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 adriannoes/awesome-agentic-ai --skill archifygit clone --depth 1 https://github.com/adriannoes/awesome-agentic-aiWrote 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/adriannoes/awesome-agentic-ai/archify)<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/archify"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/archify/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/adriannoes/awesome-agentic-ai/archify"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/archify.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 | $0.00130 | $0.02893 |
| Opus 5 | $0.00065 | $0.01447 |
| Sonnet 5 | $0.00026 | $0.00579 |
| Haiku 4.5 | $0.00013 | $0.00289 |
Grade A, and why
archify 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 9d 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.
This is a copy
88% identical to archify — 36 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Archify
Create a self-contained, interactive HTML diagram from a small typed JSON specification. Static output is the default; enable motion only when the user asks for a demo or presentation.
Fast authoring path
Use this bounded path for ordinary generation. Do not read the optional Viewer Runtime reference unless the user asks about those features.
-
Choose
architecture,workflow,sequence,dataflow, orlifecyclefrom the question. -
Read one matching schema in
schemas/,schemas/common.schema.json, and one matching JSON example inexamples/. Read only those files. Fresh authorship means new stable IDs, domain wording, and layout; use the example for field shape, not facts. When real product identity matters, querynode bin/archify.mjs brands "<name>" --json; readreferences/brand-marks.mdonly for an unknown brand with a user-provided URL. -
Artifact first: the next tool action must write the candidate. Write the candidate before inspecting renderer internals. Do not plan exact coordinates in prose. Start with one clear main path, short side branches, sparse labels, and at most 12 primary nodes. Set
meta.quality_profileto"showcase"unless the user explicitly requests a densestandardmap. Start with automatic routes and labels. Do not addvia,channelX,channelY, orlabelAtbefore a diagnostic calls for one; apply at most one diagnosed geometry control per repair. -
Validate after every candidate edit and immediately before handoff:
node bin/archify.mjs validate <type> <candidate.json> --quality showcase --jsonA receipt with only 4 artifact checks is basic validation, never showcase acceptance. A showcase pass must report all 9 artifact checks with 0 composition errors and 0 warnings. If the candidate omits or misspells the exact
meta.quality_profilefield, fix it before geometry. A passing final validation freezes the candidate: never edit it afterward. -
For a delivered HTML,
deliveris the final acceptance command:
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.
- assets/template.html 656 KB
- bin/archify.mjs 58 KB runs code
- bin/open-artifact.mjs 2.2 KB runs code
- bin/preview.mjs 23 KB runs code
- bin/visual-check.mjs 27 KB runs code
- brand-marks/catalog.json 14 KB
- brand-marks/README.md 1.4 KB
- delta/architecture-delta.mjs 71 KB runs code
- examples/agent-run.lifecycle.json 4.3 KB
- examples/agent-tool-call.workflow.json 6.2 KB
- examples/async-job-roundtrip.sequence.json 4.3 KB
- examples/brand-aware-delivery.architecture.json 3.2 KB
- examples/cache-miss-request.sequence.json 4.2 KB
- examples/checkout-platform.base.architecture.json 2.2 KB
- examples/checkout-platform.head.architecture.json 2.3 KB
- examples/deployment-release.lifecycle.json 4.2 KB
- examples/event-stream.dataflow.json 5.3 KB
- examples/incident-response.workflow.json 5.2 KB
- examples/product-analytics.dataflow.json 5.5 KB
- examples/production-deployment.architecture.json 5.3 KB
- examples/release-delivery.workflow.json 5.0 KB
- examples/web-app.architecture.json 3.7 KB
- LICENSE 1.1 KB
- package-lock.json 4.8 KB
- package.json 1.3 KB
- README.md 4.6 KB
- recipes/scenarios.mjs 27 KB runs code
- references/authoring-contract.md 10.0 KB
- references/brand-marks.md 2.1 KB
- references/delivery-contract.md 5.4 KB
- references/viewer-runtime.md 4.1 KB
- renderers/architecture/grid.mjs 2.0 KB runs code
- renderers/architecture/render-architecture.mjs 45 KB runs code
- renderers/dataflow/README.md 4.1 KB
- renderers/dataflow/render-dataflow.mjs 21 KB runs code
- renderers/lifecycle/README.md 4.8 KB
- renderers/lifecycle/render-lifecycle.mjs 25 KB runs code
- renderers/sequence/README.md 4.7 KB
- renderers/sequence/render-sequence.mjs 22 KB runs code
- renderers/shared/brand-marks.mjs 22 KB runs code
- renderers/shared/cli.mjs 10 KB runs code
- renderers/shared/desktop-readability.mjs 1.1 KB runs code
- renderers/shared/diagnostics.mjs 4.0 KB runs code
- renderers/shared/engineering-profiles.mjs 6.8 KB runs code
- renderers/shared/generated-brand-marks.mjs 160 KB runs code
- renderers/shared/generated-validators.mjs 413 KB runs code
- renderers/shared/geometry.mjs 53 KB runs code
- renderers/shared/i18n.mjs 47 KB runs code
- renderers/shared/layout-report.mjs 1015 B runs code
- renderers/shared/legend.mjs 8.4 KB runs code
- renderers/shared/output-path.mjs 10 KB runs code
- renderers/shared/repository-evidence.mjs 11 KB runs code
- renderers/shared/text-fit.mjs 2.1 KB runs code
- renderers/shared/utils.mjs 11 KB runs code
- renderers/shared/validator.mjs 3.4 KB runs code
- renderers/workflow/README.md 5.2 KB
- renderers/workflow/render-workflow.mjs 31 KB runs code
- schemas/architecture.schema.json 6.5 KB
- schemas/common.schema.json 2.7 KB
- schemas/dataflow.schema.json 6.0 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.
- 9d ago First seen · 122 lines · 130 tokens per session scan A 8532186a103b
archify is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 14d ago), licensed MIT. It adds 130 tokens to every session and 2,893 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to archify, differing in 36 lines, and is treated as a copy.
Other skills, from other repositories
conversational-ux
Design voice and conversational interfaces — dialog flows, error recovery, and persona. Use when the interface speaks and listens rather than being tapped. For graphical input collection, use form-design.
design-negotiation
Advocate for design quality, scope, and timeline with partners and leadership using evidence and shared goals. Use in the conversation itself. For the commercial vocabulary behind it, use business-design (ux-strategy).
platform-conventions
Design to iOS and Android conventions — what each OS mandates, where they diverge, and when to unify. Use when shipping native apps. For breakpoint adaptation use responsive-design; for matching competitor patterns use jakobs-law (interaction-design).
design-debt-audit
Inventory and prioritise accumulated design inconsistencies across a product. Use when drift has built up over time. For token coverage specifically use design-token-audit (designer-toolkit); for WCAG gaps use accessibility-audit (design-systems).
design-impact-reporting
Communicate design's contribution to business and user outcomes in stakeholder language. Use when reporting results upward. For choosing the metrics in the first place, use metrics-definition (ux-strategy).
motion-system
Define motion tokens — durations, easing vocabulary, and reduced-motion handling — for consistency product-wide. Use when standardising motion across a system. For crafting one specific animation, use animation-principles (interaction-design).