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 saajunaid/caddis-plugin --skill hldgit clone --depth 1 https://github.com/saajunaid/caddis-pluginWrote 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/saajunaid/caddis-plugin/hld)<a href="https://agentmods.dev/skills/saajunaid/caddis-plugin/hld"><img src="https://agentmods.dev/badge/skills/saajunaid/caddis-plugin/hld/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/saajunaid/caddis-plugin/hld"><img src="https://agentmods.dev/badge/skills/saajunaid/caddis-plugin/hld.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 | $0.00029 | $0.03733 |
| Opus 5.5 | $0.00012 | $0.01493 |
| Sonnet 5.5 | $0.00006 | $0.00747 |
| Haiku 4.5 | $0.00003 | $0.00373 |
Grade A, and why
hld 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 19d 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 — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
High-Level Design (HLD) Authoring Skill
Overview
This skill generates High-Level Design (HLD) documents for enterprise application fleet systems. It produces human-readable, professional architectural documentation and converts them to Confluence Storage Format XHTML using native PlantUML (<ac:structured-macro ac:name="plantuml">) diagrams with high contrast, crisp 200 DPI vector rendering, dynamic orientation, auto-wrapped labels, and clean embedded Creole legends.
Mandatory Workflow Steps
Step 1: Deep Codebase and Architectural Discovery
Analyze the target codebase, configuration files, deployment scripts, database schemas, and external integrations to discover:
- Business initiative objectives and high-level workflows.
- Physical hosting environments, virtual machines, databases, and client surfaces.
- All interconnected systems, platforms, and third-party gateways.
- External network connectivity, protocols, ports, and batch schedules.
Step 2: Component & Interface Classification Interview (Grill-Me)
MANDATORY GATE: Before generating diagrams or drafting documentation, the agent MUST present the discovered components and interfaces to the user and interview them to confirm lifecycle classifications:
- Component Classification:
- Which systems/components are Existing pre-production fleet infrastructure (
Impacted = No)? - Which systems/components are New or Impacted by this solution (
Impacted = Yes)?
- Which systems/components are Existing pre-production fleet infrastructure (
- Interface Classification:
- Which interfaces are Existing Connectivity (pre-existing enterprise links, rendered in Green
#16A34A)? - Which interfaces are New Connectivity (links created or modified for this initiative, rendered in Red
#DC2626)?
- Which interfaces are Existing Connectivity (pre-existing enterprise links, rendered in Green
- Present clear recommendations based on codebase findings, allowing the user to confirm or adjust classifications in a single interactive turn.
Step 3: Markdown Document Authoring
Draft the canonical HLD Markdown file following the standard 7-section structure. Adhere strictly to the scope rules below.
What ships with it
2 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.
- 19d ago Changed · -4 tokens per session da8f572f7a48
- 29d ago Changed · +120 lines · +4 tokens per session 39486232670d
- 1mo ago First seen · 101 lines · 29 tokens per session scan A ee9726e115af
hld is a skill published in the GitHub repository saajunaid/caddis-plugin (0 stars, last pushed 2d ago), licensed MIT. It adds 29 tokens to every session and 3,733 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 2026-09-18.
Other skills, from other repositories
goga-cookbook
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goga-review-plan
Verify execution plan completeness and correctness.
goga-define-challenge
Challenge the complete product definition before the PRD is generated.
goga-define-experience
Define the user experience required to achieve the established product goals and solve the identified problem.
goga-define-requirements
Define the product requirements that describe what the product must do to deliver the established user experience and achieve the agreed product goals.
goga-discover
Interview the user relentlessly about a decision until every branch of the design tree is resolved, then record the result as a short ADR.