Home/Compare/eval-view vs heron

Comparison

eval-view vs heron

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 heron if an open-source network traffic analysis tool for monitoring the performance of LLMs and AI agents without requiring SDK changes.

Markdown twin · eval-view alternatives · heron alternatives

GraphCanon updated Sep 20, 2026

eval-view logo

eval-view

hidai25/eval-view

134pushed Sep 5, 2026
vs
heron logo

heron

Netis/heron

101pushed Aug 18, 2026

Trust & integrity

Signaleval-viewheron
Maintenance
Active (13d since push)
As of Sep 18, 2026 · github_public_v1
Active (23d since push)
As of Sep 11, 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 11, 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
heron
Performance monitoring tool for LLM APIs and AI agents

Stars

eval-view
134
heron
101

Forks

eval-view
24
heron
10

Open issues

eval-view
2
heron
3

Language

eval-view
Python
heron
Rust

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
heron
An open-source network traffic analysis tool for monitoring the performance of LLMs and AI agents without requiring SDK changes.

Persona

eval-view
-
heron
-

Runtime

eval-view
-
heron
-

License

eval-view
Apache-2.0
heron
Apache-2.0

Last pushed

eval-view
Sep 5, 2026
heron
Aug 18, 2026

Categories

eval-view
AI Agents, Evaluation & Observability
heron
Evaluation & Observability

Trust and health

Days since push

eval-view
13d
heron
23d

Open issues (now)

eval-view
2
heron
3

Stars delta

eval-view
+8 (30d)
heron
+27 (30d)

Open issues delta

eval-view
-1 (30d)
heron
0 (30d)

Owner type

eval-view
User
heron
Organization

Full report

eval-view
Trust report

Choose eval-view if…

  • eval-view is primarily Python; heron is Rust.
  • Tags unique to eval-view: agent-benchmark, agent-evaluation, ai-agents, anthropic.
  • Also covers 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 heron if…

  • heron is primarily Rust; eval-view is Python.
  • Tags unique to heron: ai-agent-development, libpcap, llm-monitoring, rust.
  • When you need a provider-side solution that does not require altering existing codebases or SDKs to monitor performance metrics.

When NOT to use heron

  • When the need is for an in-agent monitoring tool rather than a network packet-based solution, as Heron operates on traffic.
  • In environments where live capture requires administrative privileges that are not available to the user performing the installation.
  • For real-time performance insights without prior deployment because Heron involves a setup phase and typically uses pre-collected `.pcap` files.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: eval-view 134 · heron 101 (synced Sep 20, 2026).

Common questions

What is the difference between eval-view and heron?
eval-view: Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI. heron: Performance monitoring tool for LLM APIs and AI agents. See the comparison table for live GitHub stats and shared categories.
When should I choose eval-view over heron?
Choose eval-view over heron when eval-view is primarily Python; heron is Rust; Tags unique to eval-view: agent-benchmark, agent-evaluation, ai-agents, anthropic; Also covers 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 heron over eval-view?
Choose heron over eval-view when heron is primarily Rust; eval-view is Python; Tags unique to heron: ai-agent-development, libpcap, llm-monitoring, rust; When you need a provider-side solution that does not require altering existing codebases or SDKs to monitor performance metrics.
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 heron?
When the need is for an in-agent monitoring tool rather than a network packet-based solution, as Heron operates on traffic. In environments where live capture requires administrative privileges that are not available to the user performing the installation. For real-time performance insights without prior deployment because Heron involves a setup phase and typically uses pre-collected .pcap files.
Is eval-view or heron more popular on GitHub?
eval-view has more GitHub stars (134 vs 101). Stars measure visibility, not whether either tool fits your constraints.
Are eval-view and heron open source?
Yes - both are open-source projects on GitHub (eval-view: Apache-2.0, heron: Apache-2.0).
Where can I find alternatives to eval-view or heron?
GraphCanon lists graph-backed alternatives at eval-view alternatives and heron alternatives (eval-view markdown twin, heron 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 heron?
eval-view: Active. heron: 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 heron?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: eval-view trust report; heron trust report.

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