cc-sdd is a spec-driven development workflow for coding agents: it turns approved software specifications into requirements, designs, task plans, and extended autonomous implementation. Developers use it across several AI coding agents, with independent review and task-level continuation for long-running work. The catalogue entries provide commands, skills, agents, and instructions for using this workflow.
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 skills add gotalab/cc-sdd --skill kiro-validate-designgit clone --depth 1 https://github.com/gotalab/cc-sddWrote 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/skills/gotalab/cc-sdd/kiro-validate-design)<a href="https://agentmods.dev/skills/gotalab/cc-sdd/kiro-validate-design"><img src="https://agentmods.dev/badge/skills/gotalab/cc-sdd/kiro-validate-design/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/skills/gotalab/cc-sdd/kiro-validate-design"><img src="https://agentmods.dev/badge/skills/gotalab/cc-sdd/kiro-validate-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 96 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00013 | $0.01088 |
| Opus 5.5 | $0.00005 | $0.00435 |
| Sonnet 5.5 | $0.00003 | $0.00218 |
| Haiku 4.5 | $0.00001 | $0.00109 |
Grade A, and why
kiro-validate-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 1mo 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.
Copies of this mod
3 near-identical copies found in the catalogue:
- kiro-validate-design — 100% identical, 4 lines differ
- kiro-validate-design — 95% identical, 20 lines differ
- kiro-validate-design — 88% identical, 71 lines differ
How it starts
The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Technical Design Validation
<background_information>
- Mission: Conduct interactive quality review of technical design to ensure readiness for implementation
- Success Criteria:
- Critical issues identified (maximum 3 most important concerns)
- Balanced assessment with strengths recognized
- Clear GO/NO-GO decision with rationale
- Actionable feedback for improvements if needed </background_information>
Execution Steps
- Gather Context:
- Read
{{KIRO_DIR}}/specs/$1/spec.jsonfor language and metadata - Read
{{KIRO_DIR}}/specs/$1/requirements.mdfor requirements - Read
{{KIRO_DIR}}/specs/$1/design.mdfor design document - Core steering context:
product.md,tech.md,structure.md - Additional steering files only when directly relevant to architecture boundaries, integrations, runtime prerequisites, domain rules, security/performance constraints, or team conventions that affect implementation readiness
- Use explicitly requested skills and task-relevant local skills/playbooks, including design, accessibility, and UX. Select by description and read only needed guidance, even for small tasks; preserve required checks and host/project rules.
- Read
Parallel Research
The following research areas are independent and can be executed in parallel:
- Context & rules loading: Spec documents, core steering, task-relevant extra steering, relevant local agent skills/playbooks, and
rules/design-review.mdfrom this skill's directory for review criteria - Codebase pattern survey: Gather existing architecture patterns, naming conventions, and component structure from the codebase to use as reference during review
If multi-agent is enabled, spawn sub-agents for each area above. Otherwise execute sequentially.
After all parallel research completes, synthesize findings for review.
- Execute Design Review:
- Reference conversation history when available: leverage prior requirements discussion and user's stated design intent
- Follow design-review.md process: Analysis → Critical Issues → Strengths → GO/NO-GO
- Limit to 3 most important concerns
- Engage interactively with user — ask clarifying questions, propose alternatives
- Use language specified in spec.json for output
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.
- 1mo ago Changed 187bb98b3cbd
- 1mo ago First seen · 104 lines · 13 tokens per session scan A cafff16570c0
kiro-validate-design is a skill published in the GitHub repository gotalab/cc-sdd (3,745 stars, last pushed 5d ago), licensed MIT. It adds 13 tokens to every session and 1,088 once invoked, about $0.0001 per session on Opus 5.5. 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.
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pr-feedback-ingest
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review-hard
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atom-audit-fleet
Audit every atom in parallel against the component guidelines, one worker per small group, merging rows into one ATOMAUDIT.md table (orchestrator-workers variant of atom-audit). Use when the atom count is 6 or more and COMPONENTGUIDELINES.md exists. Do not use below 6 atoms (use atom-audit single-agent), without…
verify-against-rubric-fleet
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graphql-contract-review
Review a GraphQL schema and a Backend-for-Frontend (BFF) contract BEFORE implementation against a GraphQL checklist (nullability, N+1, cost limits, federation, BFF thinness). Use when designing or modifying a GraphQL schema, a federated subgraph, or a BFF contract. Do not use for a REST contract (use…