Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Sahib-Sawhney-WH/sahibs-claude-plugin-marketplacenpx agentmods add commands/sahib-sawhney-wh/sahibs-claude-plugin-marketplace/projectWrote 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/sahib-sawhney-wh/sahibs-claude-plugin-marketplace/project)<a href="https://agentmods.dev/commands/sahib-sawhney-wh/sahibs-claude-plugin-marketplace/project"><img src="https://agentmods.dev/badge/commands/sahib-sawhney-wh/sahibs-claude-plugin-marketplace/project/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/sahib-sawhney-wh/sahibs-claude-plugin-marketplace/project"><img src="https://agentmods.dev/badge/commands/sahib-sawhney-wh/sahibs-claude-plugin-marketplace/project.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 | $0.00956 |
| Opus 5 | $0.00005 | $0.00478 |
| Sonnet 5 | $0.00002 | $0.00191 |
| Haiku 4.5 | $0.00001 | $0.00096 |
Grade A, and why
project 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 12d 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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DAPR Multi-Service Project
Initialize a complete multi-service DAPR project with shared components and configuration.
Behavior
When the user runs /dapr:project:
-
Create Project Structure
- Root project directory
- Shared components directory
- Individual service directories
- Shared infrastructure
-
Generate Shared Configuration
dapr.yamlfor multi-app mode- Shared component YAML files
- Resiliency policies
- Observability configuration
-
Create Service Templates
- FastAPI service template
- Dockerfile for each service
- Service-specific components
Arguments
| Argument | Description |
|---|---|
<name> |
Project name (required) |
--services |
Comma-separated service names |
--template |
Project template (ecommerce, iot, saga) |
Examples
Basic Multi-Service Project
/dapr:project my-app --services "order-service,inventory-service,payment-service"
E-Commerce Template
/dapr:project shop --template ecommerce
IoT Event Processing
/dapr:project iot-hub --template iot
Generated Structure
my-app/
├── dapr.yaml # Multi-app run configuration
├── components/ # Shared DAPR components
│ ├── statestore.yaml
│ ├── pubsub.yaml
│ ├── secretstore.yaml
│ └── resiliency.yaml
├── services/
│ ├── order-service/
│ │ ├── src/
│ │ │ └── main.py
│ │ ├── Dockerfile
│ │ ├── requirements.txt
│ │ └── components/ # Service-specific components
│ ├── inventory-service/
│ │ └── ...
│ └── payment-service/
│ └── ...
├── infrastructure/
│ ├── docker-compose.yaml # Local development
│ ├── bicep/ # Azure IaC
│ │ └── main.bicep
│ └── kubernetes/ # K8s manifests
│ └── deployment.yaml
├── tests/
│ ├── e2e/
│ └── integration/
└── README.md
dapr.yaml (Multi-App Mode)
version: 1
apps:
- appId: order-service
appDirPath: ./services/order-service
appPort: 8001
command: ["python", "-m", "uvicorn", "src.main:app", "--host", "0.0.0.0", "--port", "8001"]
- appId: inventory-service
appDirPath: ./services/inventory-service
appPort: 8002
command: ["python", "-m", "uvicorn", "src.main:app", "--host", "0.0.0.0", "--port", "8002"]
- appId: payment-service
appDirPath: ./services/payment-service
appPort: 8003
command: ["python", "-m", "uvicorn", "src.main:app", "--host", "0.0.0.0", "--port", "8003"]
common:
resourcesPath: ./components
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.
- 12d ago First seen · 145 lines · 10 tokens per session scan A 5ae96524c692
project is a command published in the GitHub repository Sahib-Sawhney-WH/sahibs-claude-plugin-marketplace (4 stars, last pushed 8mo ago), licensed MIT. It adds 10 tokens to every session and 956 once invoked, about $0.0001 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 commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.