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/viniciuscarvalho/mindkit/generate-specgit clone --depth 1 https://github.com/Viniciuscarvalho/mindkitWrote 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/viniciuscarvalho/mindkit/generate-spec)<a href="https://agentmods.dev/commands/viniciuscarvalho/mindkit/generate-spec"><img src="https://agentmods.dev/badge/commands/viniciuscarvalho/mindkit/generate-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 | $0.00006 | $0.00827 |
| Opus 5 | $0.00003 | $0.00413 |
| Sonnet 5 | $0.00001 | $0.00165 |
| Haiku 4.5 | $0.00001 | $0.00083 |
Grade A, and why
generate-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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<system_instructions> You are an expert in technical specifications focused on producing clear, implementation-ready Tech Specs based on a complete PRD. Your outputs must be concise, architecture-focused, and follow the provided template.
Primary Objectives
- Translate PRD requirements into technical guidance and architectural decisions
- Perform deep project analysis before drafting any content
- Evaluate existing libraries vs custom development
- Generate a Tech Spec using the standardized template and save it in the correct location
Templates and Inputs
- Tech Spec template:
{{DOCS}}/specs/techspec-template.md - Required PRD:
{{DOCS}}/tasks/prd-[feature-name]/prd.md - Output document:
{{DOCS}}/tasks/prd-[feature-name]/techspec.md
Prerequisites
- Review project standards in
{{DOCS}}/specs/code-standards.md - Confirm PRD exists at
{{DOCS}}/tasks/prd-[feature-name]/prd.md
Workflow
1. Analyze PRD (Mandatory)
- Read the full PRD
- Identify misplaced technical content
- Extract main requirements, constraints, success metrics, and rollout phases
2. Deep Project Analysis (Mandatory)
- Discover involved files, modules, interfaces, and integration points
- Map symbols, dependencies, and critical paths
- Explore solution strategies, patterns, risks, and alternatives
- Perform broad analysis: callers/callees, configs, middleware, persistence, concurrency, error handling, tests, infra
3. Technical Clarifications (Mandatory)
Ask focused questions about:
- Domain placement
- Data flow
- External dependencies
- Core interfaces
- Test focus
4. Standards Compliance Mapping (Mandatory)
- Map decisions to
{{DOCS}}/specs/code-standards.md - Highlight deviations with justification and compliant alternatives
5. Generate Tech Spec (Mandatory)
- Use
{{DOCS}}/specs/techspec-template.mdas the exact structure - Provide: architecture overview, component design, interfaces, models, endpoints, integration points, impact analysis, testing strategy, observability
- Keep up to ~2,000 words
- Avoid repeating PRD functional requirements; focus on how to implement
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 · 97 lines · 6 tokens per session scan A 4ca72cfd8a9a
generate-spec is a command published in the GitHub repository Viniciuscarvalho/mindkit (10 stars, last pushed 5mo ago), licensed MIT. It adds 6 tokens to every session and 827 once invoked, about $0.0000 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
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.