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-spec-quickgit 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-spec-quick)<a href="https://agentmods.dev/skills/gotalab/cc-sdd/kiro-spec-quick"><img src="https://agentmods.dev/badge/skills/gotalab/cc-sdd/kiro-spec-quick.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, 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 121 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.
- medium Excessive Agency · line 137 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 | $0.00014 | $0.01957 |
| Opus 5 | $0.00007 | $0.00979 |
| Sonnet 5 | $0.00003 | $0.00391 |
| Haiku 4.5 | $0.00001 | $0.00196 |
Grade A, and why
kiro-spec-quick 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 9d 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 — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quick Spec Generator
If --auto flag is present in $ARGUMENTS, you are in AUTOMATIC MODE.
In Automatic Mode:
- Execute ALL 4 phases in a continuous loop without stopping
- Display progress after each phase (e.g., "Phase 1/4 complete: spec initialized")
- IGNORE any "Next Step" messages from Phase 2-4 (they are for standalone usage)
- After Phase 4, run the final sanity review before exiting
- Stop ONLY after the sanity review completes or if error occurs
Core Task
Execute 4 spec phases sequentially. In automatic mode, execute all phases without stopping. In interactive mode, prompt user for approval between phases.
Before claiming quick generation is complete, run one lightweight sanity review over the generated requirements, design, and tasks. If the host supports fresh sub-agents, use one. Otherwise run the sanity review inline.
Execution Steps
Step 1: Parse Arguments and Initialize
Parse $ARGUMENTS:
- If contains
--auto: Automatic Mode (execute all 4 phases) - Otherwise: Interactive Mode (prompt at each phase)
- Extract description (remove
--autoflag if present)
Example:
"User profile with avatar upload --auto" → mode=automatic, description="User profile with avatar upload"
"User profile feature" → mode=interactive, description="User profile feature"
Display mode banner and proceed to Step 2.
Step 2: Execute Phase Loop
Execute these 4 phases in order:
Phase 1: Initialize Spec (Direct Implementation)
Core Logic:
-
Check for Brief:
- If
{{KIRO_DIR}}/specs/{feature-name}/brief.mdexists (created by/kiro-discovery), read it for discovery context (problem, approach, scope, constraints) - Use brief content as the project description instead of
$ARGUMENTS
- If
-
Generate Feature Name:
- Convert description to kebab-case
- Example: "User profile with avatar upload" → "user-profile-avatar-upload"
- Keep name concise (2-4 words ideally)
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.
- 9d ago First seen · 257 lines · 14 tokens per session scan A 0371b2f514d2
kiro-spec-quick is a skill published in the GitHub repository gotalab/cc-sdd (3,655 stars, last pushed 3mo ago), licensed MIT. It adds 14 tokens to every session and 1,957 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 skills, from other repositories
todo-for-ai-agent-runtime
Runtime integration skill for external agents connecting to Todo for AI over HTTP API Token / Agent Key, including auth, task lease, events, commit, and task logs.
implementation-plan
Define an incremental, reviewable, production-safe implementation plan for the active task and persist it as IMPLEMENTATIONPLAN.md plus a TASKSTATE.md update. Breaks work into the smallest safe slices with objective, exact scope, ordering rationale, key risks, validation approach, exit criteria, and work complexity…
slice-closure
Decide whether the current slice is ready to close, distinguishing slice completion from full task completion, then persist the result in slice notes and TASKSTATE.md as explicit reviewable closure notes. For single-slice tasks may route directly to delivery. Returns no-op when slice memory would not materially…
task-close
Perform the terminal task lifecycle transition for a finished task: verify the spec done-conditions, set TASKSTATE.md to its final closed state, and move the task folder from active/ to archive/. The symmetric counterpart to task-init and the only official way to close a whole task. Use when every slice is closed, the…
task-init
Initialize the official task folder and base task memory inside projects/ /active/YYYY-MM-DD /. Creates README.md, TASKSTATE.md, SOURCEOFTRUTH.md, DECISIONS.md, IMPLEMENTATIONPLAN.md; seeds from PROJECTCHARTER.md when present; emits a multi-repo ## Repositories section in SOURCEOFTRUTH.md when 2+ repos are provided.…
autonomous-run
Drive an approved, waved IMPLEMENTATIONPLAN through the autonomous delivery track. A thin dispatcher over the existing fleet primitives (the Workflow tool, implement-approved-slice as single writer) bounded by two human gates and a runtime governor. Runs verifiable slices with little supervision and emits PROPOSED…