Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/jmylchreest/aidenpx agentmods add skills/jmylchreest/aide/designWrote 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/jmylchreest/aide/design)<a href="https://agentmods.dev/skills/jmylchreest/aide/design"><img src="https://agentmods.dev/badge/skills/jmylchreest/aide/design/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/jmylchreest/aide/design"><img src="https://agentmods.dev/badge/skills/jmylchreest/aide/design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00008 | $0.01431 |
| Opus 5 | $0.00004 | $0.00715 |
| Sonnet 5 | $0.00002 | $0.00286 |
| Haiku 4.5 | $0.00001 | $0.00143 |
Grade A, and why
design 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.
How it starts
The opening of the file, as written. The whole thing — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Mode
Recommended model tier: smart (opus) - this skill requires complex reasoning
Output a technical design specification that downstream SDLC stages can consume.
Purpose
Create a structured design document that defines:
- What to build (interfaces, types, components)
- How it fits together (data flow, interactions)
- Why key decisions were made (rationale)
- Success criteria (acceptance criteria for TEST stage)
Workflow
Step 1: Understand the Request
Read the request and identify:
- Core functionality required
- Constraints (tech stack, patterns, performance)
- Integration points with existing code
Step 2: Explore the Codebase
Use search tools to understand existing patterns:
- Use
Grepfor similar patterns, interfaces, types - Use
Globfor relevant files - Use
mcp__plugin_aide_aide__decision_listto review all decisions - Use
mcp__plugin_aide_aide__decision_getwith the relevant topic to check specific decisions
Step 3: Define Interfaces
Define the public API/interfaces first:
// Example TypeScript interface
interface UserService {
createUser(data: CreateUserInput): Promise<User>;
getUser(id: string): Promise<User | null>;
updateUser(id: string, data: UpdateUserInput): Promise<User>;
}
interface CreateUserInput {
email: string;
name: string;
}
// Example Go interface
type UserService interface {
CreateUser(ctx context.Context, input CreateUserInput) (*User, error)
GetUser(ctx context.Context, id string) (*User, error)
UpdateUser(ctx context.Context, id string, input UpdateUserInput) (*User, error)
}
Step 4: Document Data Flow
Describe how components interact:
Request → Controller → Service → Repository → Database
↓
Validator
↓
Error Handler → Response
Step 5: Record Key Decisions
Store architectural decisions for future reference:
./.aide/bin/aide decision set "<feature>-storage" "PostgreSQL with JSONB for metadata" \
--rationale="Need flexible schema for user preferences" --by="<git-username>"
./.aide/bin/aide decision set "<feature>-auth" "JWT with refresh tokens" \
--rationale="Stateless auth, mobile client support" --by="<git-username>"
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 · 223 lines · 8 tokens per session scan A e40351bef7d3
design is a skill published in the GitHub repository jmylchreest/aide (17 stars, last pushed 2d ago), licensed MIT. It adds 8 tokens to every session and 1,431 once invoked, about $0.0000 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.
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