Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/yonggao/claude-plugins/team_analyticsgit clone --depth 1 https://github.com/yonggao/claude-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/yonggao/claude-plugins/team_analytics)<a href="https://agentmods.dev/commands/yonggao/claude-plugins/team_analytics"><img src="https://agentmods.dev/badge/commands/yonggao/claude-plugins/team_analytics.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00018 | $0.00980 |
| Opus 5 | $0.00009 | $0.00490 |
| Sonnet 5 | $0.00004 | $0.00196 |
| Haiku 4.5 | $0.00002 | $0.00098 |
Grade A, and why
team_analytics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Team Git Analytics
Analyze the git commit history across all repositories in the current directory to understand team activity patterns, individual developer contributions, performance metrics, and working areas.
Analysis Parameters
- Time Period: $ARGUMENTS (default: "90 days ago" if not specified)
- Scope: All subdirectories containing git repositories
- Focus: Developer-specific metrics, collaboration patterns, repository health
Execution Instructions
Please perform a comprehensive git analysis following these steps:
1. Repository Discovery
First, discover all git repositories in the current directory and subdirectories:
find . -maxdepth 2 -name ".git" -type d
Then list the subdirectories to identify repositories:
ls -la
2. Data Collection Phase
For each repository directory found, navigate to it and collect detailed git data using the time period: $ARGUMENTS (or "90 days ago" if no arguments provided).
For each repository, execute these git commands:
Basic repository info:
git status
git branch --show-current
Commit statistics:
git rev-list --count --since="90 days ago" HEAD
git shortlog --since="90 days ago" -sne
Detailed commit history:
git log --since="90 days ago" --pretty=format:"%H|%an|%ae|%ad|%s" --date=iso
File change statistics:
git log --since="90 days ago" --numstat --pretty=format:"%an|%ad" --date=short
Most active files:
git log --since="90 days ago" --name-only --pretty=format:
Author activity:
git log --since="90 days ago" --pretty=format:"%an"
3. Analysis Instructions
Based on the collected git data from all repositories, provide a comprehensive analysis including:
Developer Profiles (per individual):
- Commit Activity: Total commits, commit frequency, timeline patterns
- Code Changes: Lines added/deleted, net contribution, change velocity
- Working Areas: Primary files/directories worked on, specialization areas
- Collaboration: Cross-repository contributions, patterns across repos
- Commit Patterns: Timing patterns, commit message analysis, work categorization
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 162 lines · 18 tokens per session scan A d8afdd2a99e6
team_analytics is a command published in the GitHub repository yonggao/claude-plugins (2 stars, last pushed 8mo ago), licensed MIT. It adds 18 tokens to every session and 980 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.