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Agent skill

Issue Creator

by termio-sh in termio-sh/termio

Turn vague customer or user feedback from pasted text, chat excerpts, or screenshots into a clear, evidence-backed GitHub issue without inventing requirements.

MITAuto-check passedDevelopment

Install Issue Creator

skills CLI
$ npx skills add termio-sh/termio --skill issue-creator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install termio-sh/termio issue-creator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/termio-sh/termio.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/issue-creator .claude/skills/issue-creator && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
issue-creator
GitHub stars
540
Token cost
~1.7k tokens
SKILL.md length
788 words
Files
3 (incl. references)
Skills in repo
19
Repo updated
First seen
Licence
MIT

At a glance

Turn vague customer or user feedback from pasted text, chat excerpts, or screenshots into a clear, evidence-backed GitHub issue without inventing requirements.

  • Works in 9 steps: Normalize the raw input → Resolve repository conventions → Ground the request in the product → …
  • The user says create an issue for this
  • SKILL.md covers Workflow and Quality gate
  • Calls gh and rg

What it does

Issue Creator is an agent skill from termio-sh/termio. 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.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/images.md` and `references/templates.md`).

It sits in Development, covering Issue triage. It works with GitHub. The repository describes itself as: A terminal-first agentic development environment for agentic coding. Build for CLI/TUI agent. Runtime for Coding Agent, Tmux alternative. The licence is MIT.

When your agent uses it

  • The user says create an issue for this
  • Turn this user request into an issue
  • File this feedback
  • 把这个模糊需求变成 issue

Example prompts

  • “create an issue for this”
  • “turn this user request into an issue”
  • “file this feedback”
  • “/issue-creator”

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. Normalize the raw input
  2. Resolve repository conventions
  3. Ground the request in the product
  4. Apply the clarification gate
  5. Classify honestly
  6. Search for duplicates
  7. Draft a problem-first issue
  8. Attach evidence when present
  9. Create and verify

What it can do on your machine

Read from SKILL.md and the folder at commit af3b35b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • gh
    • rg

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use gh, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Issue Creator loads about 1.7k tokens when it runs, and up to ~3.2k if it reads all its reference files. Until then it costs about 94 tokens; SKILL.md has 788 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~94
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from termio-sh/termio at commit af3b35b, republished under its MIT licence (© termio-sh). 788 words, ~1,691 tokens.

Download SKILL.mdSave it as .claude/skills/issue-creator/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
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:

FieldExtract
ActorWho experiences this?
SituationWhen and where does it happen?
FrictionWhat is hard, broken, or missing now?
Desired outcomeWhat should the user be able to achieve?
ImpactWhy does it matter?
Explicit constraintsWhat did the user actually require?
UnknownsWhat 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:

bash
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:

bash
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
TypeUse when
BugExisting behavior contradicts expected or documented behavior
Feature/usabilityA clear user outcome is unsupported or unnecessarily hard
DiscoveryThe need is real but the right behavior or scope still requires investigation
No new issueExisting 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.

Show full SKILL.md (315 more words)Show less
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.
bash
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, 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 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:

bash
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:

bash
gh issue view ISSUE_NUMBER --repo OWNER/REPO \
  --json number,title,state,url,body,labels

Confirm the intended repository, title, body, evidence links, and metadata. Return the issue URL plus any assumptions or open questions retained in it.

Quality gate

Do not create the issue until all applicable checks pass:

  • The original request is represented faithfully.
  • The core problem and desired outcome are understandable.
  • Facts and inference are distinguishable.
  • No behavior, scope, or acceptance criterion was invented.
  • Existing docs/code and likely duplicate issues were checked.
  • The issue is actionable, or explicitly scoped as discovery.
  • Supplied evidence is embedded and safe for the repository's visibility.
  • The issue follows repository templates and conventions.

© termio-sh, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/issue-creator of termio-sh/termio.

  • SKILL.md
  • references/images.md
  • references/templates.md

Open the folder on GitHubat commit af3b35b

Compare with similar skills

Issue Creator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Issue Creator compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Issue Creator this skilltermio-sh/termio540—~1.7kAutomated safety check: PassMIT
Setup Matt Pocock Skillsbestofjs/bestofjs3.1k20 repos~1.7kAutomated safety check: PassMIT
Windows App SDK Issue Triage Reportmicrosoft/WindowsAppSDK4.7k—~3.4kAutomated safety check: PassApache-2.0
Exposed Bug Fix WorkflowJetBrains/Exposed9.3k—~3.8kAutomated safety check: PassApache-2.0
Pre-Release PR Triagejamiepine/voicebox57k—~3.1kAutomated safety check: PassMIT
WinAppSDK Triage Meeting Prepmicrosoft/WindowsAppSDK4.7k—~2.8kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Issue Creator

What does Issue Creator do?

Turn vague customer or user feedback from pasted text, chat excerpts, or screenshots into a clear, evidence-backed GitHub issue without inventing requirements. Issue Creator is an agent skill from termio-sh/termio. Turn vague customer or user feedback from pasted text, chat excerpts, or screenshots into a clear, evidence-backed GitHub issue without inventing requirements.

When should I use Issue Creator?

Issue Creator fits situations like: the user says create an issue for this; turn this user request into an issue; file this feedback; 把这个模糊需求变成 issue.

How do I install Issue Creator in Claude Code?

Run `npx skills add termio-sh/termio --skill issue-creator -a claude-code`. Or copy the skill folder (skills/issue-creator in termio-sh/termio) into .claude/skills/issue-creator in your project. Claude Code loads it when a task matches its description.

How do I install Issue Creator in Codex?

Run `npx skills add termio-sh/termio --skill issue-creator -a codex`. Or copy the skill folder (skills/issue-creator in termio-sh/termio) into .agents/skills/issue-creator in your project. Codex loads it when a task matches its description.

Can I use Issue Creator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add termio-sh/termio --skill issue-creator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/issue-creator, .gemini/skills/issue-creator, .github/skills/issue-creator and .opencode/skills/issue-creator in your project.

What does Issue Creator need to run?

Going by SKILL.md and its folder, Issue Creator needs the command-line tools its instructions call (gh and rg).

Does Issue Creator access the network?

SKILL.md contains no URLs. Its commands use gh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Issue Creator safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Issue Creator use?

Issue Creator is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Issue Creator use?

About 1.7k tokens (SKILL.md is roughly 6.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.5k tokens, read only when the agent opens those files.

What are the alternatives to Issue Creator?

Skills that share tags, products or a category with Issue Creator: Setup Matt Pocock Skills (bestofjs/bestofjs, 3.1k stars), Windows App SDK Issue Triage Report (microsoft/WindowsAppSDK, 4.7k stars), Exposed Bug Fix Workflow (JetBrains/Exposed, 9.3k stars) and Pre-Release PR Triage (jamiepine/voicebox, 57k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Issue Creator?

termio-sh (a GitHub organization) maintains it in termio-sh/termio, which has 540 GitHub stars. The repository holds 19 skills in this directory. The repository was last updated on October 7, 2026.

Source: termio-sh/termio on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.