Borrowing it
Nothing to install: this file belongs to litestar-org/litestar-fullstack-inertia. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/litestar-org/litestar-fullstack-inertia/main/.claude/commands/prd.mdgit clone --depth 1 https://github.com/litestar-org/litestar-fullstack-inertiaWrote 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/commands/litestar-org/litestar-fullstack-inertia/prd)<a href="https://agentmods.dev/commands/litestar-org/litestar-fullstack-inertia/prd"><img src="https://agentmods.dev/badge/commands/litestar-org/litestar-fullstack-inertia/prd/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/litestar-org/litestar-fullstack-inertia/prd"><img src="https://agentmods.dev/badge/commands/litestar-org/litestar-fullstack-inertia/prd.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00010 | $0.02093 |
| Opus 5.5 | $0.00004 | $0.00837 |
| Sonnet 5.5 | $0.00002 | $0.00419 |
| Haiku 4.5 | $0.00001 | $0.00209 |
Grade A, and why
prd 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 1mo 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 — 336 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Intelligent PRD Creation Workflow
You are creating a Product Requirements Document for: $ARGUMENTS
Intelligence Layer (ACTIVATE FIRST)
Before starting checkpoints:
- Read MCP Strategy: Load
.claude/mcp-strategy.mdfor tool selection - Learn from Codebase: Read 3-5 similar implementations
- Assess Complexity: Determine simple/medium/complex
- Adapt Workflow: Adjust checkpoint depth
Critical Rules
- CONTEXT FIRST - Read existing patterns before planning
- NO CODE MODIFICATION - Planning only (specs/ directory only)
- PATTERN LEARNING - Identify 3-5 similar features
- ADAPTIVE DEPTH - Simple=6, Medium=8, Complex=10+ checkpoints
- RESEARCH GROUNDED - Minimum 2000+ words research
- COMPREHENSIVE PRD - Minimum 3200+ words
Checkpoint 0: Intelligence Bootstrap
Load project intelligence:
- Read
CLAUDE.md(orAGENTS.md) - Read
specs/guides/patterns/README.md - Read
.claude/mcp-strategy.md
Learn from existing implementations:
For this Litestar project, search in:
app/domain/for backend patternsresources/pages/for frontend patternsapp/db/models/for data model patterns
Assess complexity:
- Simple: Single file, CRUD, config change → 6 checkpoints
- Medium: New controller/service, 2-3 files → 8 checkpoints
- Complex: New domain module, schema changes, 5+ files → 10+ checkpoints
Output: "✓ Checkpoint 0 complete - Complexity: [level], Checkpoints: [count]"
Checkpoint 1: Pattern Recognition
Identify similar implementations:
# Search for related patterns in backend
grep -r "class.*Controller" app/domain/ | head -5
grep -r "class.*Service" app/domain/ | head -5
# Search for related patterns in frontend
ls resources/pages/
Read at least 3 similar files and document:
## Similar Implementations
1. `app/domain/{feature}/controllers.py` - Description
2. `app/domain/{feature}/services.py` - Description
3. `resources/pages/{feature}/` - Description
## Patterns Observed
- Controller structure: Litestar controller with route decorators
- Service pattern: Extends SQLAlchemyAsyncRepositoryService
- Inertia integration: Returns Inertia responses with typed props
- Repository pattern: advanced-alchemy repositories
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.
- 1mo ago First seen · 336 lines · 10 tokens per session scan A c6acd1ebc95e
prd is a command published in the GitHub repository litestar-org/litestar-fullstack-inertia (44 stars, last pushed yesterday), licensed MIT. It adds 10 tokens to every session and 2,093 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-09-03.
Other commands, from other repositories
greet
Generate contextual agent greeting using GreetingBuilder infrastructure.
manager
CRUD command router for managing SYNAPSE domains, rules, and star-commands.
add-rule
Adds a new rule to an existing SYNAPSE domain file.
toggle-domain
Toggles a SYNAPSE domain between active and inactive in the manifest.
codebase
⚡⚡⚡ Scan & analyze the codebase.
video
Create a design based on video.