Agent skill

Team Health

by techwolf-ai in techwolf-ai/ai-first-toolkit

Periodic check on team dynamics, engagement signals, and development trajectory for all direct reports.

MITAuto-check passed

Install Team Health

skills CLI
$ npx skills add techwolf-ai/ai-first-toolkit --skill team-health -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install techwolf-ai/ai-first-toolkit team-health --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/techwolf-ai/ai-first-toolkit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/people-management/skills/team-health .claude/skills/team-health && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
team-health
GitHub stars
132
Token cost
~1.8k tokens
SKILL.md length
755 words
Files
3 (incl. references)
Skills in repo
29
Repo updated
First seen
Licence
MIT

At a glance

Periodic check on team dynamics, engagement signals, and development trajectory for all direct reports.

  • Works in 7 steps: Load Team Context → Scan Per Team Member → Synthesise Per Person → …
  • SKILL.md covers When to Use, Instructions and Important Notes
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Team Health is an agent skill from techwolf-ai/ai-first-toolkit. Periodic check on team dynamics, engagement signals, and development trajectory for all direct reports. Surfaces patterns across the team: who might need more challenge, who might need more support, who hasn't had a 1:1 recently. Uses two universal lenses: performance & growth, and wellbeing & connection. Outputs are prompts for reflection, not diagnoses.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/operating-principles.md` and `references/output-template.md`).

It works with Slack. The repository describes itself as: Open-source Claude Code skills and Codex skills for AI-first work. Audit, re-engineer, and bootstrap projects with AI-first design principles. The licence is MIT.

Example prompts

  • “/team-health”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Load Team Context
  2. Scan Per Team Member
  3. Synthesise Per Person
  4. Surface Team-Level Patterns
  5. Produce the Health Check
  6. Present
  7. Sub-Agent Review

What it can do on your machine

Read from SKILL.md and the folder at commit 2ee7841. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Team Health loads about 1.8k tokens when it runs, and up to ~3k if it reads all its reference files. Until then it costs about 92 tokens; SKILL.md has 755 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~92
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from techwolf-ai/ai-first-toolkit at commit 2ee7841, republished under its MIT licence (© techwolf-ai). 755 words, ~1,786 tokens.

Download SKILL.mdSave it as .claude/skills/team-health/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
team-health
description
Periodic check on team dynamics, engagement signals, and development trajectory for all direct reports. Surfaces patterns across the team: who might need more challenge, who might need more support, who hasn't had a 1:1 recently. Uses two universal lenses: performance & growth, and wellbeing & connection. Outputs are prompts for reflection, not diagnoses.

Team Health Check

Two lenses, always. "Development" asks: is this person growing and performing? "Wellbeing" asks: is this person thriving, connected, and energised? Great managers hold both.

A periodic overview of team dynamics, engagement signals, wellbeing, and development trajectory across all direct reports.

When to Use

  • Weekly or biweekly team health review
  • Before calibration or planning meetings
  • When the manager says "how's my team doing?", "team health check", "anyone I should check in with?"
  • When preparing for skip-level conversations

Instructions

If any MCP connector is unavailable, follow the connector unavailability protocol in references/operating-principles.md.

1. Load Team Context

Read from manager-context/:

  • manager-profile.md: full list of direct reports
  • team/: individual profiles with goals, projects, last review dates
  • sources.md: channels and data locations per team member

If context is missing, note it and work with available sources.

2. Scan Per Team Member

For each direct report, gather data from the last 14 days (or since last health check):

Activity & Engagement (Slack):

  • Message volume in team/project channels (relative to their baseline if known)
  • Types of messages: asking questions, answering questions, sharing updates, celebrating, flagging issues
  • Channels they're active in
  • Any public wins or recognition received
  • Any public frustration or repeated blockers

1:1 Cadence (Calendar):

  • When was their last 1:1 with the manager?
  • Were recent 1:1s kept or cancelled?
  • Are they overdue for a 1:1?

Development Goals (Notion/Drive):

  • Last time their goals were updated
  • Any progress notes or self-assessments
  • Are there development areas with no recent activity?

Workload Signals (Calendar + Slack):

  • Meeting load (heavy/normal/light for their role)
  • Are they in channels/meetings outside their usual scope? (scope expansion, could be good or concerning)

Wellbeing & Connection Signals (Slack + Calendar):

  • Energy & wellbeing: late-night messages, weekend activity, signs of overwork
  • Connection: are they participating in non-work channels (#random, social threads, team celebrations)?
  • Celebration: have they been recognised or praised recently? Have they celebrated others?
  • Tone: are their messages upbeat, neutral, or showing signs of frustration/fatigue? (use as a soft signal only, never diagnose)
  • Fun & enjoyment: any signs of passion, enthusiasm, or joy in their work (shipping excitement, sharing wins, volunteering for things)?
3. Synthesise Per Person

For each team member, produce a brief profile covering both lenses:

### [Name]: [Role]

**🎯 Development & Performance:**
**Activity:** [Normal / Increased / Decreased], [1-line evidence]
**Recent wins:** [list any, or "None surfaced"]
**Goals:** [last updated date], [current / stale]
**Development focus:** [area from goals], [evidence of progress / no visible progress]
**Growth signals:** [scope expansion, new skills, leadership behaviours, or "None"]

**🫂 Wellbeing & Connection:**
**Energy:** [Balanced / High output / Signs of overwork], [evidence, e.g., "messages after 22:00 on 3 nights"]
**Connection:** [Active in social channels / Quiet / Only work-related activity]
**Celebrated/been celebrated:** [yes, details / not recently]
**Tone:** [Positive / Neutral / Worth checking in], [soft signal only]

**Last 1:1:** [date], [on track / overdue]
**Signals to explore:** [friction, blockers, wellbeing patterns, or "None"]
4. Surface Team-Level Patterns

Look across the team for patterns in both dimensions:

🎯 Development & Performance patterns:

  • Recognition gap: Anyone who hasn't received public recognition in >2 weeks?
  • 1:1 gap: Anyone overdue for a 1:1?
  • Goal staleness: Anyone whose development goals haven't been updated in >6 weeks?
  • Growth signals: Anyone taking on new scope or showing leadership behaviours?
  • Performance signals: Anyone showing decreased engagement across multiple indicators?

