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 skills add billbuchanan-code/claude-code-power-setup --skill compactgit clone --depth 1 https://github.com/billbuchanan-code/claude-code-power-setupWrote 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/skills/billbuchanan-code/claude-code-power-setup/compact)<a href="https://agentmods.dev/skills/billbuchanan-code/claude-code-power-setup/compact"><img src="https://agentmods.dev/badge/skills/billbuchanan-code/claude-code-power-setup/compact/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/skills/billbuchanan-code/claude-code-power-setup/compact"><img src="https://agentmods.dev/badge/skills/billbuchanan-code/claude-code-power-setup/compact.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 | $0.00854 |
| Opus 5.5 | $0.00005 | $0.00342 |
| Sonnet 5.5 | $0.00003 | $0.00171 |
| Haiku 4.5 | $0.00001 | $0.00085 |
Grade A, and why
compact 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Smart Compact Instruction Generator
Analyze the current session to generate a tailored /compact instruction that preserves important context and discards noise.
Process
Step 1: Infer Session Contents
You do not have direct access to the conversation history. Instead, infer what happened in the session from available signals:
-
Check git state: Use Glob and Grep to look at:
- Files recently modified (check modification times via
ls -ltpatterns or git status) - Any HANDOFF.md or TODO files that describe session work
.claude/directory for any session artifacts
- Files recently modified (check modification times via
-
Detect agent delegation patterns: Look for signs that sub-agents were used:
- Multiple files explored in a short time (breadth-first patterns)
- Search result files or temporary analysis files
- Changes across many unrelated directories (suggests parallel agent work)
-
Detect MCP server usage: Check for:
.mcp.jsonormcp_config.jsonfiles in the project- References to external services in recently changed files
- Configuration files for Slack, GitHub, databases, etc.
-
Identify key decisions: Look for:
- New dependencies added (package.json, Cargo.toml, requirements.txt, go.mod changes)
- New files created (architectural decisions about structure)
- Configuration file changes (tooling/infrastructure decisions)
- Pattern choices visible in code (e.g., choosing a specific design pattern)
-
Identify debugging noise: Look for signs of troubleshooting:
- Files with many recent modifications (iterative debugging)
- Test files that were changed multiple times
- Log or output files
- Temporary files or scratch work
Step 2: Categorize Context
Sort everything into two categories:
Preserve (high-value context that is expensive to reconstruct):
- Architecture and design decisions made
- File paths that were created or significantly modified
- Agent delegation results (what was found, what was decided)
- MCP connection states and which servers are active
- User preferences or constraints stated during the session
- Working solutions that were arrived at
- Branch name and what it represents
- Key relationships between files discovered during exploration
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 · 104 lines · 13 tokens per session scan A 4bce84ec3a7b
compact is a skill published in the GitHub repository billbuchanan-code/claude-code-power-setup (2 stars, last pushed 2mo ago), licensed MIT. It adds 13 tokens to every session and 854 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 2026-08-31.
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