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/orangeproai/orangepro-mcp/claude-codegit clone --depth 1 https://github.com/OrangeproAI/orangepro-mcpWhat 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 | $0.00000 | $0.00467 |
| Opus 5 | $0.00000 | $0.00234 |
| Sonnet 5 | $0.00000 | $0.00093 |
| Haiku 4.5 | $0.00000 | $0.00047 |
Grade A, and why
claude-code 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.
How it starts
The opening of the file, as written. The whole thing — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OrangePro With Claude Code
Install
npm install -g @orangepro/orangepro-mcp
cd /path/to/your/repo
opro
opro prepares the behavior report, RTM, and agent next actions. If your shell has a model key, weak AI grounding and AI-suggested candidate flows run automatically. AI lanes are suggestions only; Proven remains dynamic targeted proof only.
Claude Plugin
The public, supported path today is MCP setup through opro agent --client claude-code below. The bundled plugin metadata is for marketplace submission and maintainer validation; use marketplace install commands only after OrangePro is listed in your Claude Code plugin marketplace.
When installed through a marketplace, the plugin starts the same orangepro-local MCP server and exposes the /orangepro:opro skill. It does not pin a model; OrangePro uses provider/model values from the environment, .env.provider.local, .env.local, .env, or opro setup.
MCP Setup
Print the Claude Code config:
opro agent --client claude-code
Paste the printed mcpServers.orangepro-local block into the project .mcp.json or your Claude Code MCP config. If Claude Code does not inherit shell variables, add the provider key to that local config, or keep it in a repo-local .env.provider.local file that is not committed.
The printed config intentionally does not pin a model. OrangePro uses the provider/model configured in the process environment, .env.provider.local, .env.local, .env, or opro setup.
If your Claude Code setup supports custom slash commands, map /opro to: call orangepro_start for the current checkout, then follow the returned next_actions. The command should call the MCP tool; it should not run a separate source-writing script.
Agent Prompt
Use OrangePro first. Call orangepro_start, then use orangepro_generate_tests for the returned PR or gap target. Write each runnable test to suggested_path, run run_command, and call `orangepro_prove` with the returned `prove_run` args for Dynamically Proven. Use record_run only for static diagnostics. Do not treat drafts as runnable tests.
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 · 38 lines · 0 tokens per session scan A 9a348ee1eb79
claude-code is an agent published in the GitHub repository OrangeproAI/orangepro-mcp (17 stars, last pushed 6d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 467 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 2026-08-30.
Other agents, from other repositories
ci-medic
Runs the ci-settle loop (formula convergence, step X3) — watches CI checks, triages bot comments, fixes real findings or declines with a stated reason, regenerates generated artifacts. No merge authority.
docs-auditor
Weekly standing patrol for docs drift vs code, broken links, index consistency, and i18n lag reporting (which locales are behind English and by how much). Patrols for progressive-disclosure violations doc-writer may have missed.
prs-expert
PromptScript language expert. Helps with syntax, compilation issues, and migrations.
debugger
Debugs errors, test failures, and unexpected behavior. Knows PromptScript architecture.
speckit.analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
speckit.implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.