Comparison
DeepSeek-Reasonix vs self-repair
Verdict
Pick DeepSeek-Reasonix if deepSeek-Reasonix is a terminal-based AI coding agent designed for stability and continuous operation, built with prompt caching and stability in mind; pick self-repair if self-repair provides tools to replicate research experiments on code generation systems self-reparation techniques.
Markdown twin · DeepSeek-Reasonix alternatives · self-repair alternatives
GraphCanon updated Oct 7, 2026
9views this month
vs
Trust & integrity
| Signal | DeepSeek-Reasonix | self-repair |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 | Archived (887d since push) As of Oct 7, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 18, 2026 · github_public_v1 | Not a fork · Personal account As of Oct 7, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Sep 18, 2026 · osv@v1 | No published findings from this source as of 2026-07-11 As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- DeepSeek-Reasonix
- DeepSeek-native AI coding agent for terminal
- self-repair
- Supports research on self-repair mechanisms for code generation
Stars
- DeepSeek-Reasonix
- 36k
- self-repair
- 15
Forks
- DeepSeek-Reasonix
- 2.4k
- self-repair
- 3
Open issues
- DeepSeek-Reasonix
- 1.9k
- self-repair
- 1
Language
- DeepSeek-Reasonix
- Go
- self-repair
- Python
Adopt for
- DeepSeek-Reasonix
- DeepSeek-Reasonix is a terminal-based AI coding agent designed for stability and continuous operation, built with prompt caching and stability in mind.
- self-repair
- Self-repair provides tools to replicate research experiments on code generation systems self-reparation techniques.
Persona
- DeepSeek-Reasonix
- -
- self-repair
- -
Runtime
- DeepSeek-Reasonix
- -
- self-repair
- -
License
- DeepSeek-Reasonix
- MIT License
- self-repair
- -
Last pushed
- DeepSeek-Reasonix
- Sep 18, 2026
- self-repair
- May 2, 2024
Categories
- DeepSeek-Reasonix
- AI Agents, Developer Tools
- self-repair
- Developer Tools
Trust and health
Maintenance
- DeepSeek-Reasonix
- Very active (96%)
- self-repair
- Archived (8%)
Days since push
- DeepSeek-Reasonix
- 0d
- self-repair
- 887d
Archived on GitHub
- DeepSeek-Reasonix
- No
- self-repair
- Yes
Open issues (now)
- DeepSeek-Reasonix
- 1.9k
- self-repair
- 1
Stars delta
- DeepSeek-Reasonix
- +953 (30d)
- self-repair
- 0 (30d)
Open issues delta
- DeepSeek-Reasonix
- +511 (30d)
- self-repair
- 0 (30d)
OSV dependency advisories
- DeepSeek-Reasonix
- Published findings
- self-repair
- No published findings from this source as of 2026-07-11
Full report
- DeepSeek-Reasonix
- Trust report
- self-repair
- Trust report
Choose DeepSeek-Reasonix if…
- DeepSeek-Reasonix is primarily Go; self-repair is Python.
- Pricing: Free to use under the MIT License, with potential for premium features or services..
- Requirements: Min 2 GB RAM; Requires a terminal environment for operation..
- Tags unique to DeepSeek-Reasonix: agent, ai-agent, ai-coding, cli.
- Also covers AI Agents.
- When you need a stable AI coding agent that can run continuously in the terminal, leveraging prompt caching for efficiency.
When NOT to use DeepSeek-Reasonix
- If you prefer a graphical user interface over a terminal-based tool, as Reasonix is optimized for CLI and TUI use.
- When you do not require DeepSeek-native integration, as Reasonix is specifically designed to work within this ecosystem.
Choose self-repair if…
- self-repair is primarily Python; DeepSeek-Reasonix is Go.
- Tags unique to self-repair: code-repair, experiments replication, python, research-tools.
- When aiming to replicate specific experimental data from the ICLR 2024 paper on self-repair in code generation
When NOT to use self-repair
- For creating entirely new datasets or conducting large-scale human studies, as this repository focuses on replicating existing experiments
- When the internal dependencies or incomplete code functions such as exec_sample in APPS are critical for your application without modification
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (esengine/DeepSeek-Reasonix) · observed Sep 20, 2026
- GitHub forks (esengine/DeepSeek-Reasonix) · observed Sep 20, 2026
- Last push (esengine/DeepSeek-Reasonix) · observed Sep 18, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (theoxo/self-repair) · observed Oct 7, 2026
- GitHub forks (theoxo/self-repair) · observed Oct 7, 2026
- Last push (theoxo/self-repair) · observed May 2, 2024
- License file (unknown) · observed Oct 7, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: DeepSeek-Reasonix 36k · self-repair 15 (synced Sep 20, 2026).
Common questions
- What is the difference between DeepSeek-Reasonix and self-repair?
- DeepSeek-Reasonix: DeepSeek-native AI coding agent for terminal. self-repair: Supports research on self-repair mechanisms for code generation. See the comparison table for live GitHub stats and shared categories.
- When should I choose DeepSeek-Reasonix over self-repair?
- Choose DeepSeek-Reasonix over self-repair when DeepSeek-Reasonix is primarily Go; self-repair is Python; Pricing: Free to use under the MIT License, with potential for premium features or services.; Requirements: Min 2 GB RAM; Requires a terminal environment for operation.; Tags unique to DeepSeek-Reasonix: agent, ai-agent, ai-coding, cli; Also covers AI Agents; When you need a stable AI coding agent that can run continuously in the terminal, leveraging prompt caching for efficiency.
- When should I choose self-repair over DeepSeek-Reasonix?
- Choose self-repair over DeepSeek-Reasonix when self-repair is primarily Python; DeepSeek-Reasonix is Go; Tags unique to self-repair: code-repair, experiments replication, python, research-tools; When aiming to replicate specific experimental data from the ICLR 2024 paper on self-repair in code generation.
- When should I avoid DeepSeek-Reasonix?
- If you prefer a graphical user interface over a terminal-based tool, as Reasonix is optimized for CLI and TUI use. When you do not require DeepSeek-native integration, as Reasonix is specifically designed to work within this ecosystem.
- When should I avoid self-repair?
- For creating entirely new datasets or conducting large-scale human studies, as this repository focuses on replicating existing experiments When the internal dependencies or incomplete code functions such as exec_sample in APPS are critical for your application without modification
- Is DeepSeek-Reasonix or self-repair more popular on GitHub?
- DeepSeek-Reasonix has more GitHub stars (35,596 vs 15). Stars measure visibility, not whether either tool fits your constraints.
- Are DeepSeek-Reasonix and self-repair open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to DeepSeek-Reasonix or self-repair?
- GraphCanon lists graph-backed alternatives at DeepSeek-Reasonix alternatives and self-repair alternatives (DeepSeek-Reasonix markdown twin, self-repair markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, DeepSeek-Reasonix or self-repair?
- DeepSeek-Reasonix: Very active. self-repair: Archived. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for DeepSeek-Reasonix and self-repair?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DeepSeek-Reasonix trust report; self-repair trust report.