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 tottinge/otter-skills --skill user-pov-sliced-storiesgit clone --depth 1 https://github.com/tottinge/otter-skillsWrote 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/tottinge/otter-skills/user-pov-sliced-stories)<a href="https://agentmods.dev/skills/tottinge/otter-skills/user-pov-sliced-stories"><img src="https://agentmods.dev/badge/skills/tottinge/otter-skills/user-pov-sliced-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/tottinge/otter-skills/user-pov-sliced-stories"><img src="https://agentmods.dev/badge/skills/tottinge/otter-skills/user-pov-sliced-stories.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 | $0.00084 | $0.00676 |
| Opus 5 | $0.00042 | $0.00338 |
| Sonnet 5 | $0.00017 | $0.00135 |
| Haiku 4.5 | $0.00008 | $0.00068 |
Grade A, and why
user-pov-sliced-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 12d 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User POV Sliced Stories
Role of this skill
This skill is a formatter, not a splitter. It translates an existing admission plan into user-visible invoke/result language.
Primary splitting — choosing the admission boundary, sequencing slices, writing Slice 0, bargain-hunting the next case — belongs in story-splitting-for-delivery.
Apply this skill after that plan exists, or when the user specifically asks for user-observable wording.
Build slices as user-visible behavior
Define each slice as an end-to-end behavior a user can trigger and benefit from immediately. Avoid component-only splits (UI-only, API-only, DB-only). Each slice must be independently demoable.
Workflow
- If no admission plan exists yet, create one with
story-splitting-for-deliveryfirst. - Restate the capability in customer terms: who, behavior change, value now.
- For each admission slice, write the user-visible invoke/result pair (see format below).
- Keep slices small — typically 1–3 days.
- Define concrete acceptance examples before implementation.
- Re-split after each delivered slice based on feedback.
Required output format
For each slice, always produce:
Slice N — <short user-facing title>
- User invokes: <exact command, UI action, API call, or trigger>
- User uses result: <observable value/output the user consumes immediately>
- Acceptance checks: <2–4 testable checks>
- Not yet in this slice: <explicitly deferred scope>
Sequencing rules
- Deliver 2–5 slices at a time.
- Put the safest value slice first.
- Put highest uncertainty reduction in slice 1 or 2.
- Keep later slices negotiable; do not over-specify implementation.
Quality gate before finalizing slices
Confirm each slice:
- is demoable to a stakeholder
- provides value or learning even if work stops afterward
- is testable independently
- remains vertical and user-observable
- is small enough for fast feedback
Response style
- Write from user POV, not component POV.
- Prefer concrete invocation language: command name, button label, menu path, API endpoint.
- Keep each slice concise and high signal.
- If the plan uses technical admission language, translate it — do not copy paste implementation details.
What ships with it
1 file 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.
- 12d ago First seen · 63 lines · 84 tokens per session scan A bb6d65f7e3ab
user-pov-sliced-stories is a skill published in the GitHub repository tottinge/otter-skills (3 stars, last pushed 4d ago), licensed Apache-2.0. It adds 84 tokens to every session and 676 once invoked, about $0.0004 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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