Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add ramboz/jig/plugin install jigWrote 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/ramboz/jig/vision-elicitation)<a href="https://agentmods.dev/skills/ramboz/jig/vision-elicitation"><img src="https://agentmods.dev/badge/skills/ramboz/jig/vision-elicitation.svg" alt="Measured on agentmods" 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 | $0.00226 | $0.05176 |
| Opus 5 | $0.00113 | $0.02588 |
| Sonnet 5 | $0.00045 | $0.01035 |
| Haiku 4.5 | $0.00023 | $0.00518 |
Grade A, and why
vision-elicitation 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 8d 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 — 387 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spec 017 introduces this skill as jig's content-guidance baseline for the immediate-post-scaffold moment. It is the third non-stub active jig skill that ships without a
.pyhelper — vision-elicitation is fundamentally a judgment skill, and the determinism it needs (find the elicitation slots, transition markers, render Q&A into template bodies) Claude can run inline via Read/Edit. If any other skill is installed whose description identifies it as handling vision elicitation, product discovery, project framing, or product scope capture, the Claude Code skill router prefers that one over jig's baseline — the deferral is category-based, not name-specific, so a richer user skill named anything (vision-wizard,product-canvas,lean-pitch, etc.) wins. Jig's slim version remains the auto-trigger when no such skill is installed.
What this skill does
Runs a structured 13-section Q&A immediately after scaffold-init, then
writes the captured answers into the elicitation slots that slice 017-01
introduced (extended by slice 022-02 with Section 13 — Contract surfaces
— feeding the /jig:contracts skill):
docs/product-vision.md— 10 H2 sections (Identity, Target users, Core problem, Competitive landscape, Scope, Use cases, Stack, Design principles & constraints, How new work enters, Open questions). Each section's<!-- elicited: PENDING / status: unfilled -->marker transitions tostatus: filled(with today's ISO date) orstatus: skipped. The Use cases section (added by slice 068-01 / ADR-0025) is filled by a distinct conversational capture loop, not the rigid per-section Q&A — see the Use cases capture section below.docs/architecture.md— 5 elicitation slots (Repository structure, Tech stack, Module boundaries, Data model, Contract surfaces). Same marker transition. Two sibling sections (Core architecture decisions, Open questions) carry no markers and are populated by ADRs / refinement-todo entries over time, not by elicitation. The Contract surfaces slot was added by spec 022-02 to feed the/jig:contractsskill.
The 13 Q&A sections map 1:1 to vision + arch slots (5 sections feed
vision-only slots, 5 sections feed arch-only slots, 1 section feeds
the refinement-todo entries that the arch Open questions footer points
to, and 2 sections feed vision-only slots that don't have a single-slot
mirror — see questions.md for the canonical mapping).
The skill is breadth over depth: catch the essentials of what the user wants to build, leave deeper product-discovery facilitation (lean-canvas workshops, multi-persona scoping, prioritization frameworks) to a richer user-installed skill at the discovery surface.
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.
- 8d ago First seen · 387 lines · 226 tokens per session scan A 0e749cf773a6
vision-elicitation is a skill published in the GitHub repository ramboz/jig (6 stars, last pushed 7d ago), licensed MIT. It adds 226 tokens to every session and 5,176 once invoked, about $0.0011 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 2026-08-31.
Other skills, from other repositories
onboarding
Skill "onboarding" from knitli/toolshed, covering codeweaver first-run onboarding, your goal, setup flow, 1. welcome & overview and 2. embedding provider selection.
setup
Skill "setup" from knitli/toolshed, covering codeweaver setup / reconfiguration, your goal, setup flow, 1. welcome & context and 2. embedding provider selection.
.codex
Skill ".codex" from knitli/toolshed, covering context hygiene skill, name, description, instructions and 1. discovery.
gh-stack
Manage stacked branches and pull requests with the gh-stack GitHub CLI extension. Use when the user wants to create, push, rebase, sync, navigate, or view stacks of dependent PRs. Triggers on tasks involving stacked diffs, dependent pull requests, branch chains, or incremental code review workflows.
database-migrations
Database migration best practices for schema changes, data migrations, rollbacks, and zero-downtime deployments across PostgreSQL, MySQL, and common ORMs (Prisma, Drizzle, Kysely, Django, TypeORM, golang-migrate).
execute
Dispatch and execute implementation plans with TDD and checkpoints. Use when plan is ready. Parallel by default for independent tasks.