Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/wangke19/gemini-ai-helpersnpx agentmods add commands/wangke19/gemini-ai-helpers/list-teamsWrote 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/wangke19/gemini-ai-helpers/list-teams)<a href="https://agentmods.dev/commands/wangke19/gemini-ai-helpers/list-teams"><img src="https://agentmods.dev/badge/commands/wangke19/gemini-ai-helpers/list-teams/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/wangke19/gemini-ai-helpers/list-teams"><img src="https://agentmods.dev/badge/commands/wangke19/gemini-ai-helpers/list-teams.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00008 | $0.00693 |
| Opus 5 | $0.00004 | $0.00347 |
| Sonnet 5 | $0.00002 | $0.00139 |
| Haiku 4.5 | $0.00001 | $0.00069 |
Grade A, and why
list-teams 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 9d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Name
teams:list-teams
Synopsis
/teams:list-teams
Description
The teams:list-teams command displays all team names from the team component mapping.
Note: The underlying script returns rich team data (components, description, repos, team_size, slack_channels), but this command presents only a concise list of team names. The full team data is available to the AI agent for context but should not be displayed to the user unless specifically requested.
This command is useful for:
- Discovering available teams
- Validating team names before using them in other commands
- Finding team names for use with
/teams:list-components --teamor/teams:health-check --team
Implementation
-
Verify Working Directory
- Ensure you are in the repository root directory
-
Run the list-teams Script
python3 extensions/teams/skills/list-teams/list_teams.py
-
Parse and Display Results
- Script outputs JSON with
total_teamsandteamsobject/array - New format (after regeneration):
teamsis a dictionary mapping team names to team info objects containing:components: Array of OCPBUGS component namesdescription: Team descriptionteam_size: Number of team membersrepos: Array of repository namesslack_channels: Array of Slack channel names (forum type only)
- Old format (before regeneration):
teamsis a simple array of team names - Display to user: Only show team names in a concise list format, regardless of which format is returned
- Use internally: Full team data is available for context and can be used to answer follow-up questions
- Script outputs JSON with
Examples
- List all teams:
/teams:list-teams
Arguments
None
Prerequisites
- Python 3.6 or later
Notes
- Team names are case-sensitive
- Returns only teams with OCPBUGS components
- Typical count: ~29 teams
- Reads from committed mapping file (no download needed)
Data Source
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.
- 9d ago First seen · 91 lines · 8 tokens per session scan A 34647c4ddb65
list-teams is a command published in the GitHub repository wangke19/gemini-ai-helpers (2 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 8 tokens to every session and 693 once invoked, about $0.0000 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 2026-09-03.
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session-list
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7a_stakeholder_comms
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convert-to-plan
Convert planning artifacts (lite-plan, workflow session, markdown) to issue solutions.
execute
Execute queue with DAG-based parallel orchestration (one commit per solution).
queue
Form execution queue from bound solutions using issue-queue-agent (solution-level).