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.
git clone --depth 1 https://github.com/ChrisMckerracher/claude-dream-teamWrote 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/chrismckerracher/claude-dream-team/bug)<a href="https://agentmods.dev/commands/chrismckerracher/claude-dream-team/bug"><img src="https://agentmods.dev/badge/commands/chrismckerracher/claude-dream-team/bug/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/chrismckerracher/claude-dream-team/bug"><img src="https://agentmods.dev/badge/commands/chrismckerracher/claude-dream-team/bug.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 | $0.00024 | $0.00789 |
| Opus 5 | $0.00012 | $0.00394 |
| Sonnet 5 | $0.00005 | $0.00158 |
| Haiku 4.5 | $0.00002 | $0.00079 |
Grade A, and why
bug 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bug Discovery Workflow
You are starting a Bug Discovery workflow with the Dream Team. Follow these steps precisely.
Step 1: Understand the Bug
Read the user's bug report carefully. Gather key information:
- What is the expected behavior?
- What is the actual behavior?
- Steps to reproduce (if known)
- Environment details (if relevant)
- When did it start happening? (if known)
- Error messages or logs (if available)
If the report is incomplete, ask clarifying questions using AskUserQuestion.
Step 2: Theorize Investigation Leads
Based on the bug report, develop 2-4 investigation leads. Each lead is a theory about what might be causing the bug.
Example leads:
- "Lead 1: The database query is returning stale cached data"
- "Lead 2: The API validation is rejecting valid input due to a regex bug"
- "Lead 3: A race condition between the auth middleware and the request handler"
Present the leads to the user if time permits, or proceed with investigation directly.
Step 3: Spawn Investigators
For each lead, spawn an appropriate agent:
- Coding Agent (
dream-team:coding): For leads requiring code analysis, tracing execution paths, or understanding data flow - QA Agent (
dream-team:qa): For leads requiring reproduction, testing specific conditions, or validating behavior against specs
Create a team using TeamCreate:
- Team name:
bug-{short-slug} - Description: Brief description of the bug
Provide each investigator with:
- The full bug report
- Their specific investigation lead
- Instructions to use spelunk mode for code exploration
- Instructions to challenge other investigators' findings
Step 4: Facilitate Investigation
Monitor the investigators as they work:
- Let them explore and theorize
- Encourage them to message each other with findings
- If one investigator finds strong evidence, direct others to validate
- If investigators are going in circles, redirect them
Step 5: Build Consensus
Once investigators have findings:
- Review each investigator's theory and evidence
- Look for convergence - do multiple leads point to the same root cause?
- If consensus: proceed to Step 6
- If stuck: proceed to Step 5b
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 · 108 lines · 24 tokens per session scan A 5f14a66e3641
bug is a command published in the GitHub repository ChrisMckerracher/claude-dream-team (5 stars, last pushed 6mo ago), licensed MIT. It adds 24 tokens to every session and 789 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
qa-changes
This skill should be used when the user asks to "QA a pull request", "test PR changes", "verify a PR works", "functionally test changes", or when an automated workflow triggers QA validation of code changes. Provides a structured methodology for setting up the environment, exercising changed behavior, and reporting…
doctor
Diagnosticar y reparar problemas del framework Don Cheli, git y entorno. Usa cuando el usuario dice "doctor", "problemas del framework", "don cheli no funciona", "repair Don Cheli", "debug setup", "setup broken", "framework broken", "reparar entorno". Detecta y repara issues de configuración, git y dependencias…
fix
Universal debugging and fix application with semantic code analysis.
doctor
Badi configuration validation. Checks all Badi components and produces a diagnostic report.
http-service
Build, review or debug a Bun HTTP service. Loads the http-service skill, then works the task through its workflow.
gh-issue-use-cypress
Like /gh-issue-use-browser, but pinned to the Cypress MCP — use when your project runs the Cypress MCP for browser automation. Example — /gh-issue-use-cypress "Composer > Save" saving toasts failure but the record persists.