company format — user has to reformat | Always load the matching reference file before drafting |
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| Inventing metrics or accomplishments | Internal comms must be factual — fabrication destroys trust | Only include data the user provided or MCP tools retrieved |
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| Using passive voice for accomplishments | "The feature was shipped" hides who did the work | "Team X shipped the feature" — active voice credits the team |
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| Writing walls of text for status updates | Leadership scans, doesn't read — key info gets buried | Lead with the headline, follow with 3-5 bullet points |
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| Sending without confirming audience | A team update reads differently from a company-wide newsletter | Always confirm: who will read this? |
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---
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## Related Skills
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| Skill | Relationship |
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|-------|-------------|
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| `project-management/senior-pm` | Broader PM scope — status reports feed into PM reporting |
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| `project-management/meeting-analyzer` | Meeting insights can feed into 3P updates and status reports |
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| `project-management/confluence-expert` | Publish comms as Confluence pages for permanent record |
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| `marketing-skill/content-production` | External comms — use for public-facing content, not internal |
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Reference in New Issue
Block a user