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BA ticket-authoring

Write complete, ready-to-pull work items for an issue tracker: bugs, tasks, stories, spikes, and epics, each with the fields, attachments, and done test its type requires. Use this skill whenever the user wants to write a ticket, create a Jira issue, Linear issue, or GitHub issue, file a bug report, write a user story or acceptance criteria, scope a spike, open an epic, or break work into tasks. Triggers on write a ticket, create an issue, file a bug, bug report, user story, spike, epic, task breakdown, turn this into tickets, break this down, acceptance criteria, definition of ready, ready for dev, backlog item, capitalization stage. Also triggers when the user pastes a PRD, a spec, or a bug description and asks what to do with it, even if they never say the word ticket.

rampstackco/claude-skills Agent Skills author: rampstackco 9 files body ≈ 2 382 tokens Open the sourcegithub.com↗ analyzed 7 h ago

Write complete, ready-to-pull work items for an issue tracker: bugs, tasks, stories, spikes, and epics, each with the fields, attachments, and done test its…

As a process A 83/100 · Runs to the end — weak spots: running it twice, progress reporting

GeneratorGitHubJiraLinearPersonal productivitytype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
A
83/100
Runs to the end
Progress reporting w 2
0
Running it twice w 4
30
Failures and branches w 10
50
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: ticket-authoring (rampstackco/claude-skills)

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "catalog_summary"
    • note frontmatter-key unknown frontmatter key "display_order"

    Process rating: all ten parameters 83/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 80 steps
    • 100Result and completion. Output format and completion criterion are stated
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2382 tokens

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 782: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 80 items
    • +3Output format is stated explicitly
    • +4Reference files are cited in the instructions (8 of 8)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.