Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/notque/vexjoy-agentnpx agentmods add skills/notque/vexjoy-agent/dWrote 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/notque/vexjoy-agent/d)<a href="https://agentmods.dev/skills/notque/vexjoy-agent/d"><img src="https://agentmods.dev/badge/skills/notque/vexjoy-agent/d/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/notque/vexjoy-agent/d"><img src="https://agentmods.dev/badge/skills/notque/vexjoy-agent/d.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00033 | $0.04230 |
| Opus 5.5 | $0.00013 | $0.01692 |
| Sonnet 5.5 | $0.00007 | $0.00846 |
| Haiku 4.5 | $0.00003 | $0.00423 |
Grade A, and why
d 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 today.
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 — 378 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/d — Jev Router
Routes a request in four parts. A deterministic pre-route.py guard keeps
git/PR and security work on their quality gates. You, the session model, pick
the agent, skill, and pipeline from the full routing manifest with /do's rule
text. Jev answers the attachment questions that add extra skills, and validates
that the restated outcome survives the route. A script validates your pick and
computes the attachments.
Design rationale: ${CLAUDE_SKILL_DIR}/references/jev-classifier-design.md.
Phase Banners
Every phase: /d > Phase N: PHASE_NAME — description...
After intent alignment resolves: === routing banner. Both required.
Phase 1: CLASSIFY
Resolve $SDIR: ${HOME}/.claude/scripts, falling back through
.hermes/.factory/.codex/.reasonix, or the repo's scripts/
directory.
Step 1 — JEV_RESULT. When JEV_RESULT is already in context (the
jev-route-injector hook ran the script before your first token), use it and
skip the command below.
REQUEST_FILE=$(mktemp); printf '%s' "{user_request}" > "$REQUEST_FILE"
python3 "$SDIR/jev-route.py" --request-file "$REQUEST_FILE" --json-compact
Fields: available, jev_called, source, forced, stack, project,
signals, signal_scores, domain_scores, error, latency_ms, usage.
forced is the safety force route (pr-workflow, pr-pipeline, security)
or null. project holds the request repository's languages, frameworks, and
datastores (names only) or null. error is set when Jev was unavailable or
its answers were unusable. Routing continues, and attach then carries only
the pre-route stack and the agent domain floor.
Step 2 — Pick. Set the complexity from /do Phase 1 (Trivial, Simple,
Medium, Complex). Trivial: go to Phase 1T.
For Simple and above, load /do's routing rules and the manifest. Read the rule
text in full and apply every rule:
python3 "$SDIR/print-route-rules.py"
bash "$SDIR/get-routing-manifest.sh" --request-file "$REQUEST_FILE"
What ships with it
4 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.
- today Changed · -12 lines · +8 tokens per session 0f222052c5f9
- 5d ago Changed · +24 lines 372549160f40
- 22d ago Changed 3f6264ee3581
- 23d ago Changed · +32 lines df5bbdc55ea9
- 24d ago Changed · +41 lines f19da0314dfe
- 25d ago Changed · +227 lines 88ee317a9e79
- 26d ago Changed · -159 lines · -6 tokens per session ab1e4e84cbf1
- 27d ago Changed · +4 lines 4eee12c34b8e
- 29d ago First seen · 221 lines · 31 tokens per session scan A 6a876020abee
d is a skill published in the GitHub repository notque/vexjoy-agent (442 stars, last pushed today), licensed MIT. It adds 33 tokens to every session and 4,230 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-18.
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