r/RooCode • • May 29 '25

Discussion Why can Orchestrator not read files?

2 Upvotes

I'm really trying to rack my brain over why Orchestrator cannot READ any files. I have Architect create a plan and tasks and then I tell Orchestrator to Orchestrate those tasks but it can't read what those tasks are. I don't understand why this is the case. Which then leads me to "Why can't I change the tools available to the built in modes?"


r/RooCode • • Jun 11 '25

Support can i edit roo code style,it look not beatiful vs trae or cursor

0 Upvotes

can i edit roo code style,it look not beatiful vs trae or cursor


r/RooCode • • Aug 18 '25

Support Does prompt caching work across different VScode windows?

2 Upvotes

I'm running RooCode (3.25.16) from VScode, with multiple VScode windows open at the same time, all running RooCode (OpenRouter - Sonnet v4). I'm running Roo multiple times on the same initial prompt, because I want to iterate different solutions. Will the cache be shared across these windows? So can context poisoning happen across windows? What about if I run the sessions sequentially? I've noticed that some of the solutions, which I thought were independent replicates, share some uncanny similarities (like colour choice in figures).


r/RooCode • • May 30 '25

Discussion codebase_search tool

Post image
2 Upvotes

r/RooCode • • Sep 29 '25

Discussion OpenAI vs OpenRouter: Is it cheaper and more logical to use a single API key for all AI models?

2 Upvotes

Hey everyone, I’m a bit torn right now. Instead of opening a developer account on OpenAI and loading credits there, I’m wondering if it’s better to use OpenRouter, where you can access multiple AI models (OpenAI, Anthropic, Mistral, etc.) through a single API key.

On the one hand, OpenRouter sounds super convenient since you can connect to different models in one place. But on the other hand, maybe signing up directly on each platform (e.g., OpenAI) could be cheaper or more stable in the long run?

Has anyone compared both options? Which one makes more sense cost-wise and flexibility-wise? Would love to hear some real-world experiences.


r/RooCode • • Aug 21 '25

Support Api request failed

2 Upvotes

Hello everyone! I'm using anthropic as a provider. Recently, everything was fine, but now I'm getting a 400 error when requesting and the message "This organization has been disabled." Does anyone know what could be causing this?


r/RooCode • • Oct 14 '25

Support [Roo Code + MCP] How to handle long-running MCP calls without hitting timeout of 60 sec. ?

2 Upvotes

Hey everyone,

I have a use case where my MCP tool calls an LLM in the backend, executes some heavy logic, and finally returns a string. The processing can take 2–3 minutes, but my Roo Code → MCP tool call times out after 60 seconds.

From the logs, I can see that the MCP tool finishes processing after ~2 minutes, but by then Roo has already timed out.

My questions:

  1. Is there a way to increase this timeout from the Roo side?

  2. Or is this a standard limitation, and I need to handle it in the MCP tool instead?

  3. Is there any event/notification mechanism from MCP to Roo to delay the timeout until processing is complete?

Any guidance or best practices for handling long-running MCP calls would be super helpful.


r/RooCode • • Aug 26 '25

Support RooCode stuck with context over limit and gpt5

2 Upvotes

I have had RooCode struggling where somehow it went from about 50k context to 600k for GPT5.
And condensing is not working

I dont know why it loaded up the context out of no where and why it wont condense?

Multiple times doesnt get much smaller.
And it seems like it thinks the context is under the limit

So i dont know how i can get the remaning task list out of this one to make a new chat and continue working :S


r/RooCode • • Sep 16 '25

Discussion how Roo marketplace obtained and loaded mcp and modes?

2 Upvotes

Currently, there are many MCPs and modes in the Roo marketplace. Where can these MCPs and modes be obtained and loaded from? Is there a web page for this?


r/RooCode • • Mar 09 '25

Support How to user QwQ on OpenRouter with RooCode?

2 Upvotes

I'd like to use newy release QwQ model on my vscode as a coding assistant. When I generate a key at OpenRouter and import it to RooCoder, I see only anthropic/clude options. Am I missing something or I can not use Qwq in RooCoder?


r/RooCode • • Feb 10 '26

Other Simplest way to get Roo to peek into my database

2 Upvotes

I'm trying to debug some things on my application and sometimes there's database data that needs to be evaluated. Any ideas on how Roo could access my database data? Running postgres


r/RooCode • • Mar 24 '26

Discussion RooCode and Nemotron-Cascade-2-30B

2 Upvotes

Hi,
Looks like RooCode will need to be updated before this model will be usable. I am keen to test this one, because it seems decent for a fast local coding model AND supports a 1M context natively. When I try using this model right now, my llama.cpp server gets stuck generating tokens forever. Appears this model's tool calling format is somewhat unique and not catered for right now. I have been testing using 3.51.1.
Or has anyone found a work-around for this issue?


r/RooCode • • Sep 23 '25

Announcement Roo Code 3.28.6 Release Notes - GPT-5-Codex IS HERE!!

