Star200+

Pre-install eval

daily-progress-report 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
74
Eval report
74
Trust
80
Audit
64
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

84

pass

Task wording matches this skill metadata.

  • Evaluate daily-progress-report before installing it in an agent workflow
  • design-creative
  • Research agents workflows; Claude Code teams; builders willing to evaluate younger projects

Install path

92

pass

Install handoff is available.

  • npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill daily-progress-report

Install command safety

92

pass

standard package or runtime install path

  • npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill daily-progress-report

Trust score

74

warn

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

  • Strong shortlist
  • 282 GitHub stars
  • MIT

Audit score

80

warn

Needs review

  • SKILL.md does not explicitly list required Python packages (e.g., pandas) as dependencies, only python3 binary.

Agent safety gate

64

warn

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

  • Require human approval before installing into a real workspace.
  • SKILL.md does not explicitly list required Python packages (e.g., pandas) as dependencies, only python3 binary.

License clarity

86

pass

MIT

  • MIT

Permission surface

86

pass

filesystem or document access

  • Network access: medium
  • Filesystem 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
  • SKILL.md does not explicitly list required Python packages (e.g., pandas) as dependencies, only python3 binary.
  • No OpenAgentSkill engagement data yet
  • SKILL.md excerpt appears truncated in the review but may be complete in repository.
  • Quality score needs review

Supporting checks

Trust signals behind the decision

README/SKILL.md completeness

pass

86

Metadata includes enough usage and workflow context

Recent maintenance

pass

100

Pushed today

Alternatives available

pass

82

Alternative skills are available for comparison.