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/koroqe/claude-code-sdlc/sdlc-quicknpx skills add Koroqe/claude-code-sdlc --skill sdlc-quickgit clone --depth 1 https://github.com/Koroqe/claude-code-sdlcWrote 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/koroqe/claude-code-sdlc/sdlc-quick)<a href="https://agentmods.dev/skills/koroqe/claude-code-sdlc/sdlc-quick"><img src="https://agentmods.dev/badge/skills/koroqe/claude-code-sdlc/sdlc-quick.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 | $0.00053 | $0.02117 |
| Opus 5 | $0.00026 | $0.01059 |
| Sonnet 5 | $0.00011 | $0.00423 |
| Haiku 4.5 | $0.00005 | $0.00212 |
Grade A, and why
sdlc-quick 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.
How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Command: SDLC Quick (Override)
This is an override entry point, not the primary path. The primary, autonomous path is Phase 0: Triage inside skills/develop-feature/SKILL.md — read it first if you have not already — which classifies every request into fast/quick/full on its own, with no human involvement. /sdlc-quick exists only so a developer can explicitly overrule that verdict and assert quick tier directly. It is never invoked by the pipeline itself, and no run needs it in order to complete (NFR-2) — it is a human-typed escape hatch, not a step in the normal flow.
Arguments
The change to make is $feature (also available as $ARGUMENTS). When it is empty, ask the user what to build before doing anything else — do NOT infer a change from surrounding context.
Literal-token activation only (FR-6.3)
This skill activates ONLY because it was literally invoked as /sdlc-quick <description> — an actually-invoked slash command, the same literal-token discipline already governing no-changelog and every other documented flag in this harness. A request's prose containing a word like "quick," "fast," "small," or "trivial," submitted as ordinary conversational text rather than this literal command, does NOT activate this skill and MUST still be classified by Phase 0 Triage in skills/develop-feature/SKILL.md unmodified. Nothing in this file infers activation from vocabulary; only the literal token does.
What this bypasses, and what it does not (FR-6.2)
Invoking this skill skips Phase 0 Triage entirely: no estimated file set is stated as a classification input, no full-forcing/fast-tier/quick-tier signal check runs, and no tier: ... reasoning is produced or considered. The human asserts the tier; the pipeline does not compute it. The override skips classification, never the safety rails — FR-2.2's quick→full escalation rules still apply once this skill is running (see below).
Quick Tier Execution (FR-4) — run this directly against $feature
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 · 60 lines · 0 tokens per session scan A 2339ec41d50a
sdlc-quick is a skill published in the GitHub repository Koroqe/claude-code-sdlc (51 stars, last pushed 6d ago), licensed MIT. It adds 53 tokens to every session and 2,117 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…