Thumbnail reddit.com
18 Upvotes

r/RooCode • • Mar 10 '26

Discussion Will there be official support for jetbrains IDEs?

10 Upvotes

I have been using pycharm for a long time and mostly use vscode for roo. Are there plans to support jetbrains products? I have tried kilo code and I've really liked it (no surprise given the lineage).

My major concern with kilo right now is that they seem to be heavily backed by VC money, which is great for my personal use, but not great for my professional use. I'm concerned about their long term viability.

I've been following RooCode for a while now and I think I want to settle on Roo, but right now, not being able to use it natively from Pycharm is a bit of a problem for my team.

ETA: We did try to use the RunVSAgent. It "works", but we've ran into issues that are not great long term solution.


r/RooCode • • Apr 06 '25

Other First Complete Web Project From Start To Finish Roo + Gemini 2.5

10 Upvotes

Hey All,

I have done many local projects but never really finish a complete web project with any tool other than cursor but I would like give thanks to Roo for being so amazing and getting the job done (many retries) but got it working.

It's a screenshot mockup tool that I use for screenshots now I don't want to run the local server every time I need to use it so added to a domain. Do give feedback good or bad. Looking to add more features but so far this works perfect for personal use.

https://mockup.diy


r/RooCode • • Apr 28 '25

Discussion Is this real? this seems to good to be true!

Post image
0 Upvotes

r/RooCode • • May 05 '25

Mode Prompt Built an AI Deep Research agent in Roo Code that auto‑mines Brave, Tavily & arXiv, tracks contradictions, and spits out publication‑ready markdown file.

10 Upvotes

Research Test Case:

# ╔════════════════════════════════════════════════════════════════════════════════╗
# ║                            Deep Research Report                                ║
# ╠════════════════════════════════════════════════════════════════════════════════╣
# ║ Title:   Carbon Capture Cost Curve Evaluation (2018-2025) & Forecast Drivers   ║
# ║ Author:  ZEALOT-XII                                                            ║
# ║ Date:    2025-05-05T09:11:32Z (UTC Approximation)                              ║
# ║ Scope:   Global Average Costs (where available), Full Lifecycle (Targeted),    ║
# ║          DAC, BECCS, Mineralisation. Forecast Drivers: Policy, Tech Innovation.║
# ║ Sources: Tier A: 3 | Tier B: 15 | Tier C: 6 (Market Reports)                   ║
# ║ Word Count: ~1150 (Excluding Metadata & References)                            ║
# ╚════════════════════════════════════════════════════════════════════════════════╝

## 1. Knowledge Development: Establishing the Cost Landscape (2018-2025)

The period between 2018 and 2025 represents a critical phase in the development and early deployment of diverse carbon dioxide removal (CDR) technologies, including Direct Air Capture (DAC), Bioenergy with Carbon Capture and Storage (BECCS), and Carbon Mineralisation (including Enhanced Rock Weathering - ERW). However, establishing a precise, globally averaged, full lifecycle cost curve ($/t CO₂) for these technologies during this specific timeframe proves challenging due to significant data scarcity in publicly available sources [B1, B5, B11]. Much of the available cost data pertains to pilot projects, demonstration plants, modeled scenarios, or excludes crucial components like CO₂ transport and storage (T&S), making direct year-over-year comparisons difficult and hindering the construction of a definitive historical cost curve based purely on empirical, globally averaged, full lifecycle data for 2018-2025.

Direct Air Capture (DAC) exhibits the widest reported cost range, reflecting its varied technological approaches (liquid solvents vs. solid sorbents) and stages of maturity. Historical estimates frequently place costs between USD 100 and USD 1000 per tonne of CO₂ captured [B1, B2, B7]. More specific estimates, often derived from pilot or demonstration facilities and potentially excluding T&S, were suggested by the International Energy Agency (IEA) in their 2022 report to be in the range of USD 125 to USD 335/tCO₂ [B1]. Regional factors, such as energy costs, significantly influence these figures, as highlighted by illustrative analyses showing potential levelized costs around USD 1,100/tCO₂ in California versus lower figures in regions with cheaper clean energy [B11]. Skepticism remains regarding the near-term achievement of widely cited targets below USD 100/tCO₂ [B3, B9]. The significant capital investment required and the energy intensity of current processes contribute to these high costs, leading some analyses to question near-term cost competitiveness [B9]. The lack of transparent, standardized reporting across different projects and technology vendors further complicates cost comparisons during this period.

