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.
git clone --depth 1 https://github.com/miyatti777/ai-plcWrote 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/commands/miyatti777/ai-plc/spec-story-starter)<a href="https://agentmods.dev/commands/miyatti777/ai-plc/spec-story-starter"><img src="https://agentmods.dev/badge/commands/miyatti777/ai-plc/spec-story-starter/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/commands/miyatti777/ai-plc/spec-story-starter"><img src="https://agentmods.dev/badge/commands/miyatti777/ai-plc/spec-story-starter.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 | $0.00044 | $0.00224 |
| Opus 5.5 | $0.00018 | $0.00090 |
| Sonnet 5.5 | $0.00009 | $0.00045 |
| Haiku 4.5 | $0.00004 | $0.00022 |
Grade A, and why
spec-story-starter 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 18d 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.
What it actually says
Read the skill at .claude/skills/utility/spec-story-starter/SKILL.md and execute it.
Input: $ARGUMENTS
必須入力(source / feature_label)が不足している場合は、実行前にユーザーへ確認する。target_repo / backlog_db_url / spec_output / detail_level は任意(未指定時はスキルの既定に従い、出力先は Flow/[YYYYMM]/[YYYY-MM-DD]/[feature_label]/)。
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.
- 18d ago First seen · 12 lines · 44 tokens per session scan A 438a297c1049
spec-story-starter is a command published in the GitHub repository miyatti777/ai-plc (49 stars, last pushed 17d ago), licensed MIT. It adds 44 tokens to every session and 224 once invoked, about $0.0002 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 2026-09-30.
Other commands, from other repositories
template
Manage issue templates for streamlined issue creation.
fest-show
Show festival progression (in-progress tasks, roadmap, and dependency view).
add-note
Add an internal or external note to a ConnectWise PSA ticket.
sync-linear
Sync current work with Linear ticket status.
dispatcher
Use when you want the orchestrator to pick the next repo to work on across your whole portfolio — it enumerates candidate repos below the confinement root, resolves free/busy from each repo's session.lock lease, ranks the FREE ones by backlog priority × staleness × readiness, recommends the single most worthwhile one…
workpm
A project-management workflow for coordinating multiple AI workers through five stages. It includes task assignment, shared activity logs, worker replacement, and final checks.