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/wshobson/agents/team-featuregit clone --depth 1 https://github.com/wshobson/agentsWhat 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 | $0.00014 | $0.00873 |
| Opus 5 | $0.00007 | $0.00436 |
| Sonnet 5 | $0.00003 | $0.00175 |
| Haiku 4.5 | $0.00001 | $0.00087 |
Grade A, and why
team-feature 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Team Feature
Orchestrate parallel feature development with multiple implementer agents. Decomposes features into work streams with strict file ownership, manages dependencies, and verifies integration.
Pre-flight Checks
- Verify
CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1is set - Parse
$ARGUMENTS:<feature-description>: description of the feature to build--team-size N: number of implementers (default: 2)--branch: git branch name (default: auto-generated from feature description)--plan-first: decompose and get user approval before spawning
Phase 1: Analysis
- Analyze the feature description to understand scope
- Explore the codebase to identify:
- Files that will need modification
- Existing patterns and conventions to follow
- Integration points with existing code
- Test files that need updates
Phase 2: Decomposition
-
Decompose the feature into work streams:
- Each stream gets exclusive file ownership (no overlapping files)
- Define interface contracts between streams
- Identify dependencies between streams (blockedBy/blocks)
- Balance workload across streams
-
If
--plan-firstis set:-
Present the decomposition to the user:
## Feature Decomposition: {feature} ### Stream 1: {name} Owner: implementer-1 Files: {list} Dependencies: none ### Stream 2: {name} Owner: implementer-2 Files: {list} Dependencies: blocked by Stream 1 (needs interface from {file}) ### Integration Contract {shared types/interfaces} -
Wait for user approval before proceeding
-
If user requests changes, adjust decomposition
-
Phase 3: Team Spawn
- If
--branchspecified, use Bash to create and checkout the branch:git checkout -b {branch-name} - Use
TeamCreatetool to create the team withteam_name: "feature-{timestamp}"anddescription - Spawn a
team-leadagent to coordinate - For each work stream, use
Agenttool to spawn ateam-implementer:name:implementer-{n}subagent_type: "agent-teams:team-implementer"prompt: Include owned files, interface contracts, and implementation requirements
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 · 115 lines · 14 tokens per session scan A be9dd1328f6c
team-feature is a command published in the GitHub repository wshobson/agents (39,318 stars, last pushed 3d ago), licensed MIT. It adds 14 tokens to every session and 873 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 2026-08-30.
Other commands, from other repositories
update-changelog-and-tag
You are preparing a release. Follow these steps precisely.
test-feature
Test a React Native feature on the running simulator/emulator. Verifies UI, user flows, and internal state. Generates a persistent Maestro test file.
implement_plan
You are tasked with implementing an approved technical plan from thoughts/shared/plans/. These plans contain phases with specific changes and success criteria.
review-plan
Review an implementation plan for simplification opportunities, gaps, bugs, and better approaches.
rmslop
Remove AI code slop from the current branch vs default branch.
quick-prd
SAM Quick PRD Workflow - Quill drafts a valid PRD in one pass, making explicit assumptions where the user is silent.