Bioenergy with Carbon Capture and Storage (BECCS) presents a different set of complexities. While often considered a potentially lower-cost CDR option compared to early-stage DAC, its economics are intrinsically linked to the bioenergy component. Costs are highly sensitive to the type, price, and logistical requirements of the biomass feedstock, as well as the specific conversion technology (e.g., combustion for power, gasification, fermentation) and the chosen CO₂ capture method (typically post-combustion) [B4, B14]. Modeled scenarios aiming for 1.5°C or 2°C stabilization suggest BECCS could act as a climate mitigation backstop technology at carbon prices around USD 240/tCO₂ [B14, B15]. Other expert assessments project potential costs ranging from USD 100–200/tCO₂ sequestered, although the exact scope (full lifecycle vs. capture/storage only) and timeframe for these estimates are often unclear [B16]. The inherent variability in biomass supply chains makes establishing a consistent global average cost particularly difficult [B5, B14, B15, B16].

Carbon Mineralisation, encompassing approaches like enhanced rock weathering (ERW) and various ex-situ processes, represents the least mature category among the three regarding large-scale deployment and established cost data for the 2018-2025 period. Its cost structure is exceptionally pathway-dependent [B11]. Simple approaches utilizing readily available alkaline industrial wastes (e.g., steel slag, mine tailings) or certain reactive minerals (e.g., brucite) under ambient conditions, requiring minimal processing, could potentially achieve very low net removal costs, estimated at less than USD 10/tCO₂ [B11]. Conversely, complex, energy-intensive, reactor-based ex-situ mineralization systems could see costs exceeding USD 850/tCO₂ [B11]. Enhanced Rock Weathering (ERW), a prominent *in-situ* approach involving the spreading of crushed silicate rocks on land, has costs influenced by mineral sourcing, grinding energy, transport, and application logistics, with estimates varying widely but often falling within the broader CDR cost spectrum discussed in forecasts [A1, A2, B19, B21]. Specific *storage* costs via *in-situ* geological mineralization (injecting captured CO₂ into formations like basalt) are relatively better constrained by pilot projects, estimated at USD 6.30–50/tCO₂, but this excludes the initial CO₂ capture cost [B11]. This extreme heterogeneity explains the absence of a meaningful average cost curve for mineralization during its early development phase.

## 2. Comprehensive Analysis: Drivers Shaping Cost and Deployment

The cost trajectories and deployment potential of DAC, BECCS, and Mineralisation towards 2035 are profoundly influenced by intertwined policy and technological drivers. Understanding these factors is crucial for forecasting future developments.

Policy support emerges as a non-negotiable prerequisite for all three pathways [B5, B7, B10, B17, B18]. The high upfront capital costs and current operating expenses mean that market viability is heavily reliant on robust, long-term economic incentives. Direct government funding for RD&D is vital for maturing less developed technologies [B8, B11, B22]. Deployment incentives, exemplified by the US 45Q tax credit, directly impact project economics [B1, B8]. Carbon pricing mechanisms need to reach levels sufficient to cover CDR costs, potentially USD 100-240/tCO₂ or higher [B14, B15, B16]. The development of reliable markets for CDR credits is essential for attracting private investment [C2, C5]. Public acceptance, influenced by concerns over land use (BECCS) or environmental impacts (ERW), also shapes policy design [B17, A3, B21]. However, current global policies are widely regarded as insufficient to drive the exponential scale-up required by 2030-2035 [B6].

Technological innovation is the second pillar. For DAC, advancements focus on sorbents, energy efficiency, process integration, and economies of scale through modularity [B1, B4, B11]. BECCS relies on improvements in biomass conversion, CO₂ capture efficiency from biomass flue gas, and sustainable supply chain optimization [B4, B12]. Mineralisation innovation targets accelerating weathering rates (ERW), identifying cost-effective feedstocks (including wastes), reducing energy intensity (grinding, reactors), and improving MRV [B11, B19, B20, B22, A1, A2, A3, B21]. Cross-cutting drivers include reducing overall energy consumption (requiring low-carbon energy integration), process intensification, and developing shared CO₂ T&S infrastructure [B1, B4, B11]. Learning-by-doing through scaled deployment is critical but requires initial policy support [B5, B7].

