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/dallasgoldswain/claude-code-agents-managerWrote 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/dallasgoldswain/claude-code-agents-manager/plan-gh)<a href="https://agentmods.dev/commands/dallasgoldswain/claude-code-agents-manager/plan-gh"><img src="https://agentmods.dev/badge/commands/dallasgoldswain/claude-code-agents-manager/plan-gh.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00243 |
| Opus 5 | $0.00000 | $0.00121 |
| Sonnet 5 | $0.00000 | $0.00049 |
| Haiku 4.5 | $0.00000 | $0.00024 |
Grade A, and why
plan-gh 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 7d 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.
What it actually says
Draft a detailed, step-by-step blueprint for building this project. Then, once you have a solid plan, break it down into small, iterative chunks that build on each other. Look at these chunks and then go another round to break it into small steps. review the results and make sure that the steps are small enough to be implemented safely, but big enough to move the project forward. Iterate until you feel that the steps are right sized for this project.
From here you should have the foundation to provide a series of prompts for a code-generation LLM that will implement each step. Prioritize best practices, and incremental progress, ensuring no big jumps in complexity at any stage. Make sure that each prompt builds on the previous prompts, and ends with wiring things together. There should be no hanging or orphaned code that isn't integrated into a previous step.
Make sure and separate each prompt section. Use markdown. Each prompt should be tagged as text using code tags. The goal is to output prompts, but context, etc is important as well. For each step, create a github issue.
Store the plan in plan.md. Also create a todo.md to keep state.
The spec is in the file called:
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.
- 7d ago First seen · 10 lines · 0 tokens per session scan A b98bf87dc2c2
plan-gh is a command published in the GitHub repository dallasgoldswain/claude-code-agents-manager (2 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 243 tokens. 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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