Borrowing it
Nothing to install: this file belongs to nerds-odd-e/doughnut. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/nerds-odd-e/doughnut/main/.agents/skills/story-refinement/SKILL.mdgit clone --depth 1 https://github.com/nerds-odd-e/doughnutWrote 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/nerds-odd-e/doughnut/story-refinement)<a href="https://agentmods.dev/skills/nerds-odd-e/doughnut/story-refinement"><img src="https://agentmods.dev/badge/skills/nerds-odd-e/doughnut/story-refinement.svg" alt="Measured on agentmods" 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 | $0.00059 | $0.00613 |
| Opus 5 | $0.00030 | $0.00307 |
| Sonnet 5 | $0.00012 | $0.00123 |
| Haiku 4.5 | $0.00006 | $0.00061 |
Grade A, and why
story-refinement 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Story Refinement
Build shared understanding of one selected story, or several related stories
whose boundaries need discussion. Follow .cursor/rules/planning.mdc for scope
discipline and lifecycle. Resolve repository paths from the checkout containing
this skill.
Refine through conversation
Read the selected stories and relevant prior discussion. Reuse answers already given; ask only questions that change understanding, with a concise proposed answer. Do not turn the following into a questionnaire or mandatory approval ceremony. Mark unresolved decisions explicitly; do not present proposals as developer decisions.
For each story, establish:
- Goal: beneficiary, desired change, and its contribution to the business goal. Keep this story's observable outcome distinct from the broader ambition.
- Scope: included behavior, relevant exclusions, and boundary assumptions. Prefer the smallest useful outcome; exclude uncertain additions and report them. Clarify when exclusion would prevent the stated outcome from working.
- Key examples: concrete pre-condition → trigger → result situations that explain the scope. Include boundaries or exceptions when they resolve ambiguity; do not enumerate a complete test suite.
Add UI descriptions or sketches only when interaction or presentation needs
agreement. Add Architecture only for a new consequential concern; consult
adr-awareness and relevant Accepted ADRs. Inspect existing behavior or code
only to resolve a concrete question, without turning refinement into technical
planning. Omit unused optional sections.
A story may cross features. When refining several stories, keep each outcome and boundary separate; do not merge them into one delivery by implication. Use story-decomposition if the parent problem or candidate selection needs reconsideration.
Keep the understanding in the story's home
Expand each existing story section in its home seed with Goal, Scope,
and Key examples, plus optional details above. Replace overlapping detail;
preserve story anchors, sibling stories, and seed metadata. Record only open
questions that affect this story. If no home exists, establish one under
.planning/seeds/ using the story-decomposition seed format.
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 First seen · 64 lines · 59 tokens per session scan A c01f78afe5f0
story-refinement is a skill published in the GitHub repository nerds-odd-e/doughnut (49 stars, last pushed yesterday), licensed MIT. It adds 59 tokens to every session and 613 once invoked, about $0.0003 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 2026-09-06.
Other skills, from other repositories
recipe-create-meet-space
Create a Google Meet meeting space and share the join link.
atmos-config
Atmos root configuration: atmos.yaml discovery, precedence, deep merging, basepath, imports, minimal bootstrap, and routing to narrower Atmos skills.
workthreads
SpecStory Workthreads - a weekly work-thread rollup across a team's repos from SpecStory coding histories (any agent - Claude Code, Codex, Cursor, Gemini, and more). It groups the window's sessions into threads of work per project and labels each new / open / recently closed, so a lead sees what shipped, what is still…
story-readiness
Validate that a story file is implementation-ready. Checks for embedded GDD requirements, ADR references, engine notes, clear acceptance criteria, and no open design questions. Produces READY / NEEDS WORK / BLOCKED verdict with specific gaps. Use when user says 'is this story ready', 'can I start on this story', 'is…
autotask-creator
Rules for automation CRUD from the group-chat commander. The commander does not call mutation tools and does not edit cloud/autotasks files directly. It emits one or more top-level ... containers in its final text; the bus parses and applies them after the turn.
monorepo-management
Master monorepo management with Turborepo, Nx, and pnpm workspaces to build efficient, scalable multi-package repositories with optimized builds and dependency management. Use when setting up monorepos, optimizing builds, or managing shared dependencies.