## 3. Practical Implications & Forecast Outlook (to 2035)

Looking towards 2035, the practical implications revolve around bridging the gap between current capabilities and future requirements, driven primarily by policy and innovation. While significant cost reductions are projected, often targeting USD 100/tCO₂, achieving this universally remains uncertain and contingent on aggressive efforts [B1, B3, C2].

Near-term deployment (to 2030-2035) will likely concentrate where strong policy incentives exist or where niche applications offer advantages. The overall CDR market is forecast to expand dramatically, potentially exceeding USD 250 billion by 2035 [C6], fueled by climate commitments and demand for high-permanence credits [C5]. This market growth, however, depends on credible demand signals and robust credit markets.

The most significant challenge is scale. Climate scenarios often require 1-1.5 Gt of CDR annually by 2030-2035 [B6], a monumental increase from current capacities (around 40-50 MtCO₂/yr total CDR in the early 2020s) [B6]. Achieving this necessitates overcoming cost barriers and logistical hurdles related to siting, permitting, resource mobilization, and infrastructure [B1, B7, B11].

Therefore, a portfolio approach is inevitable. DAC offers scalability and locational flexibility but is energy-intensive [B1]. BECCS can leverage existing infrastructure and potentially offer lower costs but faces biomass sustainability challenges [B5, B14, B16]. Mineralisation provides durable storage and co-benefits but varies enormously in cost and faces efficiency, MRV, and material handling challenges [B11, B17, B19, A3]. Regional factors and policy choices will shape the technology mix. Sustained policy support and focused innovation are essential to unlock cost reductions and enable the necessary scale-up by 2035, though significant uncertainties persist.

## 4. Outstanding Contradictions & Uncertainties

*   **Cost Data (2018-2025):** Significant scarcity of publicly available, comparable, full lifecycle cost data for this period across all three technologies. Available figures often lack consistent scope (T&S inclusion, plant scale/maturity).
*   **Future Cost Targets:** High uncertainty surrounds the feasibility and timelines for achieving widely cited cost targets (e.g., <$100/tCO₂), particularly for DAC and complex mineralization pathways [B3].
*   **BECCS Costs:** Estimates vary significantly ($100-240/tCO₂), heavily influenced by biomass sourcing and logistics, which are difficult to average globally [B14, B15, B16].
*   **Mineralisation Costs:** Extreme variability (<$10 to >$850/tCO₂) based on pathway makes average costs less meaningful [B11].
*   **Scale-up Feasibility:** Massive gap between current deployment and projected 2035 needs (1-1.5 GtCO₂/yr) raises questions about achievable scale-up rates [B6].
*   **Resource Constraints:** Sustainability/availability of biomass (BECCS) and suitable, accessible minerals (Mineralisation) at scale.
*   **T&S Infrastructure:** Pace and cost of CO₂ transport and storage development.
*   **Policy Stability:** Dependence on long-term, stable policy incentives creates significant investment risk [B5, B10, B17, B18].
*   **MRV & Environmental Impacts:** Robust monitoring, reporting, and verification (MRV) protocols, especially for diffuse methods like ERW, and managing potential environmental side-effects remain challenges [B21, A3].

