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 commands/cafreeman/foundry-mcp/foundry_create_specgit clone --depth 1 https://github.com/cafreeman/foundry-mcpWrote 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/cafreeman/foundry-mcp/foundry_create_spec)<a href="https://agentmods.dev/commands/cafreeman/foundry-mcp/foundry_create_spec"><img src="https://agentmods.dev/badge/commands/cafreeman/foundry-mcp/foundry_create_spec.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 | $0.00000 | $0.01603 |
| Opus 5 | $0.00000 | $0.00801 |
| Sonnet 5 | $0.00000 | $0.00321 |
| Haiku 4.5 | $0.00000 | $0.00160 |
Grade A, and why
foundry_create_spec 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 3d 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 — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Spec With Foundry
Overview
Create a comprehensive feature specification with detailed implementation guidance through collaborative design process.
Context Gathering & Project Discovery
Project Foundation Analysis:
- Load Project Context: Review project vision, tech stack, and summary to understand domain and constraints
- Existing Spec Review: List current specs to avoid duplication and ensure consistent naming patterns
- Feature Scope Validation: Confirm proposed feature aligns with project vision and technical architecture
Duplicate Prevention & Naming:
- Scan existing spec names and feature areas to avoid conflicts or overlaps
- Ensure new feature name follows project conventions and semantic clarity
- Validate that feature scope is appropriately focused and doesn't duplicate existing functionality
Comprehensive Feature Definition Process
Phase 1: Feature Discovery & Requirements
Problem Statement & User Value:
- What specific user pain point or business need does this feature address?
- How do users currently handle this need, and what are the limitations?
- What would success look like from both user and business perspectives?
- How does this feature support the overall project vision and roadmap?
User Stories & Workflows:
- Who are the primary users of this feature and what are their technical skill levels?
- What are the key user workflows and interaction patterns?
- What are the most important requirements from a user experience perspective?
- How will users discover, learn, and adopt this feature?
Technical Requirements & Constraints:
- How does this feature integrate with existing system architecture?
- What are the performance, security, or compliance requirements?
- Are there specific technology or platform constraints to consider?
- What external dependencies or third-party integrations are needed?
Phase 2: Technical Design & Planning
Architecture & Integration:
- How does this feature connect to existing components and data models?
- What new APIs, database changes, or infrastructure components are needed?
- How will this feature handle errors, edge cases, and recovery scenarios?
- What are the scalability and maintenance considerations?
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.
- 3d ago First seen · 194 lines · 0 tokens per session scan A aa089d3a718a
foundry_create_spec is a command published in the GitHub repository cafreeman/foundry-mcp (4 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,603 tokens. 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
git
Git operations with intelligent commit messages and workflow optimization.
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
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.