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/rmjosea/agentic-sdlc-kit/create-skillnpx skills add rmjosea/agentic-sdlc-kit --skill create-skillgit clone --depth 1 https://github.com/rmjosea/agentic-sdlc-kitWhat 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 | $0.00071 | $0.00723 |
| Opus 5 | $0.00036 | $0.00362 |
| Sonnet 5 | $0.00014 | $0.00145 |
| Haiku 4.5 | $0.00007 | $0.00072 |
Grade A, and why
create-skill 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 2d 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create a High-Quality Agent Skill
Create the smallest reusable procedure that reliably changes agent behavior.
Select the mode
createorrevise: change files only after responsibility and boundaries are confirmed; report files changed and validation results.evaluate: do not mutate by default; report evidence-backed findings by severity, non-findings worth preserving, andapproved,changes-required, orblocked.benchmark: define positive and adjacent-negative prompts, quality rubrics, fresh-session procedure, baseline without the skill, and comparable results.
Understand with examples
- Gather two or more realistic requests that should use the skill.
- Gather requests that look similar but should not use it.
- Identify the repeated procedure, non-obvious knowledge, and failure modes.
- Ask one material question at a time using
AGENTS.md. - Confirm the skill's responsibility and boundaries before creating files.
Do not create a skill for one-off context, generic intelligence the model
already has, or durable repository rules that belong in AGENTS.md.
Design progressive disclosure
Use three levels:
nameanddescriptionfor discovery;- concise
SKILL.mdinstructions for activation; references/,scripts/, andassets/loaded or executed only as needed.
Keep SKILL.md preferably under 200 lines and always under 500 lines. Keep
references one level deep. State the exact condition for reading each resource.
Do not duplicate information between files.
Choose resources
scripts/: deterministic or repeatedly rewritten operations; execute tests.references/: focused knowledge needed only in specific conditions.assets/: templates or output resources not intended as instructions.
Create no directory or file without a concrete use. Do not add auxiliary README, changelog, installation guide, or process diary inside a skill.
Write metadata
Use YAML frontmatter containing at least:
---
name: verb-led-name
description: What the skill does. Use when ... Include concrete triggers.
---
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.
- 2d ago First seen · 94 lines · 71 tokens per session scan A c3c2abb33f77
create-skill is a skill published in the GitHub repository rmjosea/agentic-sdlc-kit (2 stars, last pushed 1mo ago), licensed MIT. It adds 71 tokens to every session and 723 once invoked, about $0.0004 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 2026-08-31.
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