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 notque/vexjoy-agent --skill workflowgit clone --depth 1 https://github.com/notque/vexjoy-agentWrote 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/workflow)<a href="https://agentmods.dev/skills/notque/vexjoy-agent/workflow"><img src="https://agentmods.dev/badge/skills/notque/vexjoy-agent/workflow/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/workflow"><img src="https://agentmods.dev/badge/skills/notque/vexjoy-agent/workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00020 | $0.02985 |
| Opus 5.5 | $0.00008 | $0.01194 |
| Sonnet 5.5 | $0.00004 | $0.00597 |
| Haiku 4.5 | $0.00002 | $0.00298 |
Grade A, and why
workflow 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 25d 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 — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workflow Skill
Five modes for structured multi-phase work. Match the request, follow that mode's instructions.
Mode Selection
| Request pattern | Mode |
|---|---|
| Feature design/plan/implement/validate/release, end-to-end | Feature Lifecycle |
| Write spec, define requirements, create plan, interview, pause/resume | Planning |
| Keep working until, iterate until done, drive to done | Objective Loop |
| Make faster, speed up, reduce latency, profile, hill climb | Hill Climb |
| All other structured workflows: review, debug, refactor, research, create, explore, upgrade | Ad-Hoc Workflow |
Feature Lifecycle
Phase-gated workflow: DESIGN > PLAN > IMPLEMENT > VALIDATE > RELEASE. Each phase must pass its gate before the next begins.
Phase Routing
If .feature/ exists, check state: python3 ~/.claude/scripts/feature-state.py status.
Route to the indicated phase.
If no feature state exists, determine entry from intent:
- "design", "think through", "explore approaches" -> DESIGN
- "plan", "break down", "create tasks" -> PLAN (requires completed design)
- "implement", "execute plan" -> IMPLEMENT (requires completed plan)
- "validate", "quality gates" -> VALIDATE (requires completed implementation)
- "release", "merge", "ship it" -> RELEASE (requires passed validation)
- "end to end", "full lifecycle" -> DESIGN (start from beginning)
Phase References
Load the phase reference, then follow it exactly:
| Phase | Reference | Produces |
|---|---|---|
| DESIGN | references/fl-design.md |
design.md |
| PLAN | references/fl-plan.md |
Wave-ordered task list |
| IMPLEMENT | references/fl-implement.md |
Code changes |
| VALIDATE | references/fl-validate.md |
Quality gate report |
| RELEASE | references/fl-release.md |
Merged PR |
| End-to-end | references/fl-pipeline.md |
Full lifecycle |
| State conventions | references/fl-shared.md |
-- |
| Error recovery | references/fl-error-handling.md |
-- |
What ships with it
60 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.
- references/adr-template.md 9.4 KB
- references/agent-upgrade.md 12 KB
- references/article-evaluation-pipeline.md 8.9 KB
- references/article-evaluation-pipeline/references/report-template.md 2.5 KB
- references/article-evaluation-pipeline/references/wabi-sabi-classification.md 2.4 KB
- references/auto-pipeline.md 12 KB
- references/auto-pipeline/references/pipeline-catalog.json 15 KB
- references/auto-pipeline/references/pipeline-catalog.md 4.3 KB
- references/build_dag.py 13 KB runs code
- references/chain-composer.md 20 KB
- references/chain-composer/references/canonical-chains.md 14 KB
- references/comprehensive-review-workflow.js 16 KB runs code
- references/comprehensive-review.md 25 KB
- references/comprehensive-review/references/output-templates.md 11 KB
- references/comprehensive-review/references/wave-0-per-package.md 5.2 KB
- references/comprehensive-review/references/wave-1-foundation.md 9.3 KB
- references/comprehensive-review/references/wave-2-deep-dive.md 6.7 KB
- references/comprehensive-review/references/wave-3-adversarial.md 6.9 KB
- references/dag-compatibility-matrix.md 13 KB
- references/dag-composition-patterns.md 5.0 KB
- references/dag-orchestration-advanced.md 6.3 KB
- references/dag-orchestration-examples.md 11 KB
- references/dag-skill-patterns.md 13 KB
- references/de-ai-pipeline.js 14 KB runs code
- references/de-ai-pipeline.md 6.3 KB
- references/discover_skills.py 12 KB runs code
- references/do-perspectives.md 11 KB
- references/doc-pipeline.md 9.2 KB
- references/domain-research.md 32 KB
- references/domain-research/references/task-type-guide.md 11 KB
- references/explore-pipeline.js 18 KB runs code
- references/explore-pipeline.md 15 KB
- references/fan-out-workflow.js 9.3 KB runs code
- references/feedback-loop-construction.md 14 KB
- references/fl-design.md 9.2 KB
- references/fl-error-handling.md 8.4 KB
- references/fl-implement.md 7.4 KB
- references/fl-pipeline.md 6.0 KB
- references/fl-plan.md 11 KB
- references/fl-release.md 3.8 KB
- references/fl-shared.md 3.6 KB
- references/fl-validate.md 4.5 KB
- references/github-profile-rules.md 10 KB
- references/github-profile-rules/references/rule-categories.md 6.5 KB
- references/hc-domain-playbooks.md 15 KB
- references/hc-ledger.md 3.3 KB
- references/hc-profiling-tools.md 3.7 KB
- references/hc-SPEC.md 3.3 KB
- references/hill-climb.md 9.3 KB
- references/hook-development-pipeline.md 13 KB
- references/mcp-pipeline-builder.md 16 KB
- references/mcp-pipeline-builder/references/analysis-checklist.md 6.2 KB
- references/mcp-pipeline-builder/references/design-rules.md 7.1 KB
- references/mcp-pipeline-builder/references/evaluation-guide.md 7.6 KB
- references/mcp-pipeline-builder/references/python-scaffold-template.md 9.5 KB
- references/mcp-pipeline-builder/references/ts-scaffold-template.md 1.6 KB
- references/mcp-pipeline-builder/scripts/assemble-scaffold.py 6.3 KB runs code
- references/mcp-pipeline-builder/scripts/register_mcp.py 6.9 KB runs code
- references/mcp-pipeline-builder/templates/client-cli.ts.tmpl 682 B
- references/mcp-pipeline-builder/templates/client-http.ts.tmpl 1.4 KB
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.
- 26d ago Changed · -239 lines · +3 tokens per session ec16e266816c
- 27d ago Changed · +175 lines · -14 tokens per session ceb051c8dd96
- 1mo ago First seen · 143 lines · 34 tokens per session scan A 1a3ce2726650
workflow is a skill published in the GitHub repository notque/vexjoy-agent (442 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 2,985 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 2026-09-03.
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