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-tasksgit 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-tasks)<a href="https://agentmods.dev/skills/gotalab/cc-sdd/kiro-spec-tasks"><img src="https://agentmods.dev/badge/skills/gotalab/cc-sdd/kiro-spec-tasks/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-spec-tasks"><img src="https://agentmods.dev/badge/skills/gotalab/cc-sdd/kiro-spec-tasks.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 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 32 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 115 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 118 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 165 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 | $0.00012 | $0.02363 |
| Opus 5.5 | $0.00005 | $0.00945 |
| Sonnet 5.5 | $0.00002 | $0.00473 |
| Haiku 4.5 | $0.00001 | $0.00236 |
Grade A, and why
kiro-spec-tasks 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
1 near-identical copy found in the catalogue:
- kiro-spec-tasks — 91% identical, 34 lines differ
How it starts
The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementation Tasks Generator
<background_information>
- Success Criteria:
- All requirements mapped to specific tasks
- Tasks properly sized (1-3 hours each)
- Clear task progression with proper hierarchy
- Natural language descriptions focused on capabilities
- A lightweight task-plan sanity review confirms the task graph is executable before
tasks.mdis written </background_information>
Step 1: Load Context
Read all necessary context:
{{KIRO_DIR}}/specs/$1/spec.json,requirements.md,design.md{{KIRO_DIR}}/specs/$1/tasks.md(if exists, for merge mode)- Core steering context:
product.md,tech.md,structure.md - Additional steering files only when directly relevant to requirements coverage, design boundaries, runtime prerequisites, or team conventions that affect task executability
- 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.
Validate approvals:
- If
-yflag provided: Auto-approve requirements and design in spec.json. Tasks approval is also handled automatically in Step 4. - Otherwise: Verify both approved (stop if not, see Safety & Fallback)
- Determine sequential mode based on presence of
--sequential
Step 2: Generate Implementation Tasks
Load generation rules and template:
- Read
rules/tasks-generation.mdfrom this skill's directory for principles - If
sequentialis false: Readrules/tasks-parallel-analysis.mdfrom this skill's directory for parallel judgement criteria - Read
{{KIRO_DIR}}/settings/templates/specs/tasks.mdfor format (supports(P)markers)
Parallel Research
The following research areas are independent and can be executed in parallel:
- Context loading: Spec documents (requirements.md, design.md), steering files
- Rules loading: tasks-generation.md, tasks-parallel-analysis.md, tasks template
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 · +3 lines 904df94bd003
- 1mo ago Changed · +1 lines 8dbe7be7d785
- 1mo ago First seen · 193 lines · 12 tokens per session scan A 03993aaa68a3
kiro-spec-tasks is a skill published in the GitHub repository gotalab/cc-sdd (3,738 stars, last pushed 3d ago), licensed MIT. It adds 12 tokens to every session and 2,363 once invoked, about $0.0000 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.
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.
decision-interview
Ask the minimum decision questions needed before turning the task into canonical implementation rules, on behavior, data integrity, rollout safety, or test strategy. Use when missing information is decision-driven (not factual) or undecided policy blocks planning; in an attended chain it records an open decision as…
implementation-plan
Define an incremental plan for the active task as IMPLEMENTATIONPLAN.md plus a TASKSTATE.md update: smallest safe slices with scope, validation and exit criteria. No code is written. A --spec mode derives slices from a spec or PRD. A retrofit mode annotates in-progress plans so they can adopt implement-fleet. Do not…
slice-closure
Decide whether the current slice is ready to close, separating slice completion from task completion, and record the result in slice notes and TASKSTATE.md. Use when a slice was implemented, validated or reviewed and may be ready to close. Do not use before slice implementation, during planning, or for overall task…
task-close
Close a whole finished task: verify the spec done-conditions, set TASKSTATE.md to its final closed state, and move the folder from active/ to archive/. Use when all slices are closed, the work is merged or explicitly waived, and the task is ending. Do not use for one slice (use slice-closure), unfinished work…
autonomous-run
Run one approved task in one supervised session with the direct-use reference dispatcher, delegating verifiable slices to existing commands and emitting PROPOSED diffs only and never creating commits or attestation refs. Use when a maintainer invokes Fhorja directly after approve-plan and a BOOT verdict from…