A command that runs a multi-stage workflow for researching, checking, implementing, and documenting a change, with model selection for each stage.

Use it to plan a change, research the relevant information, verify findings, implement the code, and update documentation.

It organizes work that would otherwise require you to coordinate investigation, validation, coding, and documentation manually.

How grandinh/mcp-prompt-optimizer configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to grandinh/mcp-prompt-optimizer. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/grandinh/mcp-prompt-optimizer/main/.claude/commands/ori.md

Clone the repo

git clone --depth 1 https://github.com/grandinh/mcp-prompt-optimizer

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/grandinh/mcp-prompt-optimizer/ori/github.svg)](https://agentmods.dev/commands/grandinh/mcp-prompt-optimizer/ori)

Your own site

<a href="https://agentmods.dev/commands/grandinh/mcp-prompt-optimizer/ori"><img src="https://agentmods.dev/badge/commands/grandinh/mcp-prompt-optimizer/ori/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/commands/grandinh/mcp-prompt-optimizer/ori"><img src="https://agentmods.dev/badge/commands/grandinh/mcp-prompt-optimizer/ori.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 4,457 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.04457
Opus 5.5	$0.00000	$0.01783
Sonnet 5.5	$0.00000	$0.00891
Haiku 4.5	$0.00000	$0.00446

Measured 2mo ago against content hash 05ad13386713, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ori 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 2mo 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.

.claude/commands/ori.md · 627 lines

How it starts

The opening of the file, as written. The whole thing — 627 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Optimize Research Implement (ORI) Workflow

Version: 1.1 Purpose: Autonomous multi-phase workflow with intelligent model selection for researching, validating, and implementing changes with minimal user input.

Workflow Overview

Execute the following phases sequentially with built-in error handling, validation, and intelligent model selection:

PHASE 0: STRATEGY (Opus) → PHASE 1: RESEARCH (Dynamic) → PHASE 2: VERIFY (Sonnet) → PHASE 3: IMPLEMENT (Sonnet/Haiku) → PHASE 4: DOCUMENT (Haiku)

Model Selection Strategy

Per-Phase Model Recommendations

The workflow uses different models optimized for each phase:

Phase	Recommended Model	Rationale
Phase 0: Strategy	Opus	Complex reasoning, strategic planning, research design
Phase 1: Research	Dynamic	Opus decides based on complexity; Sonnet for standard, Opus for complex
Phase 2: Verify	Sonnet	Balance of speed and accuracy for validation
Phase 3: Implement	Sonnet/Haiku	Sonnet for complex code, Haiku for simple edits
Phase 4: Document	Haiku	Fast, cost-effective for doc updates

When to Use Each Model

Opus (claude-opus-4):

Strategic planning and research design
Complex multi-step reasoning
Novel or ambiguous problems
High-stakes decisions requiring deep analysis
Architectural decisions

Sonnet (claude-sonnet-4-5):

Most implementation tasks
Code generation and refactoring
Validation and verification
Balanced performance/cost for general tasks

Haiku (claude-haiku-4):

Simple file edits
Documentation updates
Formatting and style fixes
Quick, straightforward tasks

Phase 0: Research Strategy (STRATEGIC PLANNING)

Objective

Use Opus to create an optimal research strategy and select the best model for execution.

Model: Opus (claude-opus-4)

Instructions

IMPORTANT: This phase MUST use Opus via the Task tool:

Read the full file on GitHub · 627 lines

Changes

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.

2mo ago First seen · 627 lines · 0 tokens per session scan A 05ad13386713

Subscribe to this mod's changes

ori is a command published in the GitHub repository grandinh/mcp-prompt-optimizer (0 stars, last pushed 12mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,457 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.

Planning

ori next to 6 commands from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
origrandinh/mcp-prompt-optimizer	Command	0	12mo ago	MIT	A	0	Claude Code
checklistgithub/spec-kit	Command	148k	today	MIT	A	13	Claude Code
clarifygithub/spec-kit	Command	148k	today	MIT	A	27	Claude Code
specifygithub/spec-kit	Command	148k	today	MIT	A	13	Claude Code
analyzegithub/spec-kit	Command	148k	today	MIT	A	26	Claude Code
convergegithub/spec-kit	Command	148k	today	MIT	A	35	Claude Code
implementgithub/spec-kit	Command	148k	today	MIT	A	14	Claude Code

mcp-prompt-optimizer: Command for Claude Code