Comparison
ECC vs tma1
Verdict
Pick ECC when eCC is primarily JavaScript; tma1 is Go; pick tma1 when tma1 is primarily Go; ECC is JavaScript.
Markdown twin · ECC alternatives · tma1 alternatives
GraphCanon updated today
Trust & integrity
| Signal | ECC | tma1 |
|---|---|---|
| Maintenance | Very active (2d since push) As of 4d · github_public_v1 | Very active (3d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal account As of 4d · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 4d · osv@v1 | No lockfile (source not queried) As of today · 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
- ECC
- The agent harness performance optimization system for AI agents
- tma1
- Local-first observability your agent reads back. TMA1 records every LLM call, then routes what it sees into the agent's next turn via hooks and MCP.
Stars
- ECC
- 228k
- tma1
- 109
Forks
- ECC
- 35k
- tma1
- 12
Open issues
- ECC
- 93
- tma1
- 5
Language
- ECC
- JavaScript
- tma1
- Go
Adopt for
- ECC
- ECC is a performance optimization system for AI agents built to enhance skills, instincts, memory, security, and development processes.
- tma1
- -
Persona
- ECC
- -
- tma1
- -
Runtime
- ECC
- -
- tma1
- -
License
- ECC
- MIT
- tma1
- Apache-2.0
Last pushed
- ECC
- Jul 9, 2026
- tma1
- Jul 11, 2026
Categories
- ECC
- AI Agents, Developer Tools
- tma1
- AI Agents, Developer Tools, LLM Frameworks
Trust and health
Days since push
- ECC
- 2d
- tma1
- 3d
Open issues (now)
- ECC
- 93
- tma1
- 5
Owner type
- ECC
- User
- tma1
- Organization
Full report
- ECC
- Trust report
- tma1
- Trust report
Choose ECC if…
- ECC is primarily JavaScript; tma1 is Go.
- License: ECC is MIT, tma1 is Apache-2.0.
- ECC requires JavaScript environment and is open-source, licensed under MIT. Specific setup details are not provided within repository data.
- Pricing: Being open source with an MIT license, ECC itself is free to use, but additional features or support might incur costs outside of the core project..
- Tags unique to ECC: anthropic, claude, llm, productivity.
- When you are specifically working with AI agents like Claude Code and Codex that require advanced performance tuning across multiple dimensions such as skills and memory management.
When NOT to use ECC
- For projects focusing solely on traditional software development workflows without AI components, ECC's specialized tools are not necessary.
- In scenarios where you're working with closed-source or proprietary AI systems that do not allow for the same levels of customization as open platforms like those optimized by ECC.
Choose tma1 if…
- tma1 is primarily Go; ECC is JavaScript.
- License: tma1 is Apache-2.0, ECC is MIT.
- Tags unique to tma1: agent-loop, agent-observability, codex, copilot-cli.
- Also covers LLM Frameworks.
When NOT to use tma1
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (affaan-m/ECC) · observed Jul 11, 2026
- GitHub forks (affaan-m/ECC) · observed Jul 11, 2026
- Last push (affaan-m/ECC) · observed Jul 9, 2026
- License file (MIT) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (tma1-ai/tma1) · observed Jul 15, 2026
- GitHub forks (tma1-ai/tma1) · observed Jul 15, 2026
- Last push (tma1-ai/tma1) · observed Jul 11, 2026
- License file (Apache-2.0) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: ECC 228k · tma1 109 (synced Jul 11, 2026).
Common questions
- What is the difference between ECC and tma1?
- ECC: The agent harness performance optimization system for AI agents. tma1: Local-first observability your agent reads back. TMA1 records every LLM call, then routes what it sees into the agent's next turn via hooks and MCP.. See the comparison table for live GitHub stats and shared categories.
- When should I choose ECC over tma1?
- Choose ECC over tma1 when ECC is primarily JavaScript; tma1 is Go; License: ECC is MIT, tma1 is Apache-2.0; ECC requires JavaScript environment and is open-source, licensed under MIT. Specific setup details are not provided within repository data; Pricing: Being open source with an MIT license, ECC itself is free to use, but additional features or support might incur costs outside of the core project.; Tags unique to ECC: anthropic, claude, llm, productivity; When you are specifically working with AI agents like Claude Code and Codex that require advanced performance tuning across multiple dimensions such as skills and memory management.
- When should I choose tma1 over ECC?
- Choose tma1 over ECC when tma1 is primarily Go; ECC is JavaScript; License: tma1 is Apache-2.0, ECC is MIT; Tags unique to tma1: agent-loop, agent-observability, codex, copilot-cli; Also covers LLM Frameworks.
- When should I avoid ECC?
- For projects focusing solely on traditional software development workflows without AI components, ECC's specialized tools are not necessary. In scenarios where you're working with closed-source or proprietary AI systems that do not allow for the same levels of customization as open platforms like those optimized by ECC.
- When should I avoid tma1?
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Is ECC or tma1 more popular on GitHub?
- ECC has more GitHub stars (228,395 vs 109). Stars measure visibility, not whether either tool fits your constraints.
- Are ECC and tma1 open source?
- Yes - both are open-source projects on GitHub (ECC: MIT, tma1: Apache-2.0).
- Where can I find alternatives to ECC or tma1?
- GraphCanon lists graph-backed alternatives at ECC alternatives and tma1 alternatives (ECC 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, ECC or tma1?
- ECC: Very 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 ECC and tma1?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ECC trust report; tma1 trust report.