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/brain-bootstrap/claude-code-brain-bootstrapWrote 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/brain-bootstrap/claude-code-brain-bootstrap/squad-plan)<a href="https://agentmods.dev/commands/brain-bootstrap/claude-code-brain-bootstrap/squad-plan"><img src="https://agentmods.dev/badge/commands/brain-bootstrap/claude-code-brain-bootstrap/squad-plan/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/brain-bootstrap/claude-code-brain-bootstrap/squad-plan"><img src="https://agentmods.dev/badge/commands/brain-bootstrap/claude-code-brain-bootstrap/squad-plan.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 | $0.00013 | $0.00735 |
| Opus 5.5 | $0.00005 | $0.00294 |
| Sonnet 5.5 | $0.00003 | $0.00147 |
| Haiku 4.5 | $0.00001 | $0.00073 |
Grade A, and why
squad-plan 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 1mo 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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate a detailed Claude Squad parallel execution plan for: $ARGUMENTS
ultrathink — use extended reasoning for workstream decomposition and dependency analysis.
Context
Read CLAUDE.md for project architecture, conventions, and critical patterns.
Read claude/architecture.md for the workspace layout and service catalog.
Instructions
Phase 1: Analyze the Task
- Break down $ARGUMENTS into independent subtasks
- Identify natural parallelism boundaries (frontend/backend, services, features, layers)
- Map dependencies between subtasks — what must complete before something else can start
- Identify shared resources that need coordination (DB schemas, API contracts, shared types)
Phase 2: Design Workstreams
Create 2-5 distinct workstreams, each assignable to a separate Claude Code instance:
For each workstream:
- Workstream ID & Title — e.g., "WS1: API Layer"
- Assigned Role — e.g., "Backend API Developer"
- Objective — what this instance accomplishes
- Files/Components — the specific parts of the codebase this workstream owns
- Tasks — numbered checklist items with:
- Description + specific instructions
- Follow the Explore → Plan → Act TDD workflow for each coding task
- Expected outcome
- Verification steps
- Dependencies — which tasks from other workstreams must complete first
- Deliverables — what this workstream produces for other workstreams to consume
Phase 3: Integration Strategy
- Define integration points between workstreams
- Create integration test checklist
- Specify merge order (which branch merges first)
- Define smoke test for the combined result
Phase 4: Write ACTION_PLAN.md
Save the plan to claude/tasks/ACTION_PLAN.md with this structure:
# ACTION_PLAN — [Feature Name]
## Overall Objective
[Clear statement of the goal]
## Project Context
[Brief summary — refer to CLAUDE.md for details]
## Workstream Definitions
### WS1: [Title]
**Role:** [Role Name]
**Objective:** [Goal]
**Files:** [List]
#### Tasks
- [ ] Task 1: [Description] — *Explore → Plan → Act*
- [ ] Task 2: ...
**Dependencies:** None (can start immediately)
**Delivers to:** WS2 needs [output] from Task 3
### WS2: [Title]
...
## Integration Points
- [ ] [Integration task 1]
- [ ] [Integration task 2]
## Testing Strategy
- [ ] Unit tests per workstream
- [ ] Integration tests after merge
- [ ] End-to-end smoke test
## Coordination Notes
- Each instance should check off tasks as they complete
- Signal completion by updating this file
- All instances must follow `CLAUDE.md` standards
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.
- 1mo ago First seen · 105 lines · 13 tokens per session scan A b902b23fac10
squad-plan is a command published in the GitHub repository brain-bootstrap/claude-code-brain-bootstrap (11 stars, last pushed 5mo ago), licensed MIT. It adds 13 tokens to every session and 735 once invoked, about $0.0001 per session on Opus 5.5. 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
restart
Restart the Claude Mnemonic worker process.
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.
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.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.