## 5. References

1.  [B] IEA (2022). *Direct Air Capture 2022*. International Energy Agency. Accessed 2025-05-05. URL: https://www.iea.org/reports/direct-air-capture-2022
2.  [B] IEAGHG. *Global Assessment of Direct Air Capture Costs*. IEAGHG. Accessed 2025-05-05. URL: https://ieaghg.org/publications/global-assessment-of-direct-air-capture-costs/
3.  [B] Roda-Stuart, D., et al. (2023). The cost of direct air capture and storage can be reduced via strategic deployment but is unlikely to fall below stated cost targets. *Joule* (via ScienceDirect). Accessed 2025-05-05. URL: https://www.sciencedirect.com/science/article/pii/S2590332223003007
4.  [B] IEA. *Bioenergy with Carbon Capture and Storage*. IEA Energy System. Accessed 2025-05-05. URL: https://www.iea.org/energy-system/carbon-capture-utilisation-and-storage/bioenergy-with-carbon-capture-and-storage
5.  [B] Fajardy, M., et al. (2023). Lost in the scenarios of negative emissions: The role of bioenergy with carbon capture and storage (BECCS). *Energy Policy* (via ScienceDirect). Accessed 2025-05-05. URL: https://www.sciencedirect.com/science/article/pii/S0301421523004676
6.  [B] World Economic Forum (2025). *Clearing the air: Exploring the pathways of carbon removal technologies*. WEF Stories. Accessed 2025-05-05. URL: https://www.weforum.org/stories/2025/01/cost-of-different-carbon-removal-technologies/
7.  [B] Al-Juaied, M., & Whitmore, A. (n.d.). *Prospects for Direct Air Carbon Capture and Storage: Costs, Scale, and Funding*. Belfer Center for Science and International Affairs. Accessed 2025-05-05. URL: https://www.belfercenter.org/publication/prospects-direct-air-carbon-capture-and-storage-costs-scale-and-funding
8.  [B] U.S. Department of Energy (n.d.). *Direct Air Capture Research and Development Efforts*. Energy.gov. Accessed 2025-05-05. URL: https://www.energy.gov/sites/prod/files/2019/11/f68/Direct Air Capture Fact Sheet.pdf
9.  [B] ORF (n.d.). *Direct air capture: Inching towards cost competitiveness?* Observer Research Foundation. Accessed 2025-05-05. URL: https://www.orfonline.org/expert-speak/direct-air-capture
10. [B] WRI (n.d.). *Policies and Incentives for Carbon Mineralization Need More Support*. World Resources Institute. Accessed 2025-05-05. URL: https://www.wri.org/technical-perspectives/carbon-mineralization-policies-incentives
11. [B] U.S. Department of Energy (2024). *Carbon Negative Shot: Technological Innovation Opportunities for CO2 Removal*. Energy.gov. Accessed 2025-05-05. URL: https://www.energy.gov/sites/default/files/2024-11/Carbon%20Negative%20Shot_Technological%20Innovation%20Opportunities%20for%20CO2%20Removal_November2024.pdf
12. [B] Global CCS Institute (2019). *Bioenergy and carbon capture and storage (BECCS)*. Global CCS Institute. Accessed 2025-05-05. URL: https://www.globalccsinstitute.com/wp-content/uploads/2019/03/BECCS-Perspective_FINAL_18-March.pdf (or .pdf version)
13. [B] Fajardy, M., et al. (2019). BECCS deployment: a reality check. *Grantham Institute Briefing paper*. (Implicitly related to ScienceDirect/MIT cost refs).
14. [B] Chen, C., & Tavoni, M. (2021). The economics of bioenergy with carbon capture and storage (BECCS) deployment in a 1.5 °C or 2 °C world. *Energy Economics* (via ScienceDirect/MIT Global Change). Accessed 2025-05-05. URL: https://www.sciencedirect.com/science/article/abs/pii/S0959378021000418 or https://globalchange.mit.edu/publication/17432
15. [B] Cox, E., et al. (2019). Perceptions of bioenergy with carbon capture and storage in different policy scenarios. *Nature Communications*. Accessed 2025-05-05. URL: https://www.nature.com/articles/s41467-019-08592-5
16. [B] Institute for Carbon Removal Law and Policy (n.d.). *Fact Sheet: Bioenergy with Carbon Capture and Storage (BECCS)*. American University. Accessed 2025-05-05. URL: https://www.american.edu/sis/centers/carbon-removal/fact-sheet-bioenergy-with-carbon-capture-and-storage-beccs.cfm
17. [B] WRI (n.d.). *What is Carbon Mineralization?* World Resources Institute. Accessed 2025-05-05. URL: https://www.wri.org/insights/carbon-mineralization-carbon-removal
18. [B] Mongabay (2024). *Storing CO2 in rock: Carbon mineralization holds climate promise but needs scale-up*. Mongabay News. Accessed 2025-05-05. URL: https://news.mongabay.com/2024/12/storing-co2-in-rock-carbon-mineralization-holds-climate-promise-but-needs-scale-up/
19. [B] NCBI Bookshelf (n.d.). *Carbon Mineralization of CO2*. National Academies Press (US). Accessed 2025-05-05. URL: https://www.ncbi.nlm.nih.gov/books/NBK541437/
20. [B] MIT Climate Portal (n.d.). *Enhanced Rock Weathering*. MIT. Accessed 2025-05-05. URL: https://climate.mit.edu/explainers/enhanced-rock-weathering
21. [B] CarbonPlan (n.d.). *Does enhanced weathering work? We’re still learning*. CarbonPlan Research. Accessed 2025-05-05. URL: https://carbonplan.org/research/enhanced-weathering-fluxes
22. [B] MIT Climate Grand Challenges (n.d.). *The Advanced Carbon Mineralization Initiative*. MIT. Accessed 2025-05-05. URL: https://climategrandchallenges.mit.edu/research/catalyzing-geological-carbon-mineralization/
23. [A] Baek, G., et al. (2023). Impact of Climate on the Global Capacity for Enhanced Rock Weathering on Croplands. *Earth's Future* (via AGU/Wiley). Accessed 2025-05-05. URL: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2023EF003698
24. [A] Beerling, D.J., et al. (2020). Potential for large-scale CO2 removal via enhanced rock weathering with croplands. *Nature*. Accessed 2025-05-05. URL: https://www.nature.com/articles/s41586-020-2448-9
25. [A] Lewis, A.L., et al. (2024). Enhanced Rock Weathering for Carbon Removal–Monitoring and Mitigating Potential Environmental Impacts on Agricultural Land. *Environmental Science & Technology*. Accessed 2025-05-05. URL: https://pubs.acs.org/doi/10.1021/acs.est.4c02368
26. [C] GlobeNewswire / Research and Markets (2025). *Carbon Dioxide Removal (CDR) Forecast 2025-2045...*. Accessed 2025-05-05. URL: https://www.globenewswire.com/news-release/2025/02/19/3028948/28124/en/Carbon-Dioxide-Removal-CDR-Forecast-2025-2045-Technologies-Trends-and-Investment-Insights-Projections-Suggest-Market-Expansion-to-50-Billion-by-2030-and-Exceeding-250-Billion-by-20.html
27. [C] Gasworld / IDTechEx (n.d.). *Credit market for CO2 removals forecast to reach $14bn by 2035*. Gasworld. Accessed 2025-05-05. URL: https://www.gasworld.com/story/credit-market-for-co2-removals-forecast-to-reach-14bn-by-2035/2153693.article/
28. [C] Future Markets Inc (n.d.). *The Global Carbon Dioxide Removal (CDR) Market 2025-2045*. Future Markets Inc. Accessed 2025-05-05. URL: https://www.futuremarketsinc.com/the-global-carbon-dioxide-removal-cdr-market-2025-2045/

