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 commands/jeffh/claude-plugins/iterate_plangit clone --depth 1 https://github.com/jeffh/claude-pluginsWhat 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 | $0.00011 | $0.01837 |
| Opus 5 | $0.00005 | $0.00919 |
| Sonnet 5 | $0.00002 | $0.00367 |
| Haiku 4.5 | $0.00001 | $0.00184 |
Grade A, and why
iterate_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 3d 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.
This is a copy
91% identical to iterate_plan — 32 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Iterate Implementation Plan
You are tasked with updating existing implementation plans based on user feedback. You should be skeptical, thorough, and ensure changes are grounded in actual codebase reality.
Initial Response
When this command is invoked:
-
Parse the input to identify:
- Plan file path (e.g.,
thoughts/shared/plans/2025-10-16-feature.md) - Requested changes/feedback
- Plan file path (e.g.,
-
Handle different input scenarios:
If NO plan file provided:
I'll help you iterate on an existing implementation plan. Which plan would you like to update? Please provide the path to the plan file (e.g., `thoughts/shared/plans/2025-10-16-feature.md`). Tip: You can list recent plans with `ls -lt thoughts/shared/plans/ | head`Wait for user input, then re-check for feedback.
If plan file provided but NO feedback:
I've found the plan at [path]. What changes would you like to make? For example: - "Add a phase for migration handling" - "Update the success criteria to include performance tests" - "Adjust the scope to exclude feature X" - "Split Phase 2 into two separate phases"Wait for user input.
If BOTH plan file AND feedback provided:
- Proceed immediately to Step 1
- No preliminary questions needed
Process Steps
Step 1: Read and Understand Current Plan
-
Read the existing plan file COMPLETELY:
- Use the Read tool WITHOUT limit/offset parameters
- Understand the current structure, phases, and scope
- Note the success criteria and implementation approach
-
Understand the requested changes:
- Parse what the user wants to add/modify/remove
- Identify if changes require codebase research
- Determine scope of the update
Step 2: Research If Needed
Only spawn research tasks if the changes require new technical understanding.
If the user's feedback requires understanding new code patterns or validating assumptions:
- Create a research todo list using TodoWrite
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.
- 3d ago First seen · 246 lines · 11 tokens per session scan A 80af308617ad
iterate_plan is a command published in the GitHub repository jeffh/claude-plugins (12 stars, last pushed 19d ago), licensed Apache-2.0. It adds 11 tokens to every session and 1,837 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to iterate_plan, differing in 32 lines, and is treated as a copy.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.