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/luanmorenommaciel/agentspec/designgit clone --depth 1 https://github.com/luanmorenommaciel/agentspecWrote 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/luanmorenommaciel/agentspec/design)<a href="https://agentmods.dev/commands/luanmorenommaciel/agentspec/design"><img src="https://agentmods.dev/badge/commands/luanmorenommaciel/agentspec/design.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 | $0.00012 | $0.01144 |
| Opus 5 | $0.00006 | $0.00572 |
| Sonnet 5 | $0.00002 | $0.00229 |
| Haiku 4.5 | $0.00001 | $0.00114 |
Grade A, and why
design 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Command
Create architecture and technical specification in one pass (Phase 2)
Usage
/design <define-file> [--judge[=MODE]]
Examples
/design .claude/sdd/features/DEFINE_NOTIFICATION_SYSTEM.md
/design DEFINE_USER_AUTH.md
/design .claude/sdd/features/DEFINE_SEARCH_API.md
# With cross-model judge for architectural soundness (opt-in)
/design DEFINE_AUTH.md --judge # advisory, default openai/gpt-4o
/design DEFINE_AUTH.md --judge=strict # gated — FAIL blocks completion
/design DEFINE_AUTH.md --judge=openai/o3 # custom model (advisory)
/design DEFINE_AUTH.md --judge=strict:openai/gpt-4o # gated + custom model
Overview
This is Phase 2 of the 5-phase AgentSpec workflow:
Phase 0: /brainstorm → .claude/sdd/features/BRAINSTORM_{FEATURE}.md (optional)
Phase 1: /define → .claude/sdd/features/DEFINE_{FEATURE}.md
Phase 2: /design → .claude/sdd/features/DESIGN_{FEATURE}.md (THIS COMMAND)
Phase 3: /build → Code + .claude/sdd/reports/BUILD_REPORT_{FEATURE}.md
Phase 4: /ship → .claude/sdd/archive/{FEATURE}/SHIPPED_{DATE}.md
The /design command combines what used to be Plan + Spec + ADRs into a single document with architecture decisions inline.
What Happens
- Load the skill — read
.claude/skills/sdd-design/SKILL.md. It owns the Phase 2 methodology: KB-first resolution, the architecture and inline-ADR steps, the agent-matched file manifest, code patterns, the testing strategy, and the quality gate. - Follow it end to end (Steps 1–7) for the given
<define-file>. - Produce the DESIGN document at
.claude/sdd/features/DESIGN_{FEATURE_NAME}.md, update the DEFINE status per.claude/sdd/architecture/WORKFLOW_CONTRACTS.yaml, and suggest/buildas the next step.
The judge pass below is command-only — it runs after the skill's Step 7, and only when --judge is passed.
Step 8: Optional Judge Pass (--judge)
Runs only if the user invoked with --judge[=MODE]. Cross-model second
opinion on the design, focused on architectural soundness — hallucinated
APIs, wrong invariants, unsafe defaults, missing edge cases, unjustified
decisions.
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 · 115 lines · 12 tokens per session scan A e4daecbf064b
design is a command published in the GitHub repository luanmorenommaciel/agentspec (244 stars, last pushed yesterday), licensed MIT. It adds 12 tokens to every session and 1,144 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 2026-09-01.
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.