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/pangon/ai-sdlc-framework/sdlc-initnpx skills add pangon/ai-sdlc-framework --skill sdlc-initgit clone --depth 1 https://github.com/pangon/ai-sdlc-frameworkWrote 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/pangon/ai-sdlc-framework/sdlc-init)<a href="https://agentmods.dev/skills/pangon/ai-sdlc-framework/sdlc-init"><img src="https://agentmods.dev/badge/skills/pangon/ai-sdlc-framework/sdlc-init.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 | $0.00050 | $0.00431 |
| Opus 5 | $0.00025 | $0.00216 |
| Sonnet 5 | $0.00010 | $0.00086 |
| Haiku 4.5 | $0.00005 | $0.00043 |
Grade A, and why
SDLC-init 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 5d 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
Instructions
You are guiding the user through the initial setup of a new project based on the AI SDLC Framework, interactively configuring the project description and metadata.
Workflow
- Read the current
## Project Overviewsection inCLAUDE.md. If it already contains a real description (not just placeholder text), show it to the user and ask whether they want to replace or refine it. - Ask the user to describe their project: what it does and what problem it solves. As an alternative, offer to auto-generate a summary from the repository name. Do not ask for technology stack or architectural details — those belong in later phases.
- Write a concise project description optimized for AI agent consumption. Replace the entire
## Project Overviewsection content (everything between the## Project Overviewheading and the### Current Statesubheading), not just the placeholder comment. - Update
### Current Statefollowing the Current State Protocol inCLAUDE.md:- If
**Phase**:isNot initialized, rewrite the section to**Phase**: Specificationplus a**Summary**:noting that the project has been initialized and Specification elicitation has not started yet. - If the project had already advanced past initialization (re-configuration of an existing project), keep the existing
**Phase**:and status lines — update only the**Summary**:if the new description makes it inaccurate.
- If
- Confirm — show the user the final text that was written.
Rules
- If the user wants to skip, leave the section unchanged.
- Write content optimized for AI agent consumption: clear, structured, factual.
- Do not modify any file structure, templates, or procedures — only fill in project-specific content.
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.
- 5d ago First seen · 25 lines · 50 tokens per session scan A 8eec6e031e96
SDLC-init is a skill published in the GitHub repository pangon/ai-sdlc-framework (124 stars, last pushed 12d ago), licensed Apache-2.0. It adds 50 tokens to every session and 431 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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