Home/Compare/AgentGuard vs ps-fuzz

Comparison

AgentGuard vs ps-fuzz

Verdict

Pick AgentGuard when agentGuard is primarily JavaScript; ps-fuzz is Python; pick ps-fuzz when ps-fuzz is primarily Python; AgentGuard is JavaScript.

Markdown twin · AgentGuard alternatives · ps-fuzz alternatives

GraphCanon updated 1w

AgentGuard logo

AgentGuard

dipampaul17/AgentGuard

171pushed Jul 31, 2025
vs
ps-fuzz logo

ps-fuzz

prompt-security/ps-fuzz

702pushed Feb 16, 2026

Trust & integrity

SignalAgentGuardps-fuzz
Maintenance
Dormant (373d since push)
As of 1w · github_public_v1
Slowing (169d since push)
As of 2w · github_public_v1
Provenance
Not a fork · Personal account
As of 1w · github_public_v1
Not a fork · Organization account
As of 2w · github_public_v1
OSV dependency advisories
Published findings
As of 1mo · osv@v1
No lockfile (source not queried)
As of 1mo · 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

AgentGuard
Real-time guardrail that monitors token spend and manages LLM/agent loops in real time
ps-fuzz
Test and harden system prompts for GenAI apps to ensure safety and security.

Stars

AgentGuard
171
ps-fuzz
702

Forks

AgentGuard
10
ps-fuzz
102

Open issues

AgentGuard
1
ps-fuzz
20

Language

AgentGuard
JavaScript
ps-fuzz
Python

Adopt for

AgentGuard
AgentGuard is a budget-conscious observer for real-time token spending by AI agents and LLMs, integrating with major providers like OpenAI and Anthropic.
ps-fuzz
-

Persona

AgentGuard
-
ps-fuzz
-

Runtime

AgentGuard
-
ps-fuzz
-

License

AgentGuard
MIT
ps-fuzz
MIT

Last pushed

AgentGuard
Jul 31, 2025
ps-fuzz
Feb 16, 2026

Categories

AgentGuard
Evaluation & Observability, Inference & Serving
ps-fuzz
Developer Tools, Evaluation & Observability

Trust and health

Maintenance

AgentGuard
Dormant (18%)
ps-fuzz
Slowing (36%)

Days since push

AgentGuard
373d
ps-fuzz
169d

Open issues (now)

AgentGuard
1
ps-fuzz
20

Owner type

AgentGuard
User
ps-fuzz
Organization

OSV dependency advisories

AgentGuard
Published findings
ps-fuzz
No lockfile (source not queried)

Full report

AgentGuard
Trust report

Choose AgentGuard if…

  • AgentGuard is primarily JavaScript; ps-fuzz is Python.
  • Tags unique to AgentGuard: ai-agents, anthropic, cost-monitoring, observability.
  • Also covers Inference & Serving.
  • When you need precise control over spend and want live updates on token prices

When NOT to use AgentGuard

  • If you prioritize a different language for your project and cannot use JavaScript
  • In cases requiring more elaborate fallback mechanisms than what AgentGuard offers

Choose ps-fuzz if…

  • ps-fuzz is primarily Python; AgentGuard is JavaScript.
  • Tags unique to ps-fuzz: ai-fuzzer, fuzzer, generative-ai, llm-fuzzer.
  • Also covers Developer Tools.
  • When you need to methodically test system prompts in generative AI applications for potential security flaws.

When NOT to use ps-fuzz

  • If your project does not involve generative AI applications or does not require prompt testing for security reasons.
  • For tasks unrelated to the hardening and evaluation of system prompts, as ps-fuzz is specifically designed for this purpose.

Explore

Sources

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

GitHub stars on cards: AgentGuard 171 · ps-fuzz 702 (synced Aug 9, 2026).

Common questions

What is the difference between AgentGuard and ps-fuzz?
AgentGuard: Real-time guardrail that monitors token spend and manages LLM/agent loops in real time. ps-fuzz: Test and harden system prompts for GenAI apps to ensure safety and security.. See the comparison table for live GitHub stats and shared categories.
When should I choose AgentGuard over ps-fuzz?
Choose AgentGuard over ps-fuzz when AgentGuard is primarily JavaScript; ps-fuzz is Python; Tags unique to AgentGuard: ai-agents, anthropic, cost-monitoring, observability; Also covers Inference & Serving; When you need precise control over spend and want live updates on token prices.
When should I choose ps-fuzz over AgentGuard?
Choose ps-fuzz over AgentGuard when ps-fuzz is primarily Python; AgentGuard is JavaScript; Tags unique to ps-fuzz: ai-fuzzer, fuzzer, generative-ai, llm-fuzzer; Also covers Developer Tools; When you need to methodically test system prompts in generative AI applications for potential security flaws.
When should I avoid AgentGuard?
If you prioritize a different language for your project and cannot use JavaScript In cases requiring more elaborate fallback mechanisms than what AgentGuard offers
When should I avoid ps-fuzz?
If your project does not involve generative AI applications or does not require prompt testing for security reasons. For tasks unrelated to the hardening and evaluation of system prompts, as ps-fuzz is specifically designed for this purpose.
Is AgentGuard or ps-fuzz more popular on GitHub?
ps-fuzz has more GitHub stars (702 vs 171). Stars measure visibility, not whether either tool fits your constraints.
Are AgentGuard and ps-fuzz open source?
Yes - both are open-source projects on GitHub (AgentGuard: MIT, ps-fuzz: MIT).
Where can I find alternatives to AgentGuard or ps-fuzz?
GraphCanon lists graph-backed alternatives at AgentGuard alternatives and ps-fuzz alternatives (AgentGuard markdown twin, ps-fuzz 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, AgentGuard or ps-fuzz?
AgentGuard: Dormant. ps-fuzz: Slowing. 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 AgentGuard and ps-fuzz?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: AgentGuard trust report; ps-fuzz trust report.

Was this helpful?

Anonymous feedback helps us improve pages and translations.