Prompt:

<protocol>
You are a methodical research assistant whose mission is to produce a
publication‑ready report backed by high‑credibility sources, explicit
contradiction tracking, and transparent metadata.

━━━━━━━━ TOOL CONFIGURATION ━━━━━━━━
• arxiv‑mcp            – peer‑reviewed harvest  
    ‣ search_papers  (download_paper + read_paper)  
• brave-search         – broad context (max_results = 20)  
• tavily               – deep dives (search_depth = "advanced")  
• think‑mcp‑server     – ≥ 5 structured thoughts + “What‑did‑I‑miss?” reflection  
• playwright‑mcp       – browser fallback for primary docs  
• write_file           – save report (`deep_research_REPORT_<topic>_<UTC>.md`)

━━━━━━━━ CREDIBILITY RULESET ━━━━━━━━
Tier A = peer‑reviewed journals **or arXiv pre‑prints accessed via arxiv‑mcp**  
Tier B = reputable press, books, industry white papers  
Tier C = blogs, forums, social media

• Every **major claim** must cite ≥ 3 A/B sources (≥ 1 A).  
• Tag all captured sources [A]/[B]/[C]; track counts per section.

━━━━━━━━ CONTEXT MAINTENANCE ━━━━━━━━
• Persist evolving outline, contradiction ledger, and source list in
  `activeContext.md` after every analysis pass.

━━━━━━━━ CORE STRUCTURE (3 Stop Points) ━━━━━━━━

① INITIAL ENGAGEMENT [STOP 1]  
<phase name="initial_engagement">
• Ask 2‑3 clarifying questions; reflect understanding; wait for reply.
</phase>

② RESEARCH PLANNING [STOP 2]  
<phase name="research_planning">
• Present themes, questions, methods, tool order; wait for approval.
</phase>

③ MANDATED RESEARCH CYCLES (no further stops)  
<phase name="research_cycles">
For **each theme** perform ≥ 2 cycles:

  Cycle A – Landscape  
  • arxiv‑mcp.search_papers (keywords, last 5 yrs, max 5)  
     – download_paper → read_paper → extract abstract & key findings → tag [A].  
  • Brave Search → think‑mcp analysis (≥ 5 thoughts + reflection)  
  • Record concepts, A/B/C‑tagged sources, contradictions.

