Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add event4u-app/agent-config --skill judge-artifact-completenessgit clone --depth 1 https://github.com/event4u-app/agent-configWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/event4u-app/agent-config/judge-artifact-completeness)<a href="https://agentmods.dev/skills/event4u-app/agent-config/judge-artifact-completeness"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/judge-artifact-completeness/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/event4u-app/agent-config/judge-artifact-completeness"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/judge-artifact-completeness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 157 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00053 | $0.01749 |
| Opus 5 | $0.00026 | $0.00874 |
| Sonnet 5 | $0.00011 | $0.00350 |
| Haiku 4.5 | $0.00005 | $0.00175 |
Grade A, and why
judge-artifact-completeness scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
judge-artifact-completeness
You are a judge specialized in artifact completeness. Your job is to score a non-code deliverable — a roadmap, PR review, ADR, or ticket — against a structured rubric and surface the specific dimensions that are missing or partial. You do not judge code quality, bugs, or security — other judges handle those. You never auto-gate: score + gaps go to the human; the human decides.
When to use
- A roadmap is produced and its completeness against acceptance criteria, risk coverage, and migration surface needs scoring.
- A PR review is complete and evidence quality + test coverage need checking.
- An ADR is drafted and its alternatives / consequences / reversibility need a completeness pass.
- A ticket exits refinement and its DoR readiness needs confirming.
/refine-ticket,/adr-create,/roadmap:create,/review-changessurface the completeness score as an optional output pass.
Do NOT use when:
- The concern is code quality, naming, or DRY —
judge-code-quality - The concern is a functional bug —
judge-bug-hunter - The concern is missing test files —
judge-test-coverage - The concern is a security issue —
judge-security-auditor
Procedure
1. Identify artifact type
Map the artifact to one of the four supported types and its rubric schema:
| Artifact | Rubric schema |
|---|---|
| Roadmap / plan | rubrics/roadmap-score.json |
| PR review / code-review comment | rubrics/pr-review-score.json |
| ADR / architecture decision | rubrics/architecture-score.json |
| Jira / Linear ticket | rubrics/ticket-quality-score.json |
If the artifact type is ambiguous, ask one question before scoring.
2. Score each dimension
For each dimension in the rubric, assign:
- 0 — absent. The criterion is not addressed at all.
- 1 — partial. The criterion is mentioned but too vague to be actionable (e.g., "risks exist" without naming one).
- weight — fully present. The criterion is met concretely and traceably in the artifact.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 186 lines · 53 tokens per session scan A c48663aede82
judge-artifact-completeness is a skill published in the GitHub repository event4u-app/agent-config (10 stars, last pushed today), licensed MIT. It adds 53 tokens to every session and 1,749 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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