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 widnyana/eyay-toolkits --skill design-graphgit clone --depth 1 https://github.com/widnyana/eyay-toolkitsWrote 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/widnyana/eyay-toolkits/design-graph)<a href="https://agentmods.dev/skills/widnyana/eyay-toolkits/design-graph"><img src="https://agentmods.dev/badge/skills/widnyana/eyay-toolkits/design-graph/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/widnyana/eyay-toolkits/design-graph"><img src="https://agentmods.dev/badge/skills/widnyana/eyay-toolkits/design-graph.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 | $0.00064 | $0.01023 |
| Opus 5 | $0.00032 | $0.00511 |
| Sonnet 5 | $0.00013 | $0.00205 |
| Haiku 4.5 | $0.00006 | $0.00102 |
Grade A, and why
design-graph 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 4d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Graph — The Artifact
A Design Graph is the annotated call graph of a concrete problem. It is
what you produce when you apply Design Thinking (see the design-method skill) to
something, and it is written in Graph Protocol notation (see the graph-protocol skill).
Nodes are functions. Edges are data flow. The annotations answer, for every node: what flows through it (A), how many times it runs (cardinality), where and how it can fail (E), and what it needs to exist (R) — plus the global concerns: trust boundaries, behavior layers, resource scope, and test layers.
A Design Graph is not documentation written after the fact. It is drawn before implementation (planning), reconstructed from implementation (review), and compared against implementation (verdict). The graph is the contract; the code is one instantiation of it. Hard gate: when a turn will produce code or file edits, the graph comes first — render it (and any clarifying questions), get the user's approval, and only then write code that matches it.
What a complete Design Graph contains
PROBLEM: <one line>
X → DesignGraph<A, E, R>
│ │ │ │ │
│ │ │ │ └─ R: what each node needs (§5)
│ │ │ └──── E: where the graph breaks (§4)
│ │ └─────── A: what flows through nodes (§2)
│ │
│ └─ nodes = functions, edges = data flow
│
└─ the problem
SHAPES: … every noun the graph needs
GRAPH: … ascii call graph with inline R:/E:/🔒/(n) annotations
CARDINALITY: … every node marked (1) (N) or (T)
BOUNDARIES: … every unknown → trusted crossing
BEHAVIOR: … every orthogonal layer and what it wraps
SCOPE: … every resource with acquire@x → release@x
TEST LAYERS: … the R tests provide — same GRAPH, zero code change
VERDICT: … code matches graph? A and E structurally separated?
Completeness checklist
A Design Graph is complete when all of the following hold:
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.
- 4d ago Changed · +3 lines fd841a71739d
- 9d ago First seen · 99 lines · 64 tokens per session scan A cf3e555ec31a
design-graph is a skill published in the GitHub repository widnyana/eyay-toolkits (7 stars, last pushed 6d ago), licensed MIT. It adds 64 tokens to every session and 1,023 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 2026-08-31.
Other skills, from other repositories
ash-framework
Ash Framework — resources, actions, policies, aggregates, calculations, AshPhoenix.Form, LiveView, migrations. Use when generating resources via mix ash.codegen, editing changes, checks, types, validations, or domain code interfaces.
liveview-patterns
Build LiveView: async data (assignasync), PubSub (check connected?), phx-change events, form components/modals/uploads, streams for lists, livepatch. Use when handling interactions, debugging events, or tracking Presence.
deploy
Elixir/Phoenix deployment patterns — Dockerfile, fly.toml, runtime.exs, mix release, rel/ overlays. Use when configuring Fly.io, Docker, CI/CD, health checks, or production migrations.
oban
Oban job processing — workers, perform/1 (OSS) and process/1 (Pro), queues, cron, retries, unique jobs, idempotency, Oban Pro (Workflow, Batch, Chunk, Smart Engine), Testing. Use when writing Oban workers, queue config, or debugging jobs.
tidewave-integration
Tidewave MCP runtime tools — debugging, smoke testing, live state inspection, SQL queries, hex docs. Use when evaluating code in a running Phoenix app.
perf
Analyze Elixir/Phoenix performance — N+1 queries, assign bloat, ecto optimization, genserver bottlenecks. Use when slowness, timeouts, or high memory reported.