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/voro6yov/spec-driven-development/generate-applicationnpx skills add voro6yov/spec-driven-development --skill generate-applicationgit clone --depth 1 https://github.com/voro6yov/spec-driven-developmentWrote 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/voro6yov/spec-driven-development/generate-application)<a href="https://agentmods.dev/skills/voro6yov/spec-driven-development/generate-application"><img src="https://agentmods.dev/badge/skills/voro6yov/spec-driven-development/generate-application.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 | $0.00049 | $0.00649 |
| Opus 5 | $0.00024 | $0.00324 |
| Sonnet 5 | $0.00010 | $0.00130 |
| Haiku 4.5 | $0.00005 | $0.00065 |
Grade A, and why
generate-application 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an application end-to-end orchestrator. Generate the application spec and the application code for the aggregate diagram in $ARGUMENTS by chaining two orchestrator agents sequentially. Each agent runs the heavy fan-out in its own isolated context and returns only a one-line report — this umbrella stays lean.
This is a TWO-PHASE skill
This skill is not complete until both phases finish:
- Phase 1 —
application-spec:specs-generatoragent (writescommands.specs.md,queries.specs.md, andservices.md) - Phase 2 —
application-spec:code-generatoragent (scaffolds the application/infrastructure packages, implements services, exceptions, settings, the commands and queries application services, and writes integration tests)
Phase 1 ends with its own confirmation line such as Application spec generation complete for .... That message refers to Phase 1 only. It is not the end of this skill — you MUST continue to Phase 2 immediately. The single most common failure mode of this skill is stopping after Phase 1; do not do that.
Inputs
$ARGUMENTS— the path to the aggregate's Mermaid class diagram (<dir>/<stem>.md).
All artifacts produced by Phase 1 land in <dir>/<stem>.application/ per spec-core:naming-conventions; Phase 2 reads them from there. Sibling diagrams (<commands_diagram>, <queries_diagram>) are derived internally by each spawned agent; this umbrella only forwards the domain diagram path.
Workflow
Spawn each agent in its own message (via the Agent tool) and wait for it to complete before spawning the next. Do not collapse them into a single message.
Step 1 of 2 — Generate the application spec
Spawn the application-spec:specs-generator agent with prompt $ARGUMENTS.
Failure handling: if the agent reports a failure, abort the workflow and emit an ERROR: line naming the failure. Only in that case do you stop before Step 2.
Success handling: if the agent returns its normal "Application spec generation complete" confirmation (or any non-error completion), proceed immediately to Step 2 of 2 in your very next message. Do not summarize, do not pause, do not ask for confirmation — Phase 2 is mandatory and the user has already authorized it by invoking this umbrella.
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 · 46 lines · 0 tokens per session scan A 35714fc3792c
generate-application is a skill published in the GitHub repository voro6yov/spec-driven-development (4 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 49 tokens to every session and 649 once invoked, about $0.0002 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.
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…