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/djscheuf/agentic-dev-ecosystem-template/sdlc-designnpx skills add djscheuf/agentic-dev-ecosystem-template --skill sdlc-designgit clone --depth 1 https://github.com/djscheuf/agentic-dev-ecosystem-templateWrote 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/djscheuf/agentic-dev-ecosystem-template/sdlc-design)<a href="https://agentmods.dev/skills/djscheuf/agentic-dev-ecosystem-template/sdlc-design"><img src="https://agentmods.dev/badge/skills/djscheuf/agentic-dev-ecosystem-template/sdlc-design.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 | $0.00056 | $0.00282 |
| Opus 5 | $0.00028 | $0.00141 |
| Sonnet 5 | $0.00011 | $0.00056 |
| Haiku 4.5 | $0.00006 | $0.00028 |
Grade A, and why
sdlc-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 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.
What it actually says
SDLC Design Workflow
Purpose
Design a user story implementation with architecture and design patterns.
Trigger
- Starting a new feature or bug fix
- Before writing any production code
- After Requirements have been Clarified
Inputs Required
- Analysis of incoming requirements
- Relevant domain context
Workflow Steps
Step 1: Assess Current Reality
Assess Current Reality, to identify what's already in place and what needs to be built, existing ADRs, and design precedents, and architecture. using the audit-current-reality skill.
Address any verification errors before proceeding.
Step 2: Add Design Step prior to Plan
Design the stories implementation with the design-story-implementation skill, with the analysis and audit files from the previous steps.
Address any verification errors before proceeding.
Step 3: Grade the Design
grade the design based on the Design Quality Rubric using the grade-story-design skill on the design file from the previous step.
Address any verification errors before proceeding.
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 First seen · 36 lines · 56 tokens per session scan A ab8d6a275b9b
sdlc-design is a skill published in the GitHub repository djscheuf/agentic-dev-ecosystem-template (12 stars, last pushed yesterday), licensed MIT. It adds 56 tokens to every session and 282 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.
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chat-perf
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