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/claude-code-community-ireland/claude-code-resources/plangit clone --depth 1 https://github.com/Claude-Code-Community-Ireland/claude-code-resourcesWrote 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/claude-code-community-ireland/claude-code-resources/plan)<a href="https://agentmods.dev/commands/claude-code-community-ireland/claude-code-resources/plan"><img src="https://agentmods.dev/badge/commands/claude-code-community-ireland/claude-code-resources/plan.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 | $0.00013 | $0.00324 |
| Opus 5 | $0.00006 | $0.00162 |
| Sonnet 5 | $0.00003 | $0.00065 |
| Haiku 4.5 | $0.00001 | $0.00032 |
Grade A, and why
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.
What it actually says
Plan Workflow
You are creating a structured implementation plan for a feature or task.
Steps
-
Understand the request: Read the feature description from
$ARGUMENTS. If it's ambiguous, ask clarifying questions about scope, constraints, and expected behavior. -
Explore the codebase: Use the Task tool with the
Exploresubagent to understand:- Project structure and framework
- Existing patterns and conventions
- Related components that will be affected
- Current test infrastructure
-
Launch the architect: Use the Task tool to spawn the
architectagent with:Design an implementation plan for: Feature: $ARGUMENTS Codebase context: [summary from exploration]
Follow the full architecture process: understand the landscape, define requirements, propose 2-3 design options with trade-offs, recommend one approach, and provide a detailed implementation blueprint with specific files to create/modify, component responsibilities, data flow, and build sequence.
-
Create a task breakdown: Convert the blueprint into a numbered checklist of implementation steps, ordered by dependency (build foundations first).
-
Present the plan: Show the user:
- Recommended approach with rationale
- Key files to create or modify
- Ordered implementation steps
- Any risks or open questions
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 · 36 lines · 13 tokens per session scan A c50f984ccfda
plan is a command published in the GitHub repository Claude-Code-Community-Ireland/claude-code-resources (10 stars, last pushed 3mo ago), licensed MIT. It adds 13 tokens to every session and 324 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 2026-08-31.
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.