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 benjaminthomas/spec-driven-dev --skill spec-creategit clone --depth 1 https://github.com/benjaminthomas/spec-driven-devWrote 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/benjaminthomas/spec-driven-dev/spec-create)<a href="https://agentmods.dev/skills/benjaminthomas/spec-driven-dev/spec-create"><img src="https://agentmods.dev/badge/skills/benjaminthomas/spec-driven-dev/spec-create/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/benjaminthomas/spec-driven-dev/spec-create"><img src="https://agentmods.dev/badge/skills/benjaminthomas/spec-driven-dev/spec-create.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00118 | $0.01520 |
| Opus 5.5 | $0.00047 | $0.00608 |
| Sonnet 5.5 | $0.00024 | $0.00304 |
| Haiku 4.5 | $0.00012 | $0.00152 |
Grade A, and why
spec-create 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.
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Feature Specification
Transform a planning conversation into a structured spec folder that enables parallel agent implementation. The spec breaks a feature into self-contained task files — each one detailed enough that a coder agent can pick it up cold and implement it without reading anything else.
The key insight: implementation plans that live in a single file are either too large for a context window or too shallow for independent execution. By splitting into one file per task with full context in each, we enable multiple agents to work in parallel while keeping each agent's context focused.
When to Use
- After a planning conversation where requirements and technical details have been discussed
- When the user asks to create a spec, plan a feature, or break work into tasks
- When the user wants to prepare work for parallel agent implementation
Instructions
Step 1: Gather Requirements
If the conversation already contains planning context (requirements discussed, technical decisions made, architecture outlined), extract all of it. Review the entire conversation to ensure nothing is lost — the spec is the single source of truth, and anything not captured here disappears.
If no planning conversation exists, interview the user:
- What does this feature do and why does it matter?
- What are the acceptance criteria?
- What technical constraints or decisions have been made?
- What files, APIs, schemas, or patterns are involved?
Step 2: Name the Feature
Choose a kebab-case name that clearly identifies the feature (e.g., add-user-auth, migrate-to-postgres, dashboard-redesign). This becomes the folder name under specs/.
Step 3: Decompose into Tasks
Break the implementation into atomic tasks. Each task should:
- Be completable in a single coding session by one agent
- Have a clear, specific scope (one concern per task)
- Produce working, testable code when complete
- Not overlap in files modified with other tasks in the same batch
What ships with it
4 files 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 · 135 lines · 118 tokens per session scan A d247dd66c9cd
spec-create is a skill published in the GitHub repository benjaminthomas/spec-driven-dev (1 stars, last pushed 2mo ago), licensed MIT. It adds 118 tokens to every session and 1,520 once invoked, about $0.0005 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 2026-08-31.
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