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DF building-with-jev

Write, compose, integrate, and improve programs that call Jev, TypeSafe's System One judgment model.

notque/vexjoy-agent Agent Skills author: notque MIT 11 files body ≈ 10 484 tokens Open the sourcegithub.com↗ analyzed 24 h ago

Write, compose, integrate, and improve programs that call Jev, TypeSafe's System One judgment model.

As a process F 49/100 · Will not run — References files that are not bundled: ../../shared-patterns/jev-production-lessons.md, scripts/jev_limits.py, scripts/jev_router_common.py

IntegrationSoftware developmentInfrastructureData and analyticstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
D
75/100
safety, quality, tests
Safety 60%
95
Quality 40%
45
Run on models
none yet
Process rating
F
49/100
Will not run
References files that are not bundled: ../../shared-patterns/jev-production-lessons.md, scripts/jev_limits.py, scripts/jev_router_common.py
Tools and files w 18
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Read Edit Write Bash Glob Grep

Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 10484 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: ../../shared-patterns/jev-production-lessons.md
  • warning missing-ref reference to a missing file: scripts/jev_limits.py
  • warning missing-ref reference to a missing file: scripts/jev_router_common.py
  • warning missing-ref reference to a missing file: scripts/jev_vercel.py
  • warning missing-ref reference to a missing file: scripts/jev-harness.py
  • warning missing-ref reference to a missing file: scripts/jev-browser-decide.py
  • warning missing-ref reference to a missing file: scripts/jev-route.py
  • warning missing-ref reference to a missing file: scripts/jev-compact.py
  • warning missing-ref reference to a missing file: scripts/jev-browser-agent.py
  • warning missing-ref reference to a missing file: scripts/jev_search.py
  • warning missing-ref reference to a missing file: scripts/jev-budget-check.py
  • note frontmatter-key unknown frontmatter key "user_invocable"
  • note frontmatter-key unknown frontmatter key "routing"

Process rating: all ten parameters 49/100

Will not run. References files that are not bundled: ../../shared-patterns/jev-production-lessons.md, scripts/jev_limits.py, scripts/jev_router_common.py
  • 0Tools and files. 11 referenced file(s) missing: ../../shared-patterns/jev-production-lessons.md, scripts/jev_limits.py, scripts/jev_router_common.py
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 40Result and completion. Does not say what the result is
  • 40Execution cost. Instruction body is 10484 tokens: crowds the task out of the window
  • 100Steps. 83 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 15 top-level sections: this looks like several domains in one skill
  • low The skill ranks results itself: that belongs to the system behind the tool, not the model

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 100: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 83 items
  • +4Reference files are cited in the instructions (10 of 10)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 45.