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 rules/rethunk-ai/clodbridge/manage-scope-iterativelygit clone --depth 1 https://github.com/Rethunk-AI/clodbridgeWhat 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 | $0.00270 | $0.00270 |
| Opus 5 | $0.00135 | $0.00135 |
| Sonnet 5 | $0.00054 | $0.00054 |
| Haiku 4.5 | $0.00027 | $0.00027 |
Grade A, and why
manage-scope-iteratively 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
Manage Scope Iteratively
Deliver incrementally. Check in with the user after each commit.
Increment = One Commit
After completing a commit-sized unit of work:
- Commit the code
- Check in: "X is done. Should I proceed with Y?"
- Wait for user feedback
- Continue based on feedback
When to Check In
After:
- A new type definition + tests pass
- A parsing function + tests pass
- A major subsystem completes (server, tools, resources)
- You're about to start something big (> 200 lines)
- A decision point arises (should I implement X or Y?)
Example
✅ "Types and interfaces done. Next: parsing logic.
Should I proceed?"
✅ "Parsing complete + tests pass. Next: discovery modules.
Any feedback before I continue?"
✅ "Discovered design question: MCP resources (raw files, JSON index,
or both)? What's your preference?"
Don't Do This
❌ Implement everything, commit it all, then ask "What do you think?"
For checkpoint patterns and detailed examples, see the manage-scope-iteratively skill.
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 · 48 lines · 270 tokens per session scan A c4cafa4f80d7
manage-scope-iteratively is a cursor rule published in the GitHub repository Rethunk-AI/clodbridge (0 stars, last pushed 1mo ago), licensed MIT. It adds 270 tokens to every session, about $0.0014 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.
Other cursor rules, from other repositories
commitlint
Commitlint rules for conventional commit messages.
git-conventions
Git workflow and commit conventions for AI-assisted development.
git-authoring
Conventional Commit, pull-request, release-note, and PR-review conventions for this repository.
no-tool-contributors
Never add AI coding tools as contributors or co-authors.
savee
Use the Savee MCP tools when the task involves design inspiration, visual references, moodboards, or the user's own saved work.
git
Cursor rule "git" from duongductrong/cursor-kit, covering git conventions, commit messages, types, subject rules and examples.