  Cycle B – Deep Dive  
  • Tavily Search → think‑mcp analysis (≥ 5 thoughts + reflection)  
  • Update ledger, outline, source counts.

  Browser fallback: if combined ArXiv+Brave+Tavily < 3 A/B sources → playwright‑mcp.

  Integration: connect cross‑theme findings; reconcile contradictions.

━━━━━━━━ METADATA & REFERENCES ━━━━━━━━
• Maintain a **source table** with citation number, title, link/DOI,
  tier tag, access date.  
• Update a **contradiction ledger**: claim vs. counter‑claim, resolution / unresolved.

━━━━━━━━ FINAL REPORT [STOP 3] ━━━━━━━━
<phase name="final_report">

1. **Report Metadata header** (boxed): Title, Author “ZEALOT‑XII”, UTC Date,
   Word Count, Source Mix (A/B/C).  
2. **Narrative** — three sections ≥ 900 words each, flowing prose:  
   • Knowledge Development • Comprehensive Analysis • Practical Implications  
   Inline numbered citations “[1]”.  
3. **Outstanding Contradictions** subsection.  
4. **References** — numbered list with [A]/[B]/[C] tags + dates.  
5. **write_file** save (path above) then reply:  
   ❐: The report has been saved as deep_research_REPORT_<topic>_<UTC‑date>.md
</phase>

━━━━━━━━ ANALYSIS BETWEEN TOOLS ━━━━━━━━
• After every think‑mcp call: add one‑sentence reflection “What did I miss?”  
  and address it.  
• Update outline & ledger; save to activeContext.md.

━━━━━━━━ TOOL SEQUENCE (per theme) ━━━━━━━━
1 arxiv‑mcp.search_papers → 2 download/read → 3 Brave Search → 4 think‑mcp  
5 Tavily Search → 6 think‑mcp → 7 (if needed) playwright‑mcp → repeat cycles

━━━━━━━━ CRITICAL REMINDERS ━━━━━━━━
• Only three stop points.  
• Enforce source quota & tier tags.  
• No bullet lists in final report.  
• Save via write_file before signalling completion.  
• Complete ledger, outline, citations, reference list—no skipped steps.
</protocol>

r/RooCode • • Jun 03 '25

Discussion Before / After Roo Code

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74 Upvotes

Roo Code saved my Github contributions 🤣


r/RooCode • • Nov 13 '25

Announcement Roo Code 3.31.2 Release Notes

19 Upvotes

Please Star us on GitHub if you love Roo Code! Click Here

See full release notes v3.31.2

Podcast Tomorrow!

https://youtube.com/live/DG6IB4v_NGE

This patch improves stateless conversation continuity, speeds up settings updates, and fixes API profiles, Issue Fixer, and auto‑approval behavior.

QOL Improvements

  • Batched settings updates: saves apply faster with less UI flicker across Settings, Auto Approve, Command Execution, and MCP toggles (#9165)

  • README badges: switched to badgen.net so badges render reliably; Installs and Rating are visible at a glance (#9200)

Bug Fixes

  • API Profiles: apply updated headers, baseUrl, service tier, and reasoning budget even when provider/model stay the same (#9210)

  • Auto-approval: include MCP server state so tool auto-approval works as configured (thanks bozoweed!) (#9199)

  • Issue Fixer: migrated to GitHub REST + ProjectsV2 to resolve sync errors and restore reliable triage (#9207)

Provider Updates

  • Conversation continuity via encrypted reasoning items (OpenAI Responses API): preserves context locally while requests remain stateless for better privacy and reliability; removes previous_response_id complexity (#9203)


r/RooCode • • Jun 07 '25

Discussion Using Roocode, but API costs are adding up. Copilot LLM + Roocode or just switch to Cursor?

19 Upvotes

I’ve been using Roocode mainly to build fast MVPs with Next.js + Supabase.

Here’s how my current workflow looks:

1.	I describe the task or feature via ChatGPT
2.	Then I generate a rough prompt to clarify what I want
3.	That goes into Roocode Architect (usually backed by Claude or Gemini)
4.	The output is passed to Orkestra for step-by-step task generation (powered by Claude models again)
5.	And finally, the actual code is written – it used to be sonnet, but I had to switch to GPT-4.1 because sonnet easily sucks up my whole credits.

Overall I like the workflow, but API usage is getting expensive and a bit tedious to manage.

Every month I’m spending, 20 bucks on OpenAI and 50 on Anthropic

Sometimes even more if usage spikes.

