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-debuggit 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-debug)<a href="https://agentmods.dev/skills/gotalab/cc-sdd/kiro-debug"><img src="https://agentmods.dev/badge/skills/gotalab/cc-sdd/kiro-debug/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-debug"><img src="https://agentmods.dev/badge/skills/gotalab/cc-sdd/kiro-debug.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00033 | $0.01194 |
| Opus 5.5 | $0.00013 | $0.00478 |
| Sonnet 5.5 | $0.00007 | $0.00239 |
| Haiku 4.5 | $0.00003 | $0.00119 |
Grade A, and why
kiro-debug 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
2 near-identical copies found in the catalogue:
- kiro-debug — 100% identical, 0 lines differ
- kiro-debug — 86% identical, 8 lines differ
How it starts
The opening of the file, as written. The whole thing — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
kiro-debug
<background_information> This skill is for fresh-context root cause investigation. It combines local evidence, runtime/config inspection, and external documentation or issue research when available. It is not a patch generator for guess-first debugging. </background_information>
- Implementer reports
BLOCKED - Reviewer rejection repeats after remediation
- Validation fails unexpectedly
- A task appears to conflict with runtime or platform reality
- The same failure survives more than one attempted fix
Do not use this skill to speculate about fixes before gathering evidence.
Inputs
Provide:
- Exact failure symptom or blocker statement
- Error messages, stack trace, and failing command output
- Current
git diffor summary of uncommitted failed changes - Task brief: what was being built
- Reviewer feedback, if the failure came from review rejection
- Relevant spec file paths (
requirements.md,design.md) - Relevant requirement/design section numbers
- Relevant
## Implementation Notes - Runtime or environment constraints already known
Outputs
Return:
ROOT_CAUSECATEGORYFIX_PLANVERIFICATIONNEXT_ACTION: RETRY_TASK | BLOCK_TASK | STOP_FOR_HUMANCONFIDENCE: HIGH | MEDIUM | LOWNOTES
Use the language specified in spec.json.
Method
1. Read the Error Carefully
Extract:
- Exact error text
- Stack trace or failure location
- The command that produced the failure
- Whether the failure is deterministic or intermittent
2. Inspect Local Runtime and Repository State
Inspect the repository for local evidence:
package.json,pyproject.toml,go.mod,Makefile,README*- Build config
tsconfigor equivalent language/runtime config- Runtime-specific config
- Dependency versions and scripts
- Relevant changed files from
git diff
3. Search the Web if Available
If web access is available, search:
- The exact error message
- The technology + symptom combination
- Official documentation
- Version-specific issue trackers or migration notes
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 First seen · 153 lines · 33 tokens per session scan A c5ce75a0f76d
kiro-debug is a skill published in the GitHub repository gotalab/cc-sdd (3,731 stars, last pushed 9d ago), licensed MIT. It adds 33 tokens to every session and 1,194 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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