Comparison
eval-view vs tma1
Verdict
Pick eval-view if eval-view is a Python-based tool for regression testing of AI agents, supporting multiple platforms like LangGraph, CrewAI, OpenAI, and Anthropic. It snapshots AI behavior and detects regressions through diffing tool and; pick tma1 if tMA1 is specialized in local-first observability by tracking every LLM call and routing this information to the next agent turn via hooks and.
Markdown twin · eval-view alternatives · tma1 alternatives
GraphCanon updated Sep 20, 2026
10views this month
Trust & integrity
| Signal | eval-view | tma1 |
|---|---|---|
| Maintenance | Active (13d since push) As of Sep 18, 2026 · github_public_v1 | Very active (0d since push) As of Sep 10, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 10, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 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
- eval-view
- Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI
- tma1
- Local-first observability for AI agents with LLM call tracking
Stars
- eval-view
- 134
- tma1
- 117
Forks
- eval-view
- 24
- tma1
- 14
Open issues
- eval-view
- 2
- tma1
- 5
Language
- eval-view
- Python
- tma1
- Go
Adopt for
- eval-view
- Eval-view is a Python-based tool for regression testing of AI agents, supporting multiple platforms like LangGraph, CrewAI, OpenAI, and Anthropic. It snapshots AI behavior and detects regressions through diffing tool and
- tma1
- TMA1 is specialized in local-first observability by tracking every LLM call and routing this information to the next agent turn via hooks and MCP.
Persona
- eval-view
- -
- tma1
- -
Runtime
- eval-view
- -
- tma1
- -
License
- eval-view
- Apache-2.0
- tma1
- TMA1 is available under the Apache-2.0 license, allowing for broad usage with attribution.
Last pushed
- eval-view
- Sep 5, 2026
- tma1
- Sep 10, 2026
Categories
- eval-view
- AI Agents, Evaluation & Observability
- tma1
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- eval-view
- Active (82%)
- tma1
- Very active (96%)
Days since push
- eval-view
- 13d
- tma1
- 0d
Open issues (now)
- eval-view
- 2
- tma1
- 5
Stars delta
- eval-view
- +8 (30d)
- tma1
- +2 (30d)
Open issues delta
- eval-view
- -1 (30d)
- tma1
- -10 (30d)
Owner type
- eval-view
- User
- tma1
- Organization
Full report
- eval-view
- Trust report
- tma1
- Trust report
Choose eval-view if…
- eval-view is primarily Python; tma1 is Go.
- Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, ai-agents.
- eval-view ships Docker support for self-hosted deployment.
- When you need to snapshot and diff the behavior of AI agents across multiple platforms, including LangGraph, CrewAI, OpenAI, and Anthropic.
When NOT to use eval-view
- If you are working exclusively with AI platforms not supported by eval-view, such as those not listed among LangGraph, CrewAI, OpenAI, and Anthropic.
- When you do not require regression testing or behavior snapshotting for your AI agents, as eval-view is specifically designed for these purposes.
- If you are looking for a tool that does not involve backend API charges for executing your agent, as eval-view does not skip these charges even with the --no-judge flag.
- If you need a tool that automatically handles the migration from the OpenAI Assistants API to the Responses API without manual intervention, as eval-view requires following a migration guide for this.
Choose tma1 if…
- tma1 is primarily Go; eval-view is Python.
- Pricing: Free open-source tool with no initial cost to use or modify according to its Apache-2.0 license..
- Requirements: TMA1 requires an installation script that auto-configures and sets up GreptimeDB.; Operational requirements are platform-independent, as it supports macOS/Linux install scripts and a PowerShell one for Windows..
- Tags unique to tma1: agent-observability, claude-code, codex, greptimedb.
- Use TMA1 if you are operating self-hosted AI agents and require detailed observability over LLM calls that can be routed into subsequent turns for further action.
When NOT to use tma1
- Avoid TMA1 if you prefer cloud-based solutions or require real-time collaboration features that it does not inherently support due to its self-hosted nature.
- Do not use TMA1 in environments sensitive to open ports, since it runs a local server and dashboard accessible at default localhost settings which may not suit all security policies.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (hidai25/eval-view) · observed Sep 20, 2026
- GitHub forks (hidai25/eval-view) · observed Sep 20, 2026
- Last push (hidai25/eval-view) · observed Sep 5, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (tma1-ai/tma1) · observed Sep 20, 2026
- GitHub forks (tma1-ai/tma1) · observed Sep 20, 2026
- Last push (tma1-ai/tma1) · observed Sep 10, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: eval-view 134 · tma1 117 (synced Sep 20, 2026).
Common questions
- What is the difference between eval-view and tma1?
- eval-view: Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI. tma1: Local-first observability for AI agents with LLM call tracking. See the comparison table for live GitHub stats and shared categories.
- When should I choose eval-view over tma1?
- Choose eval-view over tma1 when eval-view is primarily Python; tma1 is Go; Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, ai-agents; eval-view ships Docker support for self-hosted deployment; When you need to snapshot and diff the behavior of AI agents across multiple platforms, including LangGraph, CrewAI, OpenAI, and Anthropic.
- When should I choose tma1 over eval-view?
- Choose tma1 over eval-view when tma1 is primarily Go; eval-view is Python; Pricing: Free open-source tool with no initial cost to use or modify according to its Apache-2.0 license.; Requirements: TMA1 requires an installation script that auto-configures and sets up GreptimeDB.; Operational requirements are platform-independent, as it supports macOS/Linux install scripts and a PowerShell one for Windows.; Tags unique to tma1: agent-observability, claude-code, codex, greptimedb; Use TMA1 if you are operating self-hosted AI agents and require detailed observability over LLM calls that can be routed into subsequent turns for further action.
- When should I avoid eval-view?
- If you are working exclusively with AI platforms not supported by eval-view, such as those not listed among LangGraph, CrewAI, OpenAI, and Anthropic. When you do not require regression testing or behavior snapshotting for your AI agents, as eval-view is specifically designed for these purposes. If you are looking for a tool that does not involve backend API charges for executing your agent, as eval-view does not skip these charges even with the --no-judge flag. If you need a tool that automatically handles the migration from the OpenAI Assistants API to the Responses API without manual intervention, as eval-view requires following a migration guide for this.
- When should I avoid tma1?
- Avoid TMA1 if you prefer cloud-based solutions or require real-time collaboration features that it does not inherently support due to its self-hosted nature. Do not use TMA1 in environments sensitive to open ports, since it runs a local server and dashboard accessible at default localhost settings which may not suit all security policies.
- Is eval-view or tma1 more popular on GitHub?
- eval-view has more GitHub stars (134 vs 117). Stars measure visibility, not whether either tool fits your constraints.
- Are eval-view and tma1 open source?
- Yes - both are open-source projects on GitHub (eval-view: Apache-2.0, tma1: Apache-2.0).
- Where can I find alternatives to eval-view or tma1?
- GraphCanon lists graph-backed alternatives at eval-view alternatives and tma1 alternatives (eval-view markdown twin, tma1 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, eval-view or tma1?
- eval-view: Active. tma1: Very active. 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 eval-view and tma1?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: eval-view trust report; tma1 trust report.