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 agentmods add skills/gtrabanco/agentic-workflow/design-featurenpx skills add gtrabanco/agentic-workflow --skill design-featuregit clone --depth 1 https://github.com/gtrabanco/agentic-workflowWrote 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/gtrabanco/agentic-workflow/design-feature)<a href="https://agentmods.dev/skills/gtrabanco/agentic-workflow/design-feature"><img src="https://agentmods.dev/badge/skills/gtrabanco/agentic-workflow/design-feature.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 | $0.00051 | $0.02619 |
| Opus 5 | $0.00026 | $0.01309 |
| Sonnet 5 | $0.00010 | $0.00524 |
| Haiku 4.5 | $0.00005 | $0.00262 |
Grade A, and why
design-feature 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 — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Feature
Product definition — the stage that turns an idea or a feature request into an exhaustive, checkable set of acceptance criteria, before any engineering planning happens. Docs only — no code, no branch.
Turn contract
Load and verify the canonical Turn contract (11 boxes) before ending every turn. Design-specific closure boxes (product half, capability/role matrix, expectation sweep, upsert) live only in INTERVIEW.md. Missing reference → STOP.
When to use
- A rough idea, no issue yet, and no SPEC:
design-feature "<idea>". - An existing feature slug whose SPEC is not yet marked
designed:design-feature <NN-slug>. - Revising an already-designed feature's product definition:
design-feature <NN-slug> "<change>"(instruction mode), or baredesign-feature <NN-slug>for review mode (see Interaction & upsert). plan-featureredirects here when it detects an undesigned feature or a product choice areview-specNEEDS-DESIGNverdict returned to the human.
Step 0 — Discover the project (always first)
Per the agent guide's Workflow conventions + documentation map, then
read what THIS skill needs: docs/features/_TEMPLATE/SPEC.md (the two-halves
layout + ## Design status marker), the roadmap (docs/features/ROADMAP.md),
the capability inventory (docs/CAPABILITIES.md — the substrate the
Integration closure walks; if the project has none, derive an ad-hoc inventory
from the architecture doc + codebase during step 5 and offer to seed the file
from the template), and — if the slug already has a folder — its existing
SPEC.md and decisions.md in full (upsert never starts blind). Skim the
architecture and domain docs relevant to the idea's area only far enough to
ground capability closure in the project's real entities and roles — deep
engineering research is the Engineering half's job, not this one.
Consume the internal evidence-grounding
capability for the ordered passes and the readiness preflight: inventory →
evidence → draft → cut → readiness. Its outcomes (READY-FOR-REVIEW | NEEDS-EVIDENCE | NEEDS-DESIGN | NEEDS-REPLAN) are an authoring gate, never an
approval: only review-spec can approve a Product half.
What ships with it
5 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 · +37 lines 9f3a6109a384
- 4d ago First seen · 163 lines · 51 tokens per session scan A 0b908db2e8e0
design-feature is a skill published in the GitHub repository gtrabanco/agentic-workflow (20 stars, last pushed today), licensed MIT. It adds 51 tokens to every session and 2,619 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 2026-08-30.
Other skills, from other repositories
create-glyph
Create R-based pictogram glyphs for skill, agent, or team icons in the visualization layer. Covers concept sketching, ggplot2 layer composition using the primitives library, color strategy, registration in the appropriate glyph mapping file and manifest, rendering via the build pipeline, and visual verification of the…
design-cli-output
Design terminal output for a CLI tool with chalk colors, Unicode glyphs, multiple verbosity levels (human, verbose, quiet, JSON), and consistent voice rules. Covers color palette selection, status indicator design, reporter function architecture, ceremony/narrative output variants, and cross-terminal compatibility.…
create-2d-composition
Compose 2D graphics programmatically using SVG generation, diagram layout algorithms, image compositing, and batch processing workflows. Use when generating diagrams, flowcharts, or infographics programmatically, creating reproducible scientific figures, automating production of badges or visual assets, building…
create-3d-scene
Set up a Blender scene programmatically via Python (bpy) with objects, materials, lighting, camera, and environment configuration. Use when creating reproducible 3D visualization scenes, automating product or architectural rendering setup, generating multiple scene variations programmatically, building template scenes…
design-shiny-ui
Design Shiny application UIs using bslib for theming, layoutcolumns for responsive grids, value boxes, cards, and custom CSS/SCSS. Covers page layouts, accessibility, and brand consistency. Use when building a new Shiny app UI from scratch, modernizing an existing app from fluidPage to bslib, applying brand theming…
audit-icon-pipeline
Detect missing glyphs, icons, and HD variants by comparing registries against glyph mapping files, icon directories, and manifests. Reports gaps for skills, agents, and teams across all palettes.