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 skills/billbuchanan-code/claude-code-power-setup/multi-plannpx skills add billbuchanan-code/claude-code-power-setup --skill multi-plangit clone --depth 1 https://github.com/billbuchanan-code/claude-code-power-setupWhat 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 | $0.00096 | $0.03217 |
| Opus 5 | $0.00048 | $0.01608 |
| Sonnet 5 | $0.00019 | $0.00643 |
| Haiku 4.5 | $0.00010 | $0.00322 |
Grade A, and why
multi-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 2d 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 — 458 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi-Agent Orchestration: Unified Implementation Planning
You are an orchestration agent. Given a feature description, you spawn parallel specialist agents to analyze the feature from multiple perspectives, then synthesize their outputs into a single, comprehensive implementation plan.
Feature Description
$ARGUMENTS
Core Protocol
- Language: Use English in all tool calls and agent prompts. Communicate with the user in their language.
- Read-Only Analysis: This skill produces a PLAN. It does NOT modify production code.
- Parallel Execution: Independent agent analyses MUST run in parallel using
run_in_background: true. - Code Sovereignty: Only the orchestrator (you) writes output files. Sub-agents analyze and report.
- Stop-Loss: Do not proceed to synthesis until all agent outputs are collected and validated.
Execution Workflow
Phase 1: Context Gathering
Before spawning agents, gather the project context they will need.
1.1 Project Discovery
# Identify project structure
ls -la
find . -maxdepth 2 -type f -name "*.md" -o -name "package.json" -o -name "pyproject.toml" -o -name "go.mod" -o -name "pom.xml" -o -name "Cargo.toml" 2>/dev/null | head -30
# Read project configuration
cat CLAUDE.md 2>/dev/null || cat README.md 2>/dev/null | head -100
# Identify tech stack
cat package.json 2>/dev/null | head -40
cat pyproject.toml 2>/dev/null | head -40
1.2 Relevant Code Discovery
Using the feature description from $ARGUMENTS, search for related code:
# Search for files related to the feature domain
# (adapt search terms based on the feature description)
grep -rn "relevant_term" --include="*.ts" --include="*.py" --include="*.go" --include="*.java" -l . | head -20
# Find existing tests in the area
find . -type f \( -name "*.test.*" -o -name "*.spec.*" -o -name "*_test.*" \) | head -20
# Find database schemas/migrations
find . -type f \( -name "*.sql" -o -name "schema.*" -o -name "*.entity.*" -o -name "*.model.*" \) | head -20
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.
- 2d ago First seen · 458 lines · 96 tokens per session scan A 3d78d6dd6da6
multi-plan is a skill published in the GitHub repository billbuchanan-code/claude-code-power-setup (2 stars, last pushed 1mo ago), licensed MIT. It adds 96 tokens to every session and 3,217 once invoked, about $0.0005 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.
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chat-perf
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