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Agent Orchestration
Skill

/issue-creator

Turn vague customer or user feedback from pasted text, chat excerpts, or screenshots into a clear, evidence-backed GitHub issue without inventing requirements. Use when the user says 'create an issue for this', 'turn this user request into an issue', 'file this feedback', '用户反馈建

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termio
54428 skills
Install
$ npx -y skills add termio-sh/termio --skill issue-creator --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/issue-creator

Context preview

The summary Claude sees to decide when to auto-load this skill.

Turn vague customer or user feedback from pasted text, chat excerpts, or screenshots into a clear, evidence-backed GitHub issue without inventing requirements. Use when the user says 'create an issue for this', 'turn this user request into an issue', 'file this feedback', '用户反馈建

SKILL.md

issue-creator.SKILL.md
name: issue-creator
description: "Turn vague customer or user feedback from pasted text, chat excerpts, or screenshots into a clear, evidence-backed GitHub issue without inventing requirements. Use when the user says 'create an issue for this', 'turn this user request into an issue', 'file this feedback', '用户反馈建 issue', '把这个模糊需求变成 issue', '把这段聊天/截图建成 GitHub issue', or invokes /issue-creator."

Vague user request → actionable GitHub issue

Preserve the user's voice, identify the underlying problem, add only grounded repository context, and create the smallest honest issue that moves the work forward. Never turn missing information into confident requirements.

Workflow

1. Normalize the raw input

Handle all three input modes:

  • **Pasted text:** preserve the most useful original sentence verbatim.
  • **Screenshot:** inspect both visible text and UI context. Transcribe only what

is legible and mark uncertainty. Keep the original image for `Evidence`.

  • **Mixed:** treat the pasted explanation as context and the screenshot as

primary evidence unless they conflict; surface any conflict.

Build a private scratch intake before drafting:

| Field | Extract | |---|---| | Actor | Who experiences this? | | Situation | When and where does it happen? | | Friction | What is hard, broken, or missing now? | | Desired outcome | What should the user be able to achieve? | | Impact | Why does it matter? | | Explicit constraints | What did the user actually require? | | Unknowns | What remains unclear? |

Do not force the request into “As a user, I want…” language. Preserve a direct quote when it expresses the pain better than a summary.

If the message is phrased as a question, identify the latent need but first check whether existing behavior or documentation already answers it. Do not file a feature request for something the product already supports.

2. Resolve repository conventions

Use an explicitly named repository; otherwise resolve the current checkout:

gh auth status
gh repo view --json nameWithOwner,defaultBranchRef,visibility,hasIssuesEnabled
gh issue list --state all --limit 10 --json number,title,state,url
rg --files -g 'CONTRIBUTING*' -g '.github/ISSUE_TEMPLATE/**'

Read any relevant issue template or contributing guide. Match the repository's language, headings, title style, and metadata conventions. Do not invent labels, types, milestones, or assignees.

3. Ground the request in the product

Do light, targeted exploration using nouns, UI labels, errors, and capability names from the intake. Search README/docs first, then likely code:

rg -n -i 'user phrase|normalized capability|visible UI label' \
  README.md docs Sources Shared ios web 2>/dev/null

Stop when there is enough context to name the affected area, identify existing behavior, or determine that this is a product-level discovery request. Code exploration is context gathering, not implementation planning.

4. Apply the clarification gate

Ask at most three focused questions, and only when an answer would change one of:

  • whether an issue should exist;
  • bug vs feature/discovery classification;
  • the core problem or desired outcome;
  • reproduction of a bug;
  • a material scope boundary;
  • whether evidence is safe to publish.

First try to answer gaps from the screenshot, repository, docs, and related issues. Do not ask the user to design the solution or manufacture acceptance criteria. Put non-blocking uncertainty in `Open questions` and continue.

5. Classify honestly

| Type | Use when | |---|---| | Bug | Existing behavior contradicts expected or documented behavior | | Feature/usability | A clear user outcome is unsupported or unnecessarily hard | | Discovery | The need is real but the right behavior or scope still requires investigation | | No new issue | Existing behavior/docs solve it, or a strong duplicate already tracks it |

When feedback is too broad for an implementation issue, create a bounded discovery issue such as “Define task-completion notification behavior” instead of inventing a complete solution.

6. Search for duplicates

Run separate searches using:

1. the user's exact phrase; 2. the normalized product capability; 3. the symptom or desired outcome.

gh issue list --repo OWNER/REPO --state all \
  --search 'query in:title,body' --limit 20 \
  --json number,title,state,url

If a strong duplicate exists, return it instead of creating another issue. If the overlap is partial, create the new issue and link the related one.

7. Draft a problem-first issue

Read [references/templates.md](references/templates.md), choose the matching template, and omit empty sections.

Follow these rules:

  • Write a direct, scannable title under 72 characters.
  • Separate original evidence, verified facts, and inference.
  • Describe the problem and desired outcome before any possible solution.
  • Include the user's original words as a short quote when useful.
  • Add file/component references only when verified by repository exploration.
  • Write acceptance criteria only for observable behavior supported by the

request or established product conventions.

  • Put unresolved product decisions under `Open questions`.
  • Keep one issue focused on one outcome; split independent requests.

8. Attach evidence when present

If the input includes one or more images, read [references/images.md](references/images.md) and follow its privacy, upload, and verification workflow. Do not silently drop an image.

9. Create and verify

Before any GitHub write, state the exact repository, proposed title, and any image asset path. Prepare the final Markdown body outside the repository, then:

gh issue create --repo OWNER/REPO \
  --title 'Concise problem or outcome' \
  --body-file /absolute/path/to/temporary-issue-body.md

Use an existing issue type or label only after confirming it exists. Then verify the returned issue:

gh issue view ISSUE_NUMBER --re
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Ships withtermio

A terminal-first agentic development environment for agentic coding. Build for CLI/TUI agent. Runtime for Coding Agent, Tmux alternative

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Repo: termio-sh/termio

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