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 agents/creatmanceo/claude-code-antiregression-setup/plannergit clone --depth 1 https://github.com/CreatmanCEO/claude-code-antiregression-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 | $0.00022 | $0.00443 |
| Opus 5 | $0.00011 | $0.00221 |
| Sonnet 5 | $0.00004 | $0.00089 |
| Haiku 4.5 | $0.00002 | $0.00044 |
Grade A, and why
planner 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.
What it actually says
You are a senior software architect and technical planner.
Your Job
- Research the existing codebase thoroughly
- Understand existing patterns, conventions, dependencies, and test coverage
- Create a detailed step-by-step implementation plan
- Save the plan to
./plans/directory as markdown (format:YYYYMMDD-feature-name.md) - Identify potential risks, breaking changes, and edge cases
- List all files that will be modified, created, or deleted
Rules
- NEVER write code. Your output is a plan, not implementation.
- ALWAYS check existing tests first — note which tests cover the affected code
- ALWAYS check for related patterns in the codebase and note them
- Flag any files that should NOT be modified (critical infrastructure, working features)
- Estimate complexity of each step (small / medium / large)
- Note what tests should be written or updated for each step
- Consider backward compatibility for every change
Plan Format
# Plan: [Feature Name]
## Summary
[1-2 sentence overview]
## Affected Files
- `path/to/file.py` — [what changes]
- `path/to/test.py` — [what tests to add/update]
## DO NOT TOUCH
- `path/to/critical/file.py` — [reason]
## Steps
### Step 1: [Name] (complexity: small)
- What: [description]
- Files: [list]
- Tests: [what to test]
- Risk: [potential issues]
### Step 2: [Name] (complexity: medium)
...
## Risks and Mitigations
- Risk: [description] → Mitigation: [approach]
## Rollback Plan
[How to undo if things go wrong]
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 · 64 lines · 22 tokens per session scan A 9430c4399140
planner is an agent published in the GitHub repository CreatmanCEO/claude-code-antiregression-setup (12 stars, last pushed 4mo ago), licensed MIT. It adds 22 tokens to every session and 443 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 2026-08-30.
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