🫂 Wellbeing & Connection patterns:

  • Energy imbalance: Anyone consistently working late, weekends, or showing signs of overwork?
  • Isolation risk: Anyone who's gone quiet in social channels or stopped engaging beyond work tasks?
  • Celebration deficit: Is the team celebrating wins? Are specific people consistently uncelebrated?
  • Fun factor: Is there joy and energy in team channels, or has everything become purely transactional?
  • Workload imbalance: Anyone significantly more or less loaded than peers?
Show full SKILL.md (263 more words)Show less
5. Produce the Health Check

Read references/output-template.md for the full output template structure.

6. Present
Here's your team health check. These are signals for your reflection. You know your people better than any tool.

Want me to prep a 1:1 for anyone specific?
7. Sub-Agent Review

Spawn a sub-agent to review the health check with fresh eyes. The reviewer should:

  • Check that both lenses (Development & Performance and Wellbeing & Connection) are meaningfully covered. Neither should be thin or skipped.
  • Check for baseline awareness: are signals calibrated against known baselines, or is normal behaviour being flagged?
  • Verify that language stays in "signal" territory, never crossing into diagnosis ("seems disengaged", "is struggling").
  • Check that celebration and recognition are given adequate weight, not just problem-flagging.
  • Flag any team member who appears to have very thin data. The manager should know where the blind spots are.

Incorporate the reviewer's feedback before presenting the final health check to the manager.

Important Notes

Read references/operating-principles.md for shared operating principles (data scope, DM flagging, signals vs diagnoses, connector unavailability).

Additional notes specific to this skill:

  • Celebrate first. Lead with wins, recognition, and positive energy. Wellbeing & Connection starts with seeing the good.
  • Both lenses, every time. Don't skip Wellbeing & Connection when the team is performing well. High performance without care leads to burnout. Don't skip Development & Performance when someone is struggling. Care without growth isn't enough.
  • Goals are the anchor for growth. The most actionable Development & Performance insight is usually about development goals: are they current? Is there visible progress?
  • Connection is the anchor for care. The most actionable Wellbeing & Connection insight is usually about belonging: does this person feel seen, celebrated, and connected?
  • Don't run too frequently. Weekly or biweekly is ideal. Daily health checks would over-index on noise.

© techwolf-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in plugins/people-management/skills/team-health of techwolf-ai/ai-first-toolkit.

  • SKILL.md
  • references/operating-principles.md
  • references/output-template.md

Open the folder on GitHubat commit 2ee7841

Compare with similar skills

Team Health next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Team Health compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Team Health this skilltechwolf-ai/ai-first-toolkit132—~1.8kAutomated safety check: PassMIT
Agent Browser CLIvercel-labs/agent-browser44k24 repos~864Automated safety check: PassApache-2.0
Slack GIF Creatoranthropics/skills180k29 repos~2kAutomated safety check: PassApache-2.0
Code Design Rationale Investigatorcursor/plugins11k9 repos~2.6kAutomated safety check: PassNone
Electron App Automationvercel-labs/agent-browser44k5 repos~1.7kAutomated safety check: PassApache-2.0
Slack Browser Automationvercel-labs/agent-browser44k1 repos~2.1kAutomated safety check: PassApache-2.0

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Works with

Questions about Team Health

What does Team Health do?

Periodic check on team dynamics, engagement signals, and development trajectory for all direct reports. Team Health is an agent skill from techwolf-ai/ai-first-toolkit. Periodic check on team dynamics, engagement signals, and development trajectory for all direct reports.

How do I install Team Health in Claude Code?

Run `npx skills add techwolf-ai/ai-first-toolkit --skill team-health -a claude-code`. Or copy the skill folder (plugins/people-management/skills/team-health in techwolf-ai/ai-first-toolkit) into .claude/skills/team-health in your project. Claude Code loads it when a task matches its description.

How do I install Team Health in Codex?

Run `npx skills add techwolf-ai/ai-first-toolkit --skill team-health -a codex`. Or copy the skill folder (plugins/people-management/skills/team-health in techwolf-ai/ai-first-toolkit) into .agents/skills/team-health in your project. Codex loads it when a task matches its description.

Can I use Team Health in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add techwolf-ai/ai-first-toolkit --skill team-health -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/team-health, .gemini/skills/team-health, .github/skills/team-health and .opencode/skills/team-health in your project.

What does Team Health need to run?

SKILL.md names no scripts, command-line tools or credentials: Team Health is instructions for the agent only.

Does Team Health access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Team Health safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Team Health use?

Team Health is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Team Health use?

About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.2k tokens, read only when the agent opens those files.

What are the alternatives to Team Health?

Skills that share tags, products or a category with Team Health: Agent Browser CLI (vercel-labs/agent-browser, 44k stars), Slack GIF Creator (anthropics/skills, 180k stars), Code Design Rationale Investigator (cursor/plugins, 11k stars) and Electron App Automation (vercel-labs/agent-browser, 44k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Team Health?

techwolf-ai (a GitHub organization) maintains it in techwolf-ai/ai-first-toolkit, which has 132 GitHub stars. The repository holds 29 skills in this directory. The repository was last updated on September 29, 2026.

Source: techwolf-ai/ai-first-toolkit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.