Borrowing it
Nothing to install: this file belongs to ivo-toby/mcp-picnic. 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/ivo-toby/mcp-picnic/main/.claude/commands/minispec.constitution.mdgit clone --depth 1 https://github.com/ivo-toby/mcp-picnicWrote 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/ivo-toby/mcp-picnic/minispec.constitution)<a href="https://agentmods.dev/commands/ivo-toby/mcp-picnic/minispec.constitution"><img src="https://agentmods.dev/badge/commands/ivo-toby/mcp-picnic/minispec.constitution/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/ivo-toby/mcp-picnic/minispec.constitution"><img src="https://agentmods.dev/badge/commands/ivo-toby/mcp-picnic/minispec.constitution.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 | $0.00014 | $0.01801 |
| Opus 5 | $0.00007 | $0.00901 |
| Sonnet 5 | $0.00003 | $0.00360 |
| Haiku 4.5 | $0.00001 | $0.00180 |
Grade A, and why
minispec.constitution 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 10d 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 — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Input
$ARGUMENTS
You are helping establish the project constitution through an interactive conversation. This is NOT a form-filling exercise—it's a collaborative discussion to understand the project's values and working preferences.
Philosophy
MiniSpec constitutions serve two purposes:
- Project Principles: The non-negotiable standards for this codebase
- Pairing Preferences: How you and the AI will collaborate
Both should emerge from dialogue, not templates.
Execution Flow
Phase 1: Context Gathering
First, understand the project:
-
Check for existing constitution at
.minispec.minispec/memory/constitution.md- If exists: Read it, acknowledge what's established, ask what they want to change
- If not: Start fresh
-
Explore the codebase (if not greenfield):
- Check for README.md, existing docs, package.json/pyproject.toml
- Look for existing patterns, conventions, tech stack
- Note what you observe—this informs your questions
-
Consider user input: If
$ARGUMENTScontains guidance, incorporate it into the conversation
Phase 2: Conversational Principle Discovery
Guide the engineer through establishing principles. Ask questions, don't present forms.
Start with an opening like:
"Let's establish the principles that will guide development on this project. I'll ask you some questions to understand what matters most. Feel free to be brief—we can always refine later.
First, what's the most important quality you want to maintain in this codebase? (e.g., readability, performance, security, test coverage, simplicity)"
Then explore based on their answers:
If they mention testing:
"How strict should we be about testing? Some teams want TDD, others prefer tests after implementation. What works for you?"
If they mention code quality:
"When you say code quality, what does that look like concretely? Are there specific patterns you want to enforce or avoid?"
If they mention security:
"What's your security posture? Are there compliance requirements (SOC2, HIPAA, PCI) or is it more about general best practices?"
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.
- 10d ago First seen · 202 lines · 14 tokens per session scan A c0033993cb16
minispec.constitution is a command published in the GitHub repository ivo-toby/mcp-picnic (98 stars, last pushed 26d ago), licensed MIT. It adds 14 tokens to every session and 1,801 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 2026-08-30.
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.
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.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.