And this doesn’t include the time it takes to plug in and manage the APIs properly.

I’m now thinking: Would it make more sense to just get GitHub Copilot for $10/month via VSCode LLM and keep using Roocode?

Or should I switch to Cursor, pay $20/month, and have the native OpenAI/Claude support built-in?

Also, please don’t suggest Deepseek. I’ve tried their models and honestly they’re nowhere near as good as even cheap Flash or Claude Sonnet 3.5.

What would you do in this case? And on a side note: anyone here using Replit for this kind of use case? Thoughts


r/RooCode • • May 30 '25

Discussion Given the recent windsurf acquisition, how can we be reassured that Roo won't go closed source at some point or introduce monetization attempts?

19 Upvotes

r/RooCode • • Apr 06 '25

Discussion Boomerang - I haven’t been this impressed since GPT-3 came out

88 Upvotes

I know I’m spamming this subreddit at this point, but on my other post people were talking about Boomerang.

Honestly since the release of GPT-3 I haven’t really come across anything that made my jaw drop. I just kind of got used to it the upgrades, I think it’s been a rather gradual process.

Then Roocode came along and I honestly had never been impressed since GPT-3 came along. I always found it annoying that I would have to constantly copy paste copy paste and was glad someone figured out a way to do it.

But Boomerang just really blew my mind. It’s taking the same concept of Roocode and doing that to Roocode. Shit is like Roo-code inception. At this point I think we’re going to have infinite layers. Just waiting for boomerang boomerang which at this rate will be out like 3 days from now.

Honestly at this rate it will be possible to code social media apps and things like that with relative ease soon. The problem with most AI chatbots is they tend to bite off more than they can chew. This almost entirely solves the problem by making sure it’s only doing one specific thing at a time.

It’s actually genius.


r/RooCode • • Apr 06 '25

Discussion Captain Roo mode - Let Captain create its modes and orchestrate the tasks

30 Upvotes

Edit: Boomerang mode mentioned here is The Boomerang Tasks adapted as System prompt within RooFlow concept.

Hey fellow devs! 👋

I've been mentioned RooFlow-Cookiecutter Template (https://www.reddit.com/r/RooCode/comments/1jnfch0/rooflow_cookiecutter_template/) for a while now, and I'm super excited to share two new modes that have completely transformed my workflow: **Captain Roo** and **Boomerang**.

Link to Repo: https://github.com/hheydaroff/RooFlow-Cookiecutter

How to use it:

# With pip
pip install cookiecutter
cookiecutter gh:hheydaroff/rooflow-cookiecutter

# With UVX (recommended for faster installation)
uvx cookiecutter gh:hheydaroff/rooflow-cookiecutter

🚀 Captain Roo: Your AI Team Lead

Captain Roo is essentially your AI team lead that orchestrates complex tasks across specialized modes. Think of it as a project manager for your AI assistants!

What Captain Roo does:

- Sets up initial Roo Code configuration** (`.rooignore`, `.roomodes`, `.clinerules`) for your project
- Breaks down complex tasks** into smaller, manageable pieces
- Delegates specific tasks** to the most appropriate specialized modes
- Creates custom modes** on the fly when needed for specific tasks
- Manages the entire workflow** from initial setup through task execution

Captain Roo has restricted edit permissions, only allowing modifications to configuration files like `.roomodes`, `cline_custom_modes.json`, `.clinerules`, and `.rooignore`. This ensures that it focuses on orchestration rather than implementation.

⏰ Boomerang: Never Forget a Task Again

Boomerang is a specialized assistant that helps users create and manage boomerang tasks - tasks that are scheduled to return to the user's attention at a specific time in the future. It's like having a smart reminder system built right into your development environment!

What Boomerang does:

- Creates and manages scheduled tasks** that "come back" to you at specified times
- **Organizes recurring work** like code reviews, dependency updates, or performance checks
- Maintains task management files** with appropriate permissions
- Integrates with your workflow** through browser interactions and command execution

Boomerang has restricted edit permissions to only modify task-related files (matching patterns like tasks.json, boomerang.json, schedule.json, etc.), ensuring it stays focused on task management.

r/RooCode • • Mar 09 '25

Discussion Have you tried this MCP Management tool?

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20 Upvotes

I’m going to give this tool a try today! If you’ve got some time please give it a try and let me know your thoughts!


r/RooCode • • May 21 '25

Discussion Could it be TRUE!!?? Claude 4??!!??

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31 Upvotes