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 jstoup111/ai-conductor --skill storiesgit clone --depth 1 https://github.com/jstoup111/ai-conductorWrote 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/jstoup111/ai-conductor/stories)<a href="https://agentmods.dev/skills/jstoup111/ai-conductor/stories"><img src="https://agentmods.dev/badge/skills/jstoup111/ai-conductor/stories/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/jstoup111/ai-conductor/stories"><img src="https://agentmods.dev/badge/skills/jstoup111/ai-conductor/stories.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 | $0.00045 | $0.02928 |
| Opus 5 | $0.00023 | $0.01464 |
| Sonnet 5 | $0.00009 | $0.00586 |
| Haiku 4.5 | $0.00005 | $0.00293 |
Grade A, and why
stories 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 yesterday.
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 — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Generates granular stories with happy and negative path scenarios, and is the always-present acceptance-criteria artifact for both tracks:
- Product track — extract stories from the approved PRD's enumerated functional requirements
(
FR-N); each FR is a unit. - Technical track — no PRD; write technical stories (Given/When/Then against the technical change) from the technical intent + the approved architecture.
Stories run after architecture-review (the design is known), so they describe behavior (WHAT) grounded in the agreed design — but they state observable behavior/acceptance, NOT the mechanism (architecture informs which scenarios exist; it is not copied as mechanism into story text — the how is the plan's job). Negative paths are mandatory — they feed TDD RED phases.
Read the Scope boundary: from .docs/track/<slug>.md as binding; preserve the confirmed narrow/comprehensive breadth outcome; do not permit a materially broader expansion beyond it unless the operator confirms before it enters the artifact.
Correctness gate: acceptance criteria become the definition of done. Apply the /verify-claims
protocol — if a scenario encodes an assumption about expected behavior that was never confirmed
(against the FR, the ADR, or the operator), flag it with its confidence and HARD-BLOCK for approval
(HALT if autonomous) rather than baking the guess into a Given/When/Then.
Architecture-induced negatives (do not miss these): because stories follow architecture, every failure mode a design decision introduces (an external call that times out, a queue that drops/dupes, a lock that contends) MUST appear as a negative-path story. These are exactly the cases that were missed when stories preceded the design.
If writing stories reveals a genuine structural gap the design lacks (a missing component/seam), do
not paper over it in story text — kick back to architecture (which re-opens in amendment mode).
Documentation boundary
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.
- yesterday Changed · +5 lines daa6c0d3830a
- 9d ago First seen · 204 lines · 45 tokens per session scan A 4253df188f3e
stories is a skill published in the GitHub repository jstoup111/ai-conductor (7 stars, last pushed today), licensed Apache-2.0. It adds 45 tokens to every session and 2,928 once invoked, about $0.0002 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 2026-08-31.
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