OpenAgentSkill
GitHub200+

Pre-install eval

calculator Eval report.

A machine-readable install decision for agents: task fit, Trust Score, Audit Score, install safety, permission surface, and a concrete validation plan before this skill touches a workspace.

Needs reviewMedium riskREVIEW Policy
73
Eval report
74
Trust
79
Audit
67
Agent safety

manual review

Require human approval before installing into a real workspace.

Required gates

Checks an agent must pass before install

Open JSON

Task fit

70

warn

Task fit is weak; compare alternatives before selecting.

  • Evaluate calculator before installing it in an agent workflow
  • automation
  • Browser automation workflows; Claude Code teams; teams that value GitHub adoption signals

Install path

92

pass

Install handoff is available.

  • npx skills add EXboys/evotown --skill calculator

Install command safety

92

pass

standard package or runtime install path

  • npx skills add EXboys/evotown --skill calculator

Trust score

74

warn

Good trust signals with a few areas worth checking before rollout.

  • Strong shortlist
  • 665 GitHub stars
  • MIT

Audit score

79

warn

Needs review

  • main.py does not handle malformed JSON or non-numeric inputs gracefully; json.loads() and float() can raise uncaught exceptions and crash with a traceback.

Agent safety gate

67

warn

Usable candidate, but the agent should surface permission and audit notes before installation.

  • Require human approval before installing into a real workspace.
  • main.py does not handle malformed JSON or non-numeric inputs gracefully; json.loads() and float() can raise uncaught exceptions and crash with a traceback.

License clarity

86

pass

MIT

  • MIT

Permission surface

100

pass

no high-risk permission surface in public metadata

  • Network access: medium

Validation plan

What the agent should do next

  1. 1Inspect repository, README/SKILL.md, license, and recent commits before production use.
  2. 2Install in an isolated workspace or sandbox with no production secrets available.
  3. 3Run the smallest representative task and record files touched, commands run, network access, and outputs.
  4. 4Compare the selected skill against at least one alternative when the eval status is review or failed.
  5. 5Promote only after the agent reports a successful verification result and unresolved warnings are accepted.

Do not use when

Conditions that require another skill

  • teams that need a vendor-supported SLA
  • production agents without a repository review
  • main.py does not handle malformed JSON or non-numeric inputs gracefully; json.loads() and float() can raise uncaught exceptions and crash with a traceback.
  • Input validation is minimal: missing fields default to add/0, which can silently produce results instead of reporting invalid requests.
  • SKILL.md does not document error behavior, limitations, or the exact output format beyond simple examples.
  • float() accepts non-finite values like Infinity/NaN in some JSON inputs, which could lead to misleading results.

Supporting checks

Trust signals behind the decision

README/SKILL.md completeness

pass

86

Metadata includes enough usage and workflow context

Recent maintenance

pass

88

2mo since push

Alternatives available

pass

82

Alternative skills are available for comparison.