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/studioKjm/ai-harness-templateWrote 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/studiokjm/ai-harness-template/story)<a href="https://agentmods.dev/commands/studiokjm/ai-harness-template/story"><img src="https://agentmods.dev/badge/commands/studiokjm/ai-harness-template/story/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/studiokjm/ai-harness-template/story"><img src="https://agentmods.dev/badge/commands/studiokjm/ai-harness-template/story.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 | $0.00022 | $0.01039 |
| Opus 5 | $0.00011 | $0.00519 |
| Sonnet 5 | $0.00004 | $0.00208 |
| Haiku 4.5 | $0.00002 | $0.00104 |
Grade A, and why
story 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/story — Create or Refine a User Story
Convert a fuzzy feature ask into a structured, testable story.
When to use
- After
/seedexists and you're about to implement a new feature - When a backlog item is too vague to start coding
- Before
/decompose— story output feeds into task decomposition
Usage
/story new <slug> # Create new story (interactive)
/story refine <story-id> # Run pm-strict against existing story
/story show <story-id> # Print story
/story list [epic-id] # List stories (filter by epic)
/story link <story-id> <epic-id> # Attach to epic
Prerequisites
- Seed exists at
.harness/ouroboros/seeds/seed-vN.yaml - (Optional) Active persona for richer output. Recommend running:
/persona analyst # to populate analyst_notes /persona ux-designer # if story has UI surface /persona pm-strict # to validate before marking refined
Instructions
Step 1 — Generate story ID
st-YYYY-MM-DD-<slug>. Path: .harness/bmad-lite/stories/<id>.yaml.
Step 2 — Bootstrap from template
Copy templates/story.yaml to the new path. Fill in:
id,created_at,seed_versionnarrative(required — ask user if missing)- At least one
acceptance_criteriaentry
Step 3 — Run analyst pass (if persona active)
If active persona == analyst:
- Read seed, identify entities the story touches
- Populate
analyst_notes - Flag ambiguities — if > 3, advise: "Run /interview before continuing"
Step 4 — Run ux-designer pass (if persona active)
If active persona == ux-designer AND story has UI surface:
- Populate
ux_noteswith flow summary, states, primitives - Default to existing components in the codebase
Step 5 — Run pm-strict validation
ALWAYS run pm-strict at the end of /story new or /story refine:
Check each gate:
narrative.persona,.capability,.outcome— all present, no nullsacceptance_criteriacount ≥ 1- Each AC has
given,when,thenfilled - No weasel words (fast / easy / intuitive / robust / secure / scalable / user-friendly) unless paired with a metric or behavior
- Story scope is single deployable increment (no "and also" in narrative)
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 · 125 lines · 22 tokens per session scan A 7467b9083d09
story is a command published in the GitHub repository studioKjm/ai-harness-template (43 stars, last pushed 3mo ago), licensed MIT. It adds 22 tokens to every session and 1,039 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 commands, from other repositories
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show-lessons
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harness-review
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step0-specify-feature
Pipeline Step 0 — Specify what you want to build and why, before any technical planning. Surfaces ambiguities early with [NEEDS CLARIFICATION] markers.
harness-update
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harness-doctor
Run Harness Doctor to evaluate how ready the current repository is for reliable AI coding agent collaboration.