Fetch Ticket logo

Fetch Ticket

Organization
eai-org
fetch-ticket

Fetch one or more tickets/issues from their tracker (Azure DevOps, Jira, GitHub, …) and save each as a self-contained markdown ticket file. Fetch only — no analysis or planning.

Overview

Publishereai-org
Repositoryagent-toolkit
Skill namefetch-ticket
Stars
80
Forks
18
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by eai-org on GitHub. Read the source before you install it.

Installation

Install the Fetch Ticket AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/eai-org/agent-toolkit/tree/main/skills/fetch-ticket
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/eai-org/agent-toolkit.git /tmp/agent-toolkit
mkdir -p .claude/skills
cp -r /tmp/agent-toolkit/skills/fetch-ticket .claude/skills/fetch-ticket
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fetch Ticket in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Fetch Ticket on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Fetch Ticket is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Ticket Fetcher

Fetch only — no analysis, requirements, or planning. Output is a self-contained .TICKET.md.

Source & access

Identify the tracker from the input (URL host, or id shape) and fetch through the matching MCP server — e.g. Azure DevOps MCP for ADO work items, Atlassian MCP for Jira issues, GitHub MCP / gh for GitHub issues. Use whichever equivalent tools are connected; tool name prefixes vary by config. Resolve once any handle the MCP needs (e.g. Atlassian cloudId, ADO project) and reuse it. A bare id that fits several trackers: the one the project's governing docs name, else the Source host all ticket files in the planning directory share, else the only connected tracker MCP; still open → ask, naming your pick. If no matching MCP is connected: a public ticket may be scraped from its URL as a fallback (you may still suggest installing the matching MCP when it would do the job better); a private one can't — the URL returns a login page, not the ticket — so stop and tell the user to install and authenticate the matching MCP server, then re-run.

Your task

  1. Resolve the input. Accept a full ticket URL or a bare id/key; extract the identifier. If the tracker uses a key prefix (e.g. XX-1234), keep it; otherwise use the bare number. If the input is unrecognizable, ask.

  2. Fetch the ticket. Get the work item/issue with its full field set, comments inline, and related links/relations expanded. Capture everything the ticket carries — don't pre-filter to a fixed set of fields. Convert whatever rich-text form you get (HTML, ADF, …) to clean Markdown.

  3. Pick a slug. Short kebab-case slug, 3–5 words, from the title/summary — greppable, don't overthink it.

  4. Decide the output directory. First resolve the project's planning directory: the one its governing docs name or already in use, default .agents/plans/. Inside it, first match wins:

    1. Re-fetch — the ticket already has a plan directory or flat .TICKET.md: write to the next <id>-<slug>-v2, -v3, … name beside it, the file named like its directory (<id>-<slug>-vN/<id>-<slug>-vN.TICKET.md, or flat <id>-<slug>-vN.TICKET.md), and say so in the result — never overwrite; history per re-fetch is kept on purpose.
    2. Existing family — an ancestor (parent/epic, nearest first) has a plan directory (<ancestor-id>-*, hyphen included; confirm via its .TICKET.md that it's really that ancestor's; latest -vN when several), or a group directory's ## Ticket set lists this ticket or a sibling: write flat into it (<dir>/<id>-<slug>.TICKET.md) and update the ## Ticket set sections per multiple-tickets.md.
    3. Otherwise — a new <id>-<slug>/ subdirectory.

    In doubt at any point (unsure a directory is really the family's, …): ask the user, proposing the answer you would pick. Never guess — better one extra question than a potential mistake.

  5. Write the ticket file at <output-dir>/<id>-<slug>.TICKET.md, <id>-<slug>-vN.TICKET.md on a re-fetch.

  6. Download attachments — if the ticket carries attachments, inline images, external linked assets, or design-tool links, read attachments.md first, then download into the output directory; warn on any that fail.

  7. Print the result — project-relative paths and the next-step line (see Next step).

Multiple tickets

The input may list several tickets — before picking slugs and directories, read multiple-tickets.md: it governs grouping into shared directories, the ## Ticket set section, and per-ticket launch commands.

Ticket file structure

Must stand on its own: a complete, readable version of the ticket with enough metadata that a fresh session can identify the source without re-fetching.

Header

Plain markdown header with source metadata; omit any line whose value is absent. Include whatever the tracker provides. Example:

markdown
# <title / summary>

> **Source** [<id>](<url>)
> **Type** {type}
> **Status** {status}
> **Assignee** {display name or "—"}
> **Reporter / Created by** {display name}
> **Labels / Tags** {joined or "—"}
> **Fetched** {today YYYY-MM-DD}

Body sections

A grouped ticket's ## Ticket set comes first, directly after the header — see multiple-tickets.md. Then, in this order, only if present and non-empty:

  1. ## Description
  2. ## Acceptance criteria — if the tracker has a dedicated AC field populated
  3. ## <Other fields> — one section per other populated field carrying real content (technical notes, custom fields, …), headed by the field's display name. Capture everything the ticket holds.
  4. ## Comments — oldest first, each ### <author> — <date> then the body. Best-effort: if comments aren't returned, note it briefly or omit the section.
  5. ## Related tickets — see below
  6. ## Attachments — see attachments.md
  7. ## Design references — see attachments.md

Preserve heading hierarchy, bullet structure, emphasis, and code blocks; map in-field subheadings to ####. Omit empty sections. Quote user-facing strings, code identifiers, file paths, i18n keys, and URLs verbatim — never alter or translate them.

Related tickets

From the response's links/relations (and any remote-link tool), for each unique linked ticket (excluding this one) fetch only title + status + type via a cheap call — not the full body. The main goal is that there is a trace of all related tickets, so they can be fetched later if needed. One bullet each, with the relationship if available:

markdown
- [<id>](<url>) — (<type>, <status>) <title>

For non-ticket remote links (e.g. a wiki/Confluence page), emit the title and URL as a plain bullet. If a fetch fails, list the link with (unable to fetch) rather than failing the whole run.

Attachments & design references

The full protocol — numbering, cross-MCP fetching, auth, fallback recipes, integrity checks, and entry templates — lives in attachments.md. Three rules always hold:

  1. Attachments include inline images in the description/fields, external linked assets, and design-tool links — not just tracker-hosted files.
  2. Download each straight to disk (e.g. curl -fSL <url> -o <file>); never route one as inline base64 through the model — output caps truncate it silently.
  3. A file you cannot fetch is still referenced with its source URL and added to the warn list — never block.

Boundaries

  • Do not analyze, plan, or explore the codebase for context — this does not exempt files the ticket explicitly links, which you still fetch (see attachments.md).
  • Do not modify the ticket in its tracker — fetching is read-only (no comments, transitions, edits, worklogs).
  • The only files you create: the .TICKET.md, its attachments, and any linked docs you fetched; the only edits to existing files are group members' ## Ticket set sections.

Next step

State clearly when done, using project-relative paths (never absolute): the output directory, the ticket file, and any attachments. If any attachment or design preview could not be downloaded, first emit a clear warning headed by ⚠️ listing each missing file's name and its source URL, instructing the user to download it and save it under that exact name so the embeds resolve — or, with /attach-to-ticket available, to paste it (or its saved path) and run that skill. Without refine-ticket available the result ends there; with it, hand off the next phase as a single copy-pasteable launch command in a fenced block — session name and prompt combined, so one paste starts the session — in the launch syntax of the agent tool in use (vendor-agnostic — claude below is only the example), naming the session refine-<slug>; several tickets → one block per ticket, in the suggested execution order, under a label naming it:

claude --name refine-<slug> "/refine-ticket <output-dir>/<id>-<slug>.TICKET.md"

Then offer the alternative: one line offering to clear the current session (vendor-agnostic — /clear is only the example; use the clear command of the agent tool in use) and run the next phase here, then the same block(s) with the bare prompt:

/refine-ticket <output-dir>/<id>-<slug>.TICKET.md

On a re-fetch, when the highest earlier version (-v(N-1) … down to the unsuffixed <id>-<slug>) already has a .REQUIREMENTS.md: say those requirements predate the re-fetch and put that .REQUIREMENTS.md in both commands in place of the new ticket file (session still refine-<slug>), noting that refining from scratch means running refine-ticket on the new .TICKET.md instead.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Fetch Ticket AI skill do?

Fetch one or more tickets/issues from their tracker (Azure DevOps, Jira, GitHub, …) and save each as a self-contained markdown ticket file. Fetch only — no analysis or planning.

Why use Fetch Ticket on TypingMind?

Because you install it once and use it with any model. Fetch Ticket is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Fetch Ticket in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/eai-org/agent-toolkit/tree/main/skills/fetch-ticket. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Fetch Ticket?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Fetch Ticket?

As many as you like. As long as a model supports skills, you can use Fetch Ticket with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Fetch Ticket AI skill free?

Yes. It is published on GitHub